VITAE...VITAE John Herschell Kalivas Address: Department of Chemistry Idaho State University...

VITAE

John Herschell Kalivas

Address: Department of Chemistry

Idaho State University

Pocatello, Idaho 83209

Phone Number: 208-282-2726

Fax Number: 208-282-4373

E-Mail: [email protected]

Academic Degrees:

1978 B.S., Chemistry, California Polytechnic State University, San Luis Obispo, California,

(graduation with Highest Honors).

1982 Ph.D., Chemistry, University of Washington, Seattle, Washington.

Positions Held: Professor-Idaho State University, 8/94 to present.

Associate Professor-Idaho State University, 8/90 to 7/94.

Assistant Professor-Idaho State University, 1/85 to 7/90.

Lecturer-Texas A&M University, 8/84 to 12/84.

Instructor-Univ. of Minnesota, Morris, 9/83 to 7/84.

Research Associate-University of Washington, 12/82 to 2/83.

Teaching Experience:

University of Washington: Quantitative Labs, General Chemistry Labs, Introduction to Chemistry.

University of Minnesota, Morris: General Chemistry, Instrumental Analysis, Computers in Society.

Texas A&M University: Analytical Chemistry.

Idaho State University: General Chemistry, Advanced Analytical Chemistry, Quantitative Analysis,

Qualitative Analysis, Instrumental Analysis, Chemometrics, Seminar, Independent Problems, Senior

Research, and Master’s Research.

Awards: Fall 1975 to Spring 1978: Dean’s Honor List, Cal Poly, San Luis Obispo.

Fall 1982: Annual Fund Dissertation Fellowship, Univ. of Washington ($1,800)

Summer 1986: Faculty Participant Appointment, Associated Western Universities, Salt

Lake City, Utah ($4,400)

May 1989: Outstanding Researcher, Idaho State University


May 1992: Named by Jon Sutter as being the Most Influential Professor in his college

career as part of his Outstanding Academic Student Achievement in the College of Arts

& Science Award

Fall 1992: Sabbatical leave


May 1994: Distinguished Researcher, Idaho State University ($2,000)

mailto:[email protected]

2

November 1994: Camille and Henry Dreyfus Scholar, Camille and Henry Dreyfus

Foundation, Inc., New York, New York ($60,000)

May 1996: Named by Greg Bakken as being the Most Influential Professor in his college

career as part of his Outstanding Academic Student Achievement in the College of Arts

& Science Award

May 1998: Named by Jason Brenchley as being the Most Influential Professor in his

college career as part of his Outstanding Academic Student Achievement in the College

of Arts & Science Award

May 2000: Named by Steven Fairchild as being the Most Influential Professor in his



Spring 2000: Sabbatical leave

May 2002: Named by Kelly Anderson as being the Most Influential Professor in his



May 2005: Named by Heather Seipel as being the Most Influential Professor in her

college career as part of her Outstanding Academic Student Achievement in the College


Fall 2007/Spring 2008: Sabbatical leave

May 2012: Named by Jeremy Farrell as being the Most Influential Professor in his

college career as part of her Outstanding Academic Student Achievement in the College

of Science and Engineering Award

Professional Activities:

Society Membership

American Chemical Society, 1985–present (Councilor, Idaho Section, 1987-1990)

Society for Applied Spectroscopy, 1980-present (Chair, Intermountain Section, 1989;

Treasure/Secretary, Intermountain Section, 1990; Treasure/Secretary, Snake River Section,

1991-1995)

Sigma Xi, 1985-present (Vice-President ISU Section 1987, President ISU Section 1988)

Idaho Academyof Science, 1985-present

Council on Undergraduate Research, 1992-present

North American Chapter of the International Chemometrics Society, 1991-present

Journal, Editorial/Reviewing

Applied Spectroscopy, (Associate Editor), 2010-present

Applied Spectroscopy, (Editorial Board), 1998-2009

Journal of Chemometrics, (Editor), 2013-present

Journal of Chemometrics, (Editorial Board), 1990-2012

Analytic Letters, (Editorial Board), 1993-present

Talanta (Editorial Board), 2007-present

Analytical Chemistry

Analytica Chimica Acta

Chemometrics and Intelligent Laboratory Systems

Journal of Chemical Education

3

Research Grants:

1. “Error Propagation and Optimal Performance in Multicomponent Analysis”, Faculty Research

Grant, Idaho State University, $2,026 duration 4/85 to 12/85.

2. “Optimization of Derivative Order for Chemical Spectral Analysis Using the Condition Number”,

Faculty Research Grant, Idaho State University, $2,460, duration 4/86 to 4/87.

3. “Multicomponent Spectrophotometric Identification”, Petroleum Research Fund, American

Chemical Society, $18,000, duration 1/87 to 8/89.

4. “Computer Selection of Optimal Wavelengths for Quantitative Analysis of Multicomponent

Systems”, Faculty Research Grant, Idaho State University, $1,949, duration 1/88 to 1/89.

5. “Computer-Aided Designs of Experiments for UV-Vis Spectrophotometry”, Research Corporation,

$10,000 duration 6/89 to 6/90.

6. “Global Optimized Multicomponent Analysis with UV-Vis Spectrophotometry”, Idaho State Board

of Education, $22,208, duration 9/89 to 9/90.

7. “Spectral Identification of Multicomponent Mixtures”, Faculty Research Grant, Idaho State

University, $2,497, duration 1/91 to 12/91.

8. “Evaluation of Criteria for Optimal Multicomponent Calibration Designs”, National Science

Foundation Idaho EPSCoR Research Experience for Undergraduate Program, $3,000, duration 5/91

to 4/92.

9. “Infrared Identification of Multicomponent Mixtures with Partial Gas Chromatographic Separation”,

National Science Foundation Idaho EPSCoR Regional Scholars Program, $13,393, duration 5/91 to

4/92.

10. “Identification and Characterization of Environmental Pollutants” with P. Griffiths, R. Fletcher, R.

Kirchmeier, C. Wai, R. von Wandruszka at the University of Idaho, M. Schimpf at Boise State

University, and J. Welhan at Idaho State University, National Science Foundation EPSCoR,

$1,050,000 duration 9/93 to 8/96.

11. “The Replacement of the Chemistry Building at Idaho State University” with D. Strommen, R.

Rodriguez, B. Ronald, and F. Wells, National Science Foundation, $658,063, duration 3/94 to

8/97.

12. “Investigation of the Effects of Wavelength and Factor Selection for Principal Component

Regression Using Nonlinear Spectroscopic Data”, Camille and Henry Dreyfus Scholar/Fellow

Program for Undergraduate Institutions, Camille and Henry Dreyfus Foundation, Inc., $60,000,

duration 8/95 to 7/97.

13. “An Improved Agriculture and Food Analysis Procedure”, with P. Lang, Idaho State Board of

Education, $34,141, duration 7/96 to 6/97.

4

14. “Identification and Characterization of Environmental Pollutants” with R. Kirchmeier, C. Wai, R.

von Wandruszka, P. Shapiro at the University of Idaho, and M. Schimpf at Boise State University,

National Science Foundation EPSCoR, $500,000, duration 9/96 to 8/98.

15. “Purchase of a Portable Near-Infrared Spectrophotometer” with G. Scalarone, University Research

Committee, Idaho State University, $12,000, duration 7/97 to 6/98.

16. “Use of Raman Microscopy for Non-Destructive Polymer/Multi-Layer Automobile Paint Cross

Section Analysis” Idaho National Engineering and Environmental Laboratory, $40,000, duration

10/98 to 9/99.

17. “Chemical Pattern Recognition and Detection of United States Currency”, Idaho National

Engineering and Environmental Laboratory, $10,400, duration 11/00 to 5/01.

18. “Extension of Chemical Pattern Recognition and Detection of United States Currency”, Idaho

National Engineering and Environmental Laboratory, $3,526, Duration 6/01 to 7/01.

19. “Dissemination as an Invited Lecturer at the International Union of Pure and Applied Chemistry

International Congress on Analytical Sciences”, Idaho State University Faculty Research

Committee, $ 1,680, duration 8/01 to 8/01.


National Engineering and Environmental Laboratory, $3,591, duration 9/01 to 12/01.


National Engineering and Environmental Laboratory, $4,488, duration 1/02 to 5/02.

22. “RUI: Multivariate Calibration as a Harmonious and Parsimonious Problem”, National Science

Foundation, $118,800, duration 8/04 to 7/07.

23. “A new Look at Non-Linear Multivariate Calibration”, Faculty Research Committee, Idaho State

University, $4,708, duration 1/05 to 12/05.

24. “RUI: Harmonious and Parsimonious Considerations for Correcting Chemical and Instrumental

Effects and Calibration Transfer”, National Science Foundation, $235,613, duration 8/07 to 7/11.

25. “Release Time to Investigate Norm Penalty Regularization for Biomedical Multivariate

Calibration”, InLight Solutions, Albuquerque, New Mexico, $63,894, duration 8/08 to 5/09.

26. “Scholarships for Chemistry and Biochemistry at Idaho State University” with R. Holman, C.

Evilia, J. Pak, K. De Jesus, and A. Holland, National Science Foundation, $568,957, duration 7/10

to 6/15.

27. “Multivariate Calibration Orthogonal to Non-Analyte Spectral Artifacts” Faculty Research

Committee, Idaho State University, $4,901, duration 1/11 to 12/11.

5

28. “RUI: Dynamic Net Analyte Signal Modeling for Multivariate Calibration and Maintenance”,

National Science Foundation, $334,720, duration 9/11 to 2/16.

29. “Investigation of Multivariate Calibration for Simultaneous Determination of Anions and Cations

in Ion Chromatography”, Metrohm USA, Inc., Riverview, Florida, $14,026, duration 6/12 to 8/12.

30. “Infrared Thermal Imaging for Use in Restoration of Defaced Serial Numbers”, with R. Rodriguez

and D. Strommen, Office of Justice Programs at the Department of Justice, $316,004, duration 1/14

to 12/16.

31. Scholarships for Chemistry and Biochemistry at Idaho State University” with J. Pak, C.

Evilia, A. Holland, and L. Goss, National Science Foundation, $615,375, duration 7/15

to 2/21.

32. “CDS&E: Regularization Adaption Processes for Multivariate Calibration and Maintenance”,


33. “Optimization and Statistical Testing of Experimental and Computer Methodologies for Evaluation

of the LIT-MIA Thermal Imaging Method for Recovery of Defaced Serial Numbers”. with R.

Rodriguez, Office of Justice Programs at the Department of Justice, $199,688, duration 1/17 to

12/19.

34. “CDS&E: Adaptive Learning for Multivariate Calibration with Big Data Attributes”,


Invited Publications:

Journal Publications

1. J.H. Kalivas: “Assessing Spectral Orthogonality”, Applied Spectroscopy Reviews, 25, 229-259

(1989).

2. J.H. Kalivas: “Optimization Using Variations of Simulated Annealing”, Chemometrics and

Intelligent Laboratory Systems, 15, 1-12 (1992).

3. J.H. Kalivas: “Chemometrics with Undergraduates”, Chemometrics and Intelligent Laboratory

Systems, 15, 127-135 (1992).

4. J.H. Kalivas, “Two Data Sets of Near Infrared Spectra”, Chemometrics and Intelligent Laboratory

Systems, 37, 255-259 (1997).

5. J.H. Kalivas, “Interrelationships of Multivariate Regression Methods Using Eigenvector Basis

Sets”, Journal of Chemometrics, 13, 111-132 (1999).

6. J.H. Kalivas: “Overview of Two-norm (L2) and One-norm (L1) Regularization Variants for Full

Wavelength or Sparse Spectral Multivariate Calibration Models or Maintenance”, Journal of

Chemometrics, 26, 218-230 (2012).

6

7. J.H. Kalivas, J. Palmer: “Characterizing Multivariate Calibration Tradeoffs (Bias, Variance,

Selectivity, and Sensitivity) to Select Model Tuning Parameters”, Journal of Chemometrics, 28,

347-357 (2014).

8. J.H. Kalivas: “The Flexibility of Regularization Processes for Multivariate Calibration

Maintenance”, European Pharmaceutical Review, 19(4), 21-24 (2014). (non-reviewed)

9. J.H. Kalivas, B. Brownfield, B. Karki: “Sample-Wise Spectral Multivariate Calibration

Desensitized to New Artifacts Relative to the Calibration Data Using a Residual Penalty”, Journal

of Chemometrics, 31(4), 1-12 (2017) DOI: 10.1002/cem.2873.

10. T. Lemos, J.H. Kalivas: “Leveraging Multiple Linear Regression for Wavelength Selection”,

Chemometrics and Intelligent Laboratory Systems, 168, 121-127 (2017)

https://doi.org/10.1016/j.chemolab.2017.07.011.

11. T. Stokes, M. Foteini, B. Brownfield, J.H. Kalivas, G. Mousdis, A. Amine, and C. Georgiou:

“Feasibility Assessment of Synchronous Fluorescence Spectral Fusion by Application to Argan Oil

for Adulteration Analysis”, Applied Spectroscopy, 72, 432-441 (2018) DOI:

10.1177/0003702817749232.

Chapters in Books

12. J.H. Kalivas: “Chapter 4, Calibration” in Practical Guide to Chemometrics, editor S. J. Haswell,

Marcel Dekker, New York, (1992).

13. J.H. Kalivas: “Calibration Design: Samples and Wavelengths” in Trends Applied Spectroscopy,

Vol. 1, editor J. Menon, Research Trends, India 173-186 (1993).

14. U. Hörchner, J.H. Kalivas: “Comparison of Algorithms for Wavelength Selection” in Adaption of

Simulated to Chemical Optimization Problems, editor J.H. Kalivas, Elsevier, The Netherlands,

(1995).

15. G.A. Bakken, N.J. Messick, J.H. Kalivas: “Singular Value Evolving Profiles of

Spectrochromatographic Data for Detection of Impurities and Determination of Component-Wise

Elution Regions”in Recent Developments in Applied Spectroscopy, Vol. 1, editor Scientific

Information Guild, Research Signpost, India, 41-51 (1996).

16. J.H. Kalivas, U. Hörchner: “Improved Calibrations for NIR Spectra by Wavelength Selection” in

Recent Developments in Applied Spectroscopy, Vol 1, editor Scientific Information Guild,

Research Signpost, India, 25-39 (1996).

17. P.J. Gemperline, J.H. Kalivas: “Chapter 3, Sampling Theory, Distribution Functions and the

Multivariate Normal Distribution” in Practical Guide to Chemometrics, Second Edition, editor P.J.

Gemperline, CRC Press Taylor & Francis Group, Boca Raton, Florida (2006).

https://doi.org/10.1016/j.chemolab.2017.07.011

7

18. J.H. Kalivas, P.J. Gemperline: “Chapter 5, Calibration” in Practical Guide to Chemometrics,

Second Edition, editor P.J. Gemperline, CRC Press Taylor & Francis Group, Boca Raton, Florida

(2006). 19. J.H. Kalivas: “Progression of Chemometrics in Research Supportive Curricula: Preparing for the Demands of Society” in ACS Symposium Series 970, Active Learning: Models from the Analytical Sciences, editor P.A. Mabrouk, Oxford University Press (2007). 20. J.H. Kalivas: “Calibration Methodologies” in Comprehensive Chemometrics: Chemical and Biochemical Data Analysis, editors-in-chief S. Brown, R. Tauler, and B. Walczak, Elsevier, The Netherlands (2009).

21. J. Palmer, J.H. Kalivas: “Net Analyte Signal (NAS) for Selection of Multivariate Calibration

Models and Development of NAS Sample-Wise Target Calibration Model Attributes” in ACS

Symposium, 40 Years of Chemometrics, editor B. Lavine, Oxford University Press (2015).

22. J.H. Kalivas: “Chapter 12: Data Fusion of Nonoptimized Models: Applications to Outlier

Detection, Classification, and Image Library Searching”, in Data Fusion Methodology and

Applications" editor M. Cocchi, Elsevier, The Netherlands, (2019).

23. J.H. Kalivas, S.D. Brown: “Calibration Methodologies” in Comprehensive Chemometrics:

Chemical and Biochemical Data Analysis, 2nd Edition, editors-in-chief S. Brown, R. Tauler, and B.

Walczak, Elsevier, The Netherlands (2020).

DOI: https://doi.org/10.1016/B978-0-12-409547-2.14666-9

Books

24. J.H. Kalivas, P.M. Lang: Mathematical Analysis of Spectral Orthogonality, Marcel Dekker, New

York, (1994).

25. J.H. Kalivas (editor): Adoption of Simulated Annealing to Chemical Optimization Problems,

Elsevier, The Netherlands, (1995).

26. J.H. Kalivas (section editor): Linear Regression Modeling in Comprehensive Chemometrics: Chemical and Biochemical Data Analysis, editors-in-chief S. Brown, R. Tauler, and B. Walczak, Elsevier, The Netherlands (2009).

Journal Publications:

27. J.H. Kalivas, B.R. Kowalski: “Generalized Standard Addition Method for Multicomponent

Instrument Characterization and Elimination of Interferences in Inductively Coupled Plasma

Spectrometry”, Analytical Chemistry, 53, 2207-2212 (1981).

28. J.H. Kalivas, B.R. Kowalski: “Compensation for Drift and Interferences in Multicomponent

Analysis”, Analytical Chemistry, 54, 560-565 (1982).

29. J.H. Kalivas, B.R. Kowalski: “Automated Multicomponent Analysis with Correction for

Interferences and Matrix Effects”, Analytical Chemistry, 55, 532-535 (1983).

https://doi.org/10.1016/B978-0-12-409547-2.14666-9

8

30. J.H. Kalivas: “Precision and Stability for the Generalized Standard Addition Method”, Analytical

Chemistry, 55, 565-567 (1983).

31. I.E. Frank, J.H. Kalivas, B.R. Kowalski: “Partial Least Squares Solutions for Multicomponent

Analysis”, Analytical Chemistry, 55, 1800-1804 (1983).

32. J.H. Kalivas: “Determination of Optimal Parameters for Multicomponent Analysis Using the

Calibration Matrix Condition Number”, Analytical Chemistry, 58, 989-992 (1986).

33. L.L. Juhl, J.H. Kalivas: “Evaluation of the Calibration Matrix Condition Number As a Criterion for

Optimal Derivative Spectrophotometric Multicomponent Analysis”, Analytica Chimica Acta, 187,

347-351 (1986).

34. J.H. Kalivas: “A Simplex Optimized Inductively Coupled Plasma Spectrometer with Minimization

of Interferences”, Applied Spectroscopy, 41, 1338-1342 (1987).

35. J.H. Kalivas: “Evaluation of Volume and Matrix Effects for the Generalized Standard Addition

Method”, Talanta, 34, 899-903 (1987).

36. L.L. Juhl, J.H. Kalivas: “Evaluation of Experimental Designs for Multicomponent Analysis with

Spectrophotometry”, Analytical Chimica Acta, 207, 125-135 (1988).

37. J.H. Kalivas, C.W. Blount: “Error Analysis for Multicomponent Systems”, Journal of Chemical

Education, 65, 794-795 (1988).

38. J.H. Kalivas: “Variance-Decomposition of Pure-Component Spectra as a Measure of Selectivity”,

Journal of Chemometrics, 3, 443-449 (1989).

39. J.H. Kalivas, P. Lang: “Condition Numbers, Iterative Refinement and Error Bounds”, Journal of

Chemometrics, 3, 443-449 (1989).

40. J.H. Kalivas, N. Roberts, J. Sutter: “Global Optimization by Simulated Annealing with Wavelength

Selection for Ultraviolet-Visible Spectrophotometry”, Analytical Chemistry, 61, 2024-2030 (1989).

41. L.L. Juhl, J.H. Kalivas, J.M. Sutter: “Observations of Trends for Singular Values and Eigenvectors

from Library Searching Ultraviolet/Visible Spectra with Spectral Subtraction”, Analytical Chimica

Acta, 237, 223-232 (1990).

42. J.H. Kalivas: “Generalized Simulated Annealing for Calibration Sample Selection From an Existing

Set and Orthogonalization of Undesigned Experiments”, Journal of Chemometrics, 5, 37-48 (1991).

43. J.M. Sutter, J.H. Kalivas: “Convergence of Generalized Simulated Annealing with Variable Step

Size with Application Toward Parameter Estimations of Linear and Nonlinear Models”, Analytical

Chemistry, 63, 2383-2386 (1991).

9

44. K. Hitchcock, J.M. Sutter, J.H. Kalivas: “Computer-Generated Multicomponent Calibration

Designs for Optimal Analysis Sample Predictions”, Journal of Chemometrics, 6, 85-96 (1992).

45. T.D. Jarvis, J.H. Kalivas: “Fundamentals of Condition Index Evolving Profiles for Qualitative

Analysis of Unresolved Chromatographic Peaks”, Analytica Chimica Acta, 266, 13-24 (1992).

46. J.M. Sutter, J.H. Kalivas, P.M. Lang: “Which Principal Components to Utilize for Principal

Component Regression”, Journal of Chemometrics, 6, 217-225 (1992).

47. T.D. Jarvis, J.H. Kalivas: “Condition Index Evolving Profile Library Searches: Gas

Chromatography-Fourier Transform Infrared Spectrometry Application”, Analytica Chimica Acta,

272, 53-59 (1993).

48. J.M. Sutter, J.H. Kalivas: “Comparison of Forward Selection. Backward Elimination, and

Generalized Simulated Annealing for Variable Selection”, Microchemical Journal, 47, 60-66

(1993).

49. P.M. Lang, J.H. Kalivas: “A Global Perspective on Multivariate Methods in Spectral Chemical

Analysis”, Journal of Chemometrics, 7, 153-163 (1993).

50. G.A. Bakken, J.H. Kalivas: “Assessing Chromatographic Peak Purity Using Condition Index and

Singular Value Evolving Profiles”, Analytica Chimica Acta, 300, 173-181 (1995).

51. U. Hörchner, J.H. Kalivas: “Further Investigation on a Comparative Study of Simulated

Annealing and Genetic Algorithm for Wavelength Selection”, Analytica Chimica Acta, 311, 1-13

(1995).

52. U. Hörchner, J.H. Kalivas: “Simulated Annealing Type Optimization Algorithms: Fundamentals

and Wavelength Selection Applications”, Journal of Chemometrics, 9, 283-308 (1995).

53. J.H. Kalivas, P.M. Lang: “Interrelationships Between Sensitivity and Selectivity Measures for

Spectroscopic Analysis”, Chemometrics and Intelligent Laboratory Systems, 32, 135-149 (1996).

54. N.J. Messick, J.H. Kalivas, P.M. Lang: “Selectivity and Related Measures for nth-Order Data”,

Analytical Chemistry, 68, 1572-1579 (1996).

55. G.A. Bakken, N.J. Messick, J.H. Kalivas: “Determination of Component-Wise Chromatographic

Elution Regions Using Singular Value Evolving Profiles”, Analytica Chimica Acta, 334, 15-25

(1996).

56. N.J. Messick, J.H. Kalivas: “Determination of Chromatographic Elution Profiles Using Non-

Normalized Singular Value Evolving Profiles”, Microchemical Journal, 55. 235-246 (1997).

57. N.J. Messick, J.H. Kalivas, P.M. Lang: “Selecting Factors for Partial Least Squares”,

Microchemical Journal, 55, 200-207 (1997).

10

58. Y.L. Xie, J.H. Kalivas: “Use of Matrix Orthogonal Projection to Peak Purity Assessment”,

Analytical Letters, 30,395-416 (1997).

59. J.M. Brenchley, U Hörchner, J.H. Kalivas: “Wavelength Selection Characterization for NIR

Spectra”, Applied Spectroscopy, 51, 689-699 (1997).

60. Y.L. Xie, J.H. Kalivas: “Evaluation of Principal Component Selection Methods to Form a Global

Prediction Model by Principal Component Regression”, Analytica Chimica Acta, 348, 19-27

(1997).

61. Y.L. Xie, J.H. Kalivas: “Local Prediction Models by Principal Component Regression”, Analytica

Chimica Acta, 348, 29-38 (1997).

62. J.H. Kalivas, P.M. Lang: “Response to: Comments on Interrelationships Between Sensitivity and

Selectivity Measures for Spectroscopic Analysis”, Chemometrics and Intelligent Laboratory

Systems, 38, 95-100 (1997).

63. G.A. Bakken, D.R. Long, J.H. Kalivas: “Examination of Criteria for Local Model Principal

Component Regression”, Applied Spectroscopy, 51, 1814-1822 (1997).

64. P.M. Lang, J.M. Brenchley, R.G. Nieves, J.H. Kalivas: “Cyclic Subspace Regression”, Journal of

Multivariate Analysis, 65, 58-70 (1998).

65. J.M. Brenchley, R.G. Nieves, P.M. Lang, J.H. Kalivas: “Stabilization of Cyclic Subspace

Regression”, Chemometrics and Intelligent Laboratory Systems, 41, 127-134 (1998).

66. C.E. Anderson, R.G. Nieves, J.H. Kalivas: “Spectral Orthogonality Considerations for Library

Searching Nth-Order Data”, Chemometrics and Intelligent Laboratory Systems, 41, 115-125 (1998).

67. J.H. Kalivas: “Cyclic Subspace Regression with Analysis of the Hat Matrix”, Chemometrics and

Intelligent Laboratory Systems, 45, 209-217 (1998).

68. G.A. Bakken, T.P. Houghton, J.H. Kalivas: “Cyclic Subspace Regression with Analysis of

Wavelength Selection Criteria”, Chemometrics and Intelligent Laboratory Systems, 45, 219-232

(1998).

69. V.A. Allen, J.H. Kalivas, R.G. Rodriguez: “Post-Consumer Plastic Identification Using Raman

Spectroscopy”, Applied Spectroscopy, 53, 672-681 (1999).

70. C.E. Anderson, J.H. Kalivas: “Fundamentals of Calibration Transfer Through Procrustes Analysis”,

Applied Spectroscopy, 53, 1268-1276 (1999).

71. J.J. Rosentreter, R. Nieves, J.H. Kalivas, J. Rousseau, R.C. Bartholomay: “The Use of Chemical

and Physical Properties for Rapid Characterization of Strontium Distribution Coefficients at the

Idaho National Engineering and Environmental Laboratory, Idaho”, U.S. Geological Survey, Water

Resources Investigations /report, 99-4123 (June 1999).

11

72. T. Houghton, J.H. Kalivas: “Implementation of Traditional and Real-World Cooperative Learning

Techniques in Quantitative Analysis Including Near Infrared Spectroscopy for Analysis of Live

Trout”, Journal of Chemical Education, 77, 1314-1318 (2000).

73. J.M. Brenchley, R.L. Green, S.Z. Fairchild, J.H. Kalivas, G. Scalarone: “Capability of Urine

Analysis for the Disease Blastomycosis Using Infrared Spectroscopy and Eigenvector Signal to

Noise Assessment” Analytical Letters, 33, 3165-3181 (2000).

74. J.H. Kalivas: “Basis Sets for Multivariate Calibration”, Analytica Chimica Acta, 428, 31-40 (2001).

75. S.Z. Fairchild, J.H. Kalivas: “PCR Eigenvector Selection Based on Correlation Relative Standard

Deviations”, Journal of Chemometrics, 15, 615-625 (2001).

76. J.H. Kalivas, R.L. Green: “Pareto Optimal Multivariate Calibration for Spectroscopic Data”,

Applied Spectroscopy, 55, 1645-1652 (2001).

77. R.L. Green, J.H. Kalivas: “Graphical Diagnostics for Regression Model Determinations with

Consideration of the Bias/Variance Trade-off”, Chemometrics and Intelligent Laboratory Systems,

60, 173-188 (2002).

78. N.M. Faber, J. Ferré, R. Boqué, J.H. Kalivas: “Second-order Bilinear Calibration: The Effects of

Vectorising the Data Matrices of the Calibration Set”, Chemometrics and Intelligent Laboratory

Systems, 63, 107-116 (2002).

79. J.M. Clark, K.A. Daum, J.H. Kalivas: “Demonstrated Potential of Ion Mobility Spectrometry for

Detection of Adulterated Perfumes and Plant Speciation”, Analytical Letters, 36, 215-244 (2003).

80. N.M. Faber, J. Ferré, R. Boqué, J.H. Kalivas: “Quantifying Selectivity in Spectrophotometric

Multicomponent Analysis”, Trends in Analytical Chemistry, 22, 352-361 (2003).

81. K.J. Anderson, J.H. Kalivas: “Assessment of Pareto Calibration, Stability, and Wavelength

Selection”, Applied Spectroscopy, 57, 309-316 (2003).

82. J.H. Kalivas: “Pareto Calibration with Built-In Wavelength Selection”, Analytica Chimica Acta,

505, 9-14 (2004).

83. H.A. Seipel, J.H. Kalivas: “Effective Rank for Multivariate Calibration Methods”, Journal of

Chemometrics, 18, 306-311 (2004) and “Erratum to Seipel HA, Kalivas JH. Effective Rank for

Multivariate Calibration Methods. J. Chemometrics 2004; 18: 306-311”, Journal of Chemometrics,

19, 64 (2005).

84. J.B. Forrester, J.H. Kalivas: “Ridge Regression Optimization Using a Harmonious Approach”,


12

85. J.H. Kalivas, J.B. Forrester, H.A. Seipel: “QSAR Modeling Based on the Bias/Variance

Compromise: A Harmonious Approach”, Journal of Computer-Aided Molecular Design, 18,

537-547 (2004).

86. J.H. Kalivas: “Realizing Work Place Skills in Instrumental Analysis”, Journal of Chemical

Education, 82, 895-897 (2005).

87. J.H. Kalivas, “Multivariate Calibration: An Overview”, Analytical Letters, 38, 2259-2279 (2005).

88. A.C. Olivieri, N.M. Faber, J. Ferré, R. Boque, J.H. Kalivas, H. Mark: “Uncertainty Estimation and

Figures of Merit for Multivariate Calibration”, Pure and Applied Chemistry, 78, 633-661 (2006).

89. F. Stout, J.H. Kalivas: “Tikhonov Regularization in Standard and General Form for Multivariate

Calibration with Applications Towards Removing Unwanted Spectral Artifacts”, Journal of

Chemometrics, 20, 22-33 (2006).

90. F. Stout, M.R. Baines, J.H. Kalivas: “Impartial Graphical Comparison of Multivariate Calibration

Methods and the Harmony/Parsimony Tradeoff”, Journal of Chemometrics, 20, 464-475 (2006).

91. F. Stout, J.H. Kalivas, K. Héberger: “Wavelength Selection for Multivariate Calibration Using

Tikhonov Regularization”, Applied Spectroscopy, 61, 85-95 (2007).

92. F. Stout, J.H. Kalivas: “Evaluation of Multivariate Calibration Using a Tikhonov Regularization

Approach and the Generalized Pair-Correlation Method with Non-linear Data”, Analytical Letters,

40, 1227-1251 (2007).

93. J.H. Kalivas: “Learning from Procrustes Analysis to Improve Multivariate Calibration”, Journal of

Chemometrics, 22, 227-234 (2008).

94. J.H. Kalivas: “An Elementary School Service Learning Project Based on a Research Supportive

Curriculum Format in the General Chemistry Laboratory”, Journal of Chemical Education, 85,

1410-1415 (2008)

95. O. Farkas, I.G. Zenkevich, F. Stout, J.H. Kalivas, K. Héberger: “Prediction of Gas Chromatographic

Retention Indices for Fatty Acid Methyl Esters”, Journal of Chromatography A, 1198-1199, 188-

195 (2008).

96. J.H. Kalivas, G.G. Siano, E. Andries, H.C. Goicoechea: “Calibration Maintenance and Transfer

Using Tikhonov Regularization Approaches”, Applied Spectroscopy, 63, 800-809 (2009).

97. M.R. Kunz, J. Ottaway, J.H. Kalivas, E. Andries: “Impact of Standardization Sample Designs on

Tikhonov Regularization Variants for Spectroscopic Calibration and Maintenance and Transfer”,


98. E. Andries, J.H. Kalivas, “Multivariate Calibration Leverages and Spectral F-Ratios via the Filter

Factor Representation”, Journal of Chemometrics, 24, 249-260 (2010).

13

99. R. Kunz, J.H. Kalivas, E. Andries: “Model Updating for Spectral Calibration Maintenance and

Transfer Using 1-Norm Variants of Tikhonov Regularization”, Analytical Chemistry, 82, 3642-3649

(2010).

100. J. Ottaway, J.H. Kalivas, E. Andries: “Spectral Multivariate Calibration with Wavelength

Selection Using Variants of Tikhonov Regularization”, Applied Spectroscopy, 64, 1388-1395

(2010).

101. M.R. Kunz, J. Ottaway, J.H. Kalivas, C.A. Georgiou, G.A. Mousdis: “Updating a Synchronous

Fluorescence Spectroscopic Virgin Olive Oil Adulteration Calibration to a New Geographical

Region”, Journal of Agricultural and Food Chemistry, 59, 1051-1057 (2011).

102. J. Farrell, K. Higgins, J.H. Kalivas: “Updating a Near-Infrared Multivariate Calibration Model

Formed with Lab-Prepared Pharmaceutical Tablet Types to New Tablet Types in Full Production”,

Journal of Pharmaceutical and Biomedical Analysis, 61, 114-121 (2012).

103. K. Higgins, J.H. Kalivas, E. Andries: “Evaluation of Target Factor Analysis and Net Analyte

Signal as Processes for Classification Purposes with Application to Benchmark Data Sets and

Extra Virgin Olive Oil Adulteration”, Journal of Chemometrics, 26, 66-75 (2012).

104. P. Shahbazikhah, J.H. Kalivas: “A Consensus Modeling Approach to Update a Spectroscopic

Calibration”, Chemometrics and Intelligent Laboratory Systems, 120, 142-153 (2013).

105. J. Ottaway, J. Farrell, J.H. Kalivas: “Spectral Multivariate Calibration without Laboratory Prepared

or Determined Reference Analyte Values”, Analytical Chemistry, 85, 1509-1516 (2013).

106. E. Andries, J.H. Kalivas: “Interrelationships between Generalized Tikhonov Regularization,

Generalized Net Analyte Signal, and Generalized Least Squares for Desensitizing a Multivariate

Calibration to Interferences”, Journal of Chemometrics, 27, 126-140 (2013).

107. J.H. Kalivas, C.A. Georgiou, M. Moira, I. Tsafaras, E. Petrakis, G.A. Mousdis: “Food Adulteration

Analysis without Laboratory Prepared or Determined Reference Food Adulterant Values”, Food

Chemistry, 148, 289-293 (2014). For a PowerPoint presentation, see

www.sciencedirect.com/science/article/pii/S030881461301501X

108. S.A. Drivelos, K. Higgins, J.H. Kalivas, S.A. Haroutounian, C.A. Georgiou: “Data Fusion for

Food Authentication. Combining Rare Earth Elements and Trace Metal to Discriminate “Fava

Santorinis” from Other Yellow Split Peas using Chemometric Tools”, Food Chemistry, 165,

316-322 (2014).

109. J. Ottaway, J.H. Kalivas: “Feasibility Study to Transform Spectral and Instrumental Artifacts for

Multivariate Calibration Maintenance”, Applied Spectroscopy, 69, 407-416 (2015).

110. J.H. Kalivas, K. Héberger, E. Andries: “Using Sum of Ranking Differences (SRD) to Ensemble

Multivariate Calibration Model Merits for Tuning Parameter Selection and Comparing Calibration

Methods”, Analytica Chimica Acta, 869, 21-33 (2015).

http://www.sciencedirect.com/science/article/pii/S030881461301501X

14

111. P. Shahbazikhah, J.H. Kalivas, E. Andries, T. O’Loughlin: “Using the L1 Norm to Select Basis Set

Vectors for Multivariate Calibration and Calibration Updating”, Journal of Chemometrics, 30,

109-120 (2016).

112. A. Tencate, J.H. Kalivas, E. Andries: “Penalty Processes for Combining Roughness and

Smoothness in Spectral Multivariate Calibration”, Journal of Chemometrics, 30, 144-152 (2016).

113. A.J. Tencate, J.H. Kalivas, A.J. White: “Fusion Strategies for Selecting Multiple Tuning

Parameters for Multivariate Calibration and other Penalty Based Processes: A Model Updating

Application for Pharmaceutical Analysis”, Analytica Chimica Acta, 921, 28-37 (2016).

114. B. Brownfield, J.H. Kalivas: “Consensus Outlier Detection using Sum of Ranking Differences of

Common and New Outlier Measures without Tuning Parameter Selections”, Analytical

Chemistry, 89, 5087-5094 (2017) DOI: https://doi.org//10.1021/acs.analchem.7b00637.

115. B. Brownfield, J.H. Kalivas: “Correction to Consensus Outlier Detection using Sum of Ranking

Differences of Common and New Outlier Measures without Tuning Parameter Selections,

Analytical Chemistry, 89, 5087-5094 (2017) DOI: 10.1021/acs.analchem.7b00637”, Analytical

Chemistry, 89, 9609-9609 (2017) DOI: https://doi.org//10.1021/acs.analchem.7b02828

116. J.H. Kalivas, J. Ferré, A.J. Tencate: “Selectivity-Relaxed Classical and Inverse Least Squares

Calibration and Selectivity Measures with a Unified Selectivity Coefficient”, Journal of

Chemometrics, 31, 1-23 (2017) DOI: 10.1002/cem.2925, Open Access

http://onlinelibrary.wiley.com/doi/10.1002/cem.2925/epdf

117. B. Brownfield, T. Lemos, J.H. Kalivas: “Consensus Classification Using Non-Optimized

Classifiers”, Analytical Chemistry, 90, 4429-4437 (2018) DOI:

https://doi.org//10.1021/acs.analchem.7b04399.

118. E. Andries, J.H. Kalivas, A. Gurung: “Sample and Feature Augmentation Strategies for

Calibration Updating: A Comparative Study”, Journal of Chemometrics, 31(1), 1-20 (2019)

DOI: https://doi.org//10.1002/cem.3080

119. I. Unobe, L. Lau, J. Kalivas, R. Rodriguez, A. Sorensen: “Restoration of Defaced Serial Numbers

Using Lock-in Infrared Thermography (Part I)”, Journal of Spectral Imaging, 8, Article ID a19

(2019) DOI: https://doi.org/10.1255/jsi.2019.a19

120. I. Unobe, L. Lau, J. Kalivas, R. Rodriguez, A. Sorensen: “Restoration of Defaced Serial Numbers

Using Lock-in Infrared Thermography (Part II)”, Journal of Spectral Imaging, 8, Article ID a20

(2019) DOI: https://doi.org/10.1255/jsi.2019.a20

121. T. Lemos, R. Emerson, J.H. Kalivas: “Identifying Chemical, Physical, and Instrumental Matrix

Matched Samples by Leveraging Spectral Model Regression Vectors”, Analytical Chemistry,

92(1), 815-823 (2020) DOI: http://doi.org/10.1021/acs.analchem.9b03302.

https://doi.org/10.1021/acs.analchem.7b00637


http://onlinelibrary.wiley.com/doi/10.1002/cem.2925/epdf


https://doi.org/10.1002/cem.3080

https://doi.org/10.1255/jsi.2019.a19

https://doi.org/10.1255/jsi.2019.a20

http://doi.org/10.1021/acs.analchem.9b03302

15

122. T. Lemos, J.H. Kalivas: “Self-Optimized One-Class Classification Using Sum of Ranking

Differences Combined with a Receiver Operator Characteristic Curve”, Analytical Chemistry, 92,

5354-5361 (2020). http://doi.org/10.1021/acs.analchem.0c00017.

123. A. Gurung, J.H. Kalivas: “Model Selection Challenges with Application to Multivariate

Calibration Updating Methods”, Journal Chemometrics 2020;34:e3245; {34(7), 1-17 (2020)}


124. B.K. Chabuka, J.H. Kalivas: “Application of a Hybrid Fusion Classification Process for

Identification of Microplastics Based on FTIR Spectroscopy”, Applied Spectroscopy In press.

Manuscripts Submitted:

1. S. Hansen, A. Mirkouei, M.M. Ramirez-Corredores, K. Sharma, R. Spiers, J.H. Kalivas, E.

Struhs: “Effect of Sono-Catalytic Transfer Hydrogenation and In-Line Characterization on Upgrading

Pyrolysis-Derived Oil”, Ultrasonics - Sonochemistry Submitted June 2020.

Manuscripts in Preparation:

1. R.C. Spiers, J.H. Kalivas: “Utilizing Model Diversity and Prediction Similarity for Reliable

Transductive Multivariate Calibration Model Selections by Consensus Filtering”, in preparation for

Analytical Chemistry.

2. R.C. Spiers, J.H. Kalivas: “Harnessing Unlabeled Data for Transductive Model Updating and

Parameter Selection”, in preparation for Analytical Chemistry.

3. J.H. Kalivas, T. Lemos: “Automatic Food Authentication and Adulteration Detection by

Classification Data Fusion” in preparation for Applied Spectroscopy.

Invited Meeting Talks:

1. J.H. Kalivas: “Novel Approach to Interference Correction” 1st ICAP Atomic Emission Workshop,

Weyerhauser Technology Center, Tacoma, Washington, 1981.

2. J.H. Kalivas, K. Hitchcock, J.M. Sutter: “Multivariate Calibration Designs by Generalized

Simulated Annealing”, International Congress on Analytical Sciences 1991, Makuhari-Messe,

Chiba, Japan, 1991.

3. J.H. Kalivas, J.M. Sutter, P.M. Lang: “Optimization Applications of Generalized Simulated

Annealing Including: Not Only a Question of How Many Principal Components for PCR, But Also

Which Ones”, International Conference on Chemometrics in Analytical Chemistry, Montreal,

Quebec, Canada, 1992.

4. J.H. Kalivas, P.M. Lang: “Getting the Most Out of PCR and PLS”, Federation of Analytical

Chemistry and Spectroscopy Societies (FACSS), Detroit, Michigan, 1993.

http://doi.org/10.1021/acs.analchem.0c00017


16

5. J.H. Kalivas, P.M. Lang: “Singular Values and Their Use in Global Selectivity and Sensitivity

Assessments”, Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), St. Louis,

Missouri, 1994.

6. J.H. Kalivas: “Selection of Principal Components to Build Global and Local Models by PCR and

Analysis of Wavelength Selection Versus Principal Component Selection”, International

Conference on Chemometrics in Analytical Chemistry, Tarragona, Spain, 1996.

7. J.H. Kalivas, P.M. Lang: “Interrelationships Between PCR and PLS by Cyclic Subspace Regression

with Applications”, First Conference on Chemometrics in China, Zhangjiajie, China, 1997.

8. J.H. Kalivas: “The Hat Matrix: A Bridge Between PCR, PLS, and LS”, Federation of Analytical

Chemistry and Spectroscopy Societies (FACSS), Providence, Rhode Island, 1997.

9. J.H. Kalivas, C.E. Anderson: “Multidimensional Scaling for Multivariate Calibration Transfer”,

Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Providence, Rhode

Island, 1997.

10. J.H. Kalivas, V.A. Allen, R.G. Rodriguez: “Identification of Recycled Plastic Waste by Raman

Spectroscopy’, National Meeting of the American Chemical Society, Dallas, Texas, 1998.

11. J.H. Kalivas: “PCR and PLS the Same and Not the Same”, Ninth International Diffuse Reflectance

Conference, Chambersburg, Pennsylvania, 1998.

12. J.H. Kalivas: “A Simple Geometric View of Cyclic Subspace Regression and Continuum

Regression: Are They Different Methods?”, Federation of Analytical Chemistry and Spectroscopy

Societies (FACSS), Austin, Texas, 1998.

13. J.H. Kalivas, R. Green: “Graphical Diagnostics of Model Parameters”, Fourth International

Conference on Environmetrics and Chemometrics, Las Vegas, Nevada, 2000.

14. J.H. Kalivas, S. Fairchild, R. Green: “Parsimony Paradox”, Federation of Analytical Chemistry and

Spectroscopy Societies (FACSS), Nashville, Tennessee, 2000.

15. J.H. Kalivas: “Chemometrics with Undergraduates: When Can you Start?”, Federation of Analytical

Chemistry and Spectroscopy Societies (FACSS), Nashville, Tennessee, 2000.

16. J.H. Kalivas: “Multivariate Calibration by Pareto-Optimality”, International Congress on Analytical

Sciences, Tokyo, Japan, 2001.

17. J.H. Kalivas: “Evolution of Chemometrics in the Undergraduate Analytical Chemistry Curriculum”,

South East Regional Meeting of the American Chemical Society, Savannah, Georgia, 2001.

18. J.H. Kalivas: “Regression Diagnostic Considerations for Determining Pareto Calibration Models”,

Third Aegean Analytical Chemistry Days, Polihnitos, Lesvos, Greece, 2002.

17

19. J.H. Kalivas: “Defining Multivariate Calibration Model Complexity for Model Selection and

Comparison”, Fourth Winter Symposium on Chemometrics, Chernogolovka, Russia, 2005.

20. J.H. Kalivas: “Student-Centered Learning in Analytical Chemistry for Realizing Work Place

Skills”, National Meeting of the American Chemical Society, Washington DC, 2005.

21. J.H. Kalivas: “Active Learning Using a Research Supportive Curriculum Format with Service

Learning in the General Chemistry Laboratory”, Northwest Regional Meeting of the American

Chemical Society, Boise, Idaho, 2007.

22. J.H. Kalivas: “Applying Mean Centering Lessons from Procrustes Analysis to Improve Multivariate

Calibration”, Conferentia Chemometrica, Hungary, 2007.

23. J.H. Kalivas: “Multiple Uses of Tikhonov Regularization in Multivariate Calibration”, Conferentia

Chemometrica, Hungary, 2009.

24. J.H. Kalivas: “Multivariate Calibration and Maintenance without Reference Samples via Tikhonov

Regularization Incorporating Two Tuning Parameters”, Conferentia Chemometrica, Hungary, 2011.

25. J.H. Kalivas: “Student-Centered Learning in Analytical Chemistry for Realizing Work Place

Skills”, Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Reno, Nevada,

2011.

26. J.H. Kalivas, P. Shahbazikhah: “Consensus Multivariate Calibration or Maintenance without

Reference Samples Using Tikhonov Type Regularization Approaches”, Eighth Winter Symposium

on Chemometrics, Drakino, Russia, 2012.

27. J.H. Kalivas, P. Shahbazikhah, E. Andries: “Using Sparse Modeling Algorithms to Select

Multivariate Calibration Basis Set Vectors”, XIII Chemometrics in Analytical Chemistry, Budapest,

Hungary, 2012.

28. J.H. Kalivas, P. Shahbazikhah, E. Andries: “Selecting Multivariate Calibration Basis Set Vectors to

Optimize Spectroscopic Performance”, SciX 2012, Kansas City, Missouri, 2012.

29. J.H. Kalivas, J. Palmer: “Assessing Multivariate Calibration Trade-offs to Select Model Tuning

Parameters”, SciX 2013, Milwaukee, Wisconsin, 2013.

30. J.H. Kalivas: “Characterizing the Implicative Selectivity/Sensitivity Balance Using the Explicative

Bias/Variance Tradeoff in Selecting Multivariate Calibration Model Tuning Parameters”, AnalytiX

2014, Dalian, China, 2014.

31. J.H. Kalivas, K. Higgins, C.A. Georgiou, M. Mira, I. Tsafaras, G.A. Mousdis, E. Petrakis, S.A.

Drivelos, S.A. Haroutounian: “Identifying Authentic and/or Adulterated Food Products Followed by

Adulterant Quantitation without Reference Samples: Application to Fava Santorinis and Extra

Virgin Olive Oil”, American Chemical Society National Meeting, San Francisco, California, 2014.

18

32. J.H. Kalivas: “Advancing Regularization Processes in Multivariate Calibration to Include

Multimerits and Multituning Parameters”, International Chemometric Research Meeting,

Nijmegen, The Netherlands, 2014.

33. J.H. Kalivas, B. Brownfield: “Outlier Detection by Fusion of Multiple Merits”, AnalytiX

2015, Nanjing, China, 2015.

34. J.H. Kalivas, A. Tencate: “Fusion of Multiple Measures of Calibration Model Quality to Rank

Models Based on Multiple Tuning Parameters”, Conferentia Chemometrica, Budapest, Hungary,

2015.

35. J.H. Kalivas, B. Brownfield: “Characterizing Calibration Data Sets by Fusion of Dissimilarity

Merits Including Outlier Detection”, SciX 2015, Providence, Rhode Island, 2015.

36. J.H. Kalivas, B. Brownfield, A. Tencate: “Advancing Multivariate Spectral Calibration with Fusion

of Multiple Quality Measures”, Eastern Analytical Symposium (EAS), Newark, New Jersey, 2015.

37. J.H. Kalivas, A. Tencate: “Ranking Multivariate Calibration Models Formed from Multiple Tuning

Parameters (Model Penalties)”, National Meeting of the American Chemical Society, San Diego,

California, 2016.

38. J.H. Kalivas, R. Emerson: “Taking a Big Data Approach to Local Spectral Calibration”,

Chemometrics in Analytical Chemistry, Barcelona, Spain, 2016.

39. J.H. Kalivas, B. Brownfield: “Chemometric Processes for Food Authentication and Adulteration

Analysis”, Institute of Food Technologists (IFT) Meeting, Chicago, Illinois, 2016.

40. J.H. Kalivas: “Penalty Based Methods for Calibration Maintenance”, SciX 2016, Minneapolis,

Minnesota, 2016.

41. J.H. Kalivas, B. Brownfield, I. Unobe: “Data Fusion Using Window Based Models: Application to

Outlier Detection, Classification, and Forensic Image Analysis”, Topics in Chemometrics,

Newcastle, Australia, 2017.

42. J.H. Kalivas, B. Brownfield, I. Unobe: “A New Perspective on Data Fusion: Window Based Models

with Application to Outlier Detection, Classification, and Forensic Image Analysis”, IX Colloquium

Chemiometricum Mediterraneum, Arles, France, 2017.

43. J.H. Kalivas, B. Brownfield, I. Unobe: “Reducing Ambiguity in Outlier Detection, Classification,

and Forensics Image Analysis with Data Fusion”, Conferentia Chemometrica, Gyöngyös-

Farkasmály, Hungary, 2017.

44. J.H. Kalivas, I. Unobe, L. Lau, A. Sorensen, R. Rodriguez: “Non-Destructive Recovery of Defaced

Serial Numbers Using Infrared Thermal Imaging”, SciX 2017, Reno, Nevada, 2017.

19

45. E. Andries, J.H. Kalivas, A. Gurung: “Calibration Updating by Sample and Feature Augmentation”,

SciX 2017, Reno, Nevada, 2017.

46. J.H. Kalivas, J. Ferŕe, E. Andries, A. Tencate, A. Gurung: “Orthogonality and Unlabeled Data in

Multivariate Calibration”, Arctic Anlaysis II, Fludir, Iceland, April 2018.

47. J.H. Kalivas, T. Lemos: “Fusion of Non-Optimized Classifiers: Application to Food Authentication

and Adulteration”, 11th Aegean Analytical Chemistry Days, Chania, Crete, Greece, Sept 2018.

48. J.H. Kalivas, I. Unobe, T. Lemos: “Data Fusion with Non-Optimized models: Application to

Principal Component Analysis of Lock-in Thermography Images and Classification Problems”,

SciX 2018, Atlanta, Georgia, 2018.

49. J.H. Kalivas, I. Unobe, L. Lau, A. Sorensen, R. Rodriguez: “Non-Destructive Recovery of Defaced

Serial Numbers Using Infrared Thermal Imaging”, Pittcon, Philadelphia, Pennsylvania, March

2019.

50. J.H. Kalivas, T. Lemos, R. Emerson: “Leveraging the Regression Vector for Proper Matrix

Matching Aimed at Local Spectral Calibration”, Topics in Chemometrics, Szeged (Zanjan), Hungry,

2019.

51. J.H. Kalivas, T. Lemos: “Unraveling Sample Matrix Effects for Multivariate Calibration”, National

Meeting of the American Chemical Society, San Diego, California, 2019.

52. J.H. Kalivas, R. Spiers: “Using Model Diversity and Prediction Similarities of Unlabeled Samples

for Model Selection of Multivariate Calibration Updating Methods”, SciX 2019, Palm Springs,

Calif., 2019.

53. J.H. Kalivas, T. Lemos: “Food Authentication and Adulteration Detection with Data Fusion of

Non-Optimized Classifiers”, SciX 2019, Palm Springs, Calif., 2019.

54. J.H. Kalivas, T. Lemos: “Identifying Matrix Matched Samples by Leveraging Spectral Calibration

Model Regression Vectors”, SciX 2019, Palm Springs, Calif., 2019.

55. B.K. Chabuka, J.H. Kalivas: “Identification of Microplastics Using Non-Optimized Discriminant

Fusion Classification based on ATR-FTIR Spectroscopy”, SciX 2019, Palm Springs, Calif., 2019.

56. J.K. Kalivas, T. Lemos: “Harnessing Spectral Model Regression Vectors to Unravel Chemical,

Physical, and Instrumental Matrix Effects”, Eastern Analytical Symposium (EAS), Plainsboro, New

Jersey, 2019.

Meeting Talks and Posters:

57. J.H. Kalivas, B.R. Kowalski: “Generalized Standard Addition Method with Inductively Coupled

Plasma Emission”, Congress of the International Union of Pure and Applied Chemistry,

Vancouver, British Columbia, Canada, 1981.

20

58. J.H. Kalivas, C. Jochum, B.R. Kowalski: “Intelligent Analytical Instrumentation: Self-correcting

Multicomponent Analysis”, The Pittsburgh Conference and Exposition on Analytical Chemistry and

Applied Spectroscopy, Atlantic City, New Jersey, 1982.

59. J.H. Kalivas: “A Method for the Choice of Optimal Analytical Wavelengths in Spectrophotometric

Analysis of Multicomponent Systems”, Annual Meeting of the Idaho Academy of Science,

Pocatello, Idaho, 1985.

60. J.H. Kalivas:” Error Propagation as a Criterion for Optimal Spectrophotometic Multicomponent

Analysis”, The Pittsburgh Conference and Exposition on Analytical Chemistry and Applied

Spectroscopy, Atlantic City, New Jersey, 1986.

61. L.L. Juhl, J.H. Kalivas: “Optimization of Derivative Order for Spectral Multicomponent Analysis”,

Northwest Regional Meeting of the American Chemical Society, Portland, Oregon, 1986.

62. L.L. Juhl, J.H. Kalivas: “Correction to the Generalized Standard Addition Method”, Northwest

Regional Meeting of the American Chemical Society, Portland, Oregon, 1986.

63. J.H. Kalivas: Simplex Optimization of an ICP Spectrometer with Minimization of Spectral

Interferences”, National Meeting of the American Chemical Society, Denver, Colorado, 1987.

64. L.L. Juhl, J.H. Kalivas: “Evaluation of Wavelength Ranges for Multicomponent Analysis with

Spectrophotometry”, Pacific Conference on Chemistry and Spectroscopy, Irvine, California, 1987.

65. J. Sutter, J.H. Kalivas: “Automatic Computerized Wavelength Selection with Simplex”, National

Meeting of the American Chemical Society, Toronto, Canada, 1988.

66. P. Troescher, G. Wiegand, J.H. Kalivas: “Optimization of an Organic Synthesis with Simplex”,

Northwest Regional Meeting of the American Chemical Society, Spokane, Washington, 1988.

67. J.H. Kalivas: “Variance-Decomposition Proportions for Regression Coefficients”, Second Hidden

Peak Symposium on Computer-Enhanced Analytical Spectroscopy, Snowbird, Utah, 1988.

68. J.H. Kalivas, P. Lang: “Computable Error Bounds for Multicomponent Analysis”, Second Hidden

Peak Symposium on Computer-Enhanced Analytical Spectroscopy, Snowbird, Utah, 1988.

69. J.H. Kalivas: “Detecting and Assessing Spectral Orthogonality”, National Meeting of the

American Chemical Society, Los Angeles, California, 1988.

70. N. Roberts, J.H. Kalivas: “The Generalized Simulated Annealing Method Versus Simplex for

Function Optimization”, National Meeting of the American Chemical Society, Dallas, Texas,

1989.

71. J. Sutter, J.H. Kalivas: “Optimal Wavelength Selection for UV-Vis, Spectrophotometry Using

Simulated Annealing”, National Meeting of the American Chemical Society, Dallas, Texas, 1989.

21

72. J.H. Kalivas, L. Juhl, J. Sutter: “Variance-Decomposition: A New Procedure for Searching a UV-

Vis Spectral Library”, International Conference on Computers in Chemical Research and

Education, Riva del Garda, Italy, 1989.

73. J.H. Kalivas, N. Roberts, J. Sutter: “Simulated Annealing: A Controlled Heuristic Search

Procedure for Global Optimization”, International Conference on Computers in Chemical Research

and Education, Riva del Garda, Italy, 1989.

74. J.H. Kalivas: “Optimizing Performance for Near Infrared Multicomponent Analysis Using

Computer Designed Experiments”, Third Symposium on Computer-Enhanced Analytical

Spectroscopy, Snowbird, Utah, 1990.

75. J. Sutter, J.H. Kalivas: “Calibration Sample Design Using Generalized Simulated Annealing”,

Joint Northwest/Rocky Mountain Regional Meeting of the American Chemical Society, Salt Lake

City, Utah, 1990.

76. K. Hitchcock, J.H. Kalivas: “Multivariate Calibration of UV-Vis Spectra For Quantitative Analysis

Using Simulated Annealing Designed Experiments”, Federation of Analytical Chemistry and

Spectroscopy Societies Conference, Cleveland, Ohio, 1990.

77. J.H. Kalivas, J.M. Sutter: “Convergence of Generalized Simulated Annealing with Variable Step

Size for Parameter Estimations of Linear and Non-Linear Models”, Gordon Conference on

Statistics in Chemistry and Chemical Engineering, New Hampton, New Hampshire, 1991.

78. T.D. Jarvis, J.H. Kalivas: “Chromatographic Curve Resolution and Eluent Identification”, National

Meeting of the American Chemical Society, San Francisco, California, 1992.

79. J.M. Sutter, J.H. Kalivas: “Generalized Simulated Annealing Used for Variable Selection”,

National Meeting of the American Chemical Society, San Francisco, California, 1992.

80. J.H. Kalivas, T.D. Jarvis, P.R. Griffiths, E. Hasenoehrl: “Analyte Identification of Unresolved

Chromatographic Peaks Using Condition Index Evolving Profiles”, International Conference on

Chemometrics in Analytical Chemistry, Montreal, Quebec, Canada, 1992.

81. P.M. Lang, J.H. Kalivas: “A Global Perspective on Multivariate Methods in Spectral Chemical

Analysis”, International Conference on Chemometrics in Analytical Chemistry, Montreal, Quebec,

Canada, 1992.

82. J.H. Kalvas, G.A. Bakken: “Assessment of Peak Purity in Chromatography by Condition Index

Evolving Profile”, National Meeting of the American Chemical Society, San Diego, California,

1994.

83. U. Hörchner, J.H. Kalivas: “Comparison of Global Organization Methods for Wavelength

Selection”, Fifth Symposium on Computer-Enhanced Analytical Spectroscopy, Snowbird, Utah,

1994.

22

84. N.J. Messick, U. Hörchner, J.H. Kalivis: “Deterministic and Stochastic Wavelength Selection

Procedures for Spectroscopic Calibrations”, National Meeting of the American Chemical Society,

Washington D.C., 1994.

85. G.A. Bakken, J.H. Kalivas: “Singular Value Evolving Profiles for Assessment of Chromatographic

Peak Purity”, National Meeting of the American Chemical Society, Washington D.C., 1994.

86. G.A. Bakken, J.H. Kalivas: “Singular Value Evolving Profiles for the Assessment of

Chromatographic Peak Purity without Reference Spectra”, National Meeting of the American

Chemical Society, Anaheim, California, 1995.

87. N.J. Messick, G.A. Bakken, J.H. Kalivas: “Impurity Detection of GC-FTIR Data Employing the

Assessment of Singular Value Evolving Profiles”, Rocky Mountain Conference on Analytical

Chemistry, Denver, Colorado, 1995.

88. D.R. Long-Reitzel, J.H. Kalivas: “Sample Dependent Principal Component Regression”, Rocky

Mountain Conference on Analytical Chemistry, Denver, Colorado, 1995.

89. U. Hörchner, J.H. Kalivas: “Improvement of Calibrations for NIR Spectra by Wavelength

Selection”, Gordon Conference on Statistics in Chemistry and Chemical Engineering, New

Hampton, New Hampshire, 1995.

90. J.H. Kalivas, P.M. Lang: “A Unique Measure of Selectivity for N-Dimensional Data Arrays”,

International Chemical Congress of Pacific Basin Societies, Honolulu, Hawaii, 1995.

91. J.H. Kalivas, U. Hörchner: “Improvements of Calibrations for Near-IR Spectra by Exclusion of

Deteriorated Spectral Regions”, International Chemical Congress of Pacific Basin Societies,

Honolulu, Hawaii, 1995.

92. J.M. Brenchley, J.H. Kalivas: “When Have Enough Wavelengths Been Chosen, and Are They the

Right Ones?”, Northwest Regional American Chemical Society Meeting, Corvallis, Oregon, 1996.

93. G.A. Bakken, D.R. Long, J.H. Kalivas: “Sample Dependent Principal Component Regression”,

Northwest Regional American Chemical Society Meeting, Corvallis, Oregon, 1996.

94. J.M. Brenchley, J.H. Kalivas: “Selecting Effective Wavelengths to Improve Quantitative Analysis4

Based on Near-Infrared Spectra”, Federation of Analytical Chemistry and Spectroscopy Societies

Conference, Kansas City, Missouri, 1996.

95. G.A. Bakken, J.H. Kalivas: “Investigation of Factor Selection in Principal Component

Regression”, Federation of Analytical Chemistry and Spectroscopy Societies Conference, Kansas

City, Missouri, 1996.

96. G.A. Bakken, R.M. Mohseni, T. Houghton, J.H. Kalivas: “Examination of Wavelength Selection

Criteria”, National Meeting of the American Chemical Society, San Francisco, California, 1997.

23

97. J.M. Brenchley, R.G. Nieves, P.M. Lang, J.H. Kalivas: “A Mathematical Stabilization of an

Inherently Unstable Algorithm”, National Meeting of the American Chemical Society, San

Francisco, California, 1997.

98. C.E. Anderson, R.G. Nieves, J.H. Kalivas: “Evaluation of Multi-Order Library Searches”, National

Meeting of the American Chemical Society, San Francisco, California, 1997.

99. R.G. Nieves, J.M. Brenchley, P.M. Lang, J.H. Kalivas: “Relationships Between PCR and PLS by

Cyclic Subspace Regression”, National Meeting of the American Chemical Society, San Francisco,

California, 1997.

100. T.P. Houghton, J.H. Kalivas: “Real-World Chemical Analysis: Incorporation of a Trout Aquarium

in Quantitative Analysis”, National Meeting of the American Chemical Society, Las Vegas,

Nevada, 1997.

101. J.M. Brenchley, G. Scalarone, J.H. Kalivas: “Determination of Disease State by Spectroscopy”,

Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Providence, Rhode

Island, 1997.

102. V. Allen, J.H. Kalivas, R.G. Rodriguez: “Identification of Post Consumer Plastics Using Raman

Spectroscopy”, Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Austin,

Texas, 1998.

103. R. Green, T.P. Houghton, J.H. Kalivas: “Lipid Analysis of Live Trout Using PCR and NIR

Spectroscopy for an Analytical Chemistry Laboratory Course”, Federation of Analytical

Chemistry and Spectroscopy Societies (FACSS), Austin, Texas, 1998.

104. R.L. Green, J.H. Kalivas: “Signal to Noise Assessment of Eigenvectors Based on Cross

Validation”, National Meeting of the American Chemical Society, San Francisco, California,

2000.

105. S.Z. Fairchild, R.L. Green, J.H. Kalivas: “Signal to Noise Assessment of Eigenvectors Based on

Cross Validation”, National Meeting of the American Chemical Society, San Francisco,

California, 2000.

106. J.H. Kalivas, S.Z. Fairchild: “A Better Way to Perform Principal Component Regression”,

International Chemical Congress of Pacific Basin Societies, Honolulu, Hawaii, 2000.

107. J. Clark, J.H. Kalivas: “Potential Application of Ion Mobility for Detection of Adulterated

Perfumes and Plant Speciation”, The Pittsburgh Conference, New Orleans, Louisiana, 2002.

108. K. Anderson, J.H. Kalivas: “Comparison of the Pareto Optimal Modal with PLS for Prediction of

Fetal Lung Maturity Using Amniotic Fluid and Infrared Spectroscopy”, The Pittsburgh

Conference, New Orleans, Louisiana, 2002.

24

109 J.H. Kalivas: “Realizing Work Place Skills in Instrumental Analysis”, National Meeting of the

American Chemical Society, New York, New York, 2003.

110. J.H. Kalivas, H. Seipel: “Determination of Pseudo-Rank and Degrees of Freedom for Multivariate

Calibration”, Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Fort

Lauderdale, Florida, 2003.

111. J.H. Kalivas, J. Forrester: “Using Error information with the L-Curve for Multivariat Calibration”,

Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Fort Lauderdale,

Florida, 2003.

112. J.H. Kalivas, J. Forrester, H. Seipel: “Pareto Optimization of QSAR Date for Model Selection and

Validation”, National Meeting of the American Chemical Society, Anaheim, California, 2004.

113. J. Forrester, J.H. Kalivas: “A Harmonious Approach to the Optimization of Ridge Regression”,

Idaho Academy of Science, Pocatello, Idaho, 2004.

114. H. Seipel, J.H. Kalivas: “Effective Rank for Multivariate Calibration”, Idaho Academy of Science

Pocatello, Idaho, 2004.

115. F.R. Stout, J.H. Kalivas: “Multivariate Spectral Calibration Using Regularization with

Smoothing”, The Pittsburgh Conference, Orlando, Florida, 2005.

116. F.R. Stout, J.H. Kalivas, K. Héberger, O. Farkas: “Determining Essential Molecular Descriptors

For Quantitative Structure Activity Relationship Prediction Models”, International Chemometrics

Conference, CHEMOMETRICS VII, Hungary, 2005.

117. F.R. Stout, J.H. Kalivas: “Tikhonov Regularization with the Vector 1-norm”, Pacifichem 2005

Congress, Honolulu, Hawaii, 2005.

118. F.R. Stout, J.H. Kalivas: “Use of the 1-norm in Pareto Optimization for Wavelength Selection”,

The Pittsburgh Conference, Orlando, Florida, 2006.

119. J.H. Kalivas: “Research Supportive Curriculum with Service Learning in the General Chemistry

Laboratory”, National Meeting of the American Chemical Society, San Francisco, California,

2006.

120. J.H. Kalivas, F.R. Stout: “The Harmony/Parsimony Tradeoff in Multivariate Calibration”,

Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), Orlando, Florida, 2006.

121. P. Forlay-Frick, R. Put, E. Van Gyseghem, J.H. Kalivas, Y. Vander Heyden, and K. Héberger:

“Comparison of Methods for Selection of Dissimilar Reversed-phase HPLC Systems”, The XXXI

Symposium on Chromatographic Methods of Investigating the Organic Compounds, Poland, 2007.

122. J.H. Kalivas, F. Stout, M.R. Baines: “Objective Comparison of Multivariate Calibration Methods”,

Conferentia Chemometrica, Hungary, 2007.

25

123. K. Héberger, J.H. Kalivas: “Similarity and Dissimilarity of C18 (Octadecylsilyl Silica) Columns in

RP-HPLC”, Conferentia Chemometrica, Hungary, 2007.

124. O. Farkas, I.G. Zenkevich, F. Stout, J.H. Kalivas, K. Héberger: “Prediction of Kovats Indicies for

Fatty Acid Methyl Esters. Optimal or Parsimonious Models?”, Conferentia Chemometrica,

Hungary, 2007.

125. J.H. Kalivas, K. Héberger: “Comparison of Methods for Selection of Chromatographic Columns”,

Conference on Chemometrics in Analytical Chemistry, France, 2008.

126. H.C. Goicoechea, G.G. Siano, E. Andries, J.H. Kalivas: “Double Regularization for Temperature

Correction with Tikhonov Regularization. Application to Calibration Transfer”, Conference on

Chemometrics in Analytical Chemistry, France, 2008.

127. B. Cole, J.H. Kalivas: “Calibration Maintenance and Transfer Using Multiple Linear Regression

Based Modeling of New Spectral Variances”, Conferentia Chemometrica, Hungary, 2009.

128. S. B. Cole, J.H. Kalivas: “Calibration Maintenance and Transfer Using Multiple Linear Regression

Based Modeling of New Spectral Variances”, Society of Photo-Optical Instrumentation Engineers

(SPIE) Defense, Security, and Sensing, Orlando, Florida, 2010.

129. J.H. Kalivas, J. Ottaway: “Net Analyte Signal as a Prediction Error Proxy for Multivariate

Calibration”, Society of Photo-Optical Instrumentation Engineers (SPIE) Defense, Security, and

Sensing, Orlando, Florida, 2010.

130. J.H. Kalivas, J.M. Ottaway, M.R. Kunz, E. Andries: “Multiple Uses of Tikhonov Regularization in

Multivariate Calibration”, Society of Photo-Optical Instrumentation Engineers (SPIE) Defense,

Security, and Sensing, Orlando, Florida, 2010.

131. J.M. Ottaway, J.H. Kalivas, E. Andries: “Wavelength Selection for Multivariate Calibration Using

Tikhonov Regularization”, Society of Photo-Optical Instrumentation Engineers (SPIE) Defense,

Security, and Sensing, Orlando, Florida, 2010

132. M. R. Kunz, J.H. Kalivas, E. Andries: “Calibration Maintenance and Transfer with Wavelength

Selection Tikhonov Regularization”, Society of Photo-Optical Instrumentation Engineers (SPIE)

Defense, Security, and Sensing, Orlando, Florida, 2010.

133. J.A. Farrell, K. Higgins, J.H. Kalivas: “Updating a Near-Infrared (NIR) Multivariate Calibration

Model Formed with Lab Prepared Pharmaceutical Tablet Types in Full Production”, Pittcon,

Atlanta, Georgia, 2011.

134. J. Ottaway, J.A. Farrell, J.H. Kalivas: “Spectral Multivariate Calibration Without Reference

Samples via Tikhonov Regularization”, Pittcon, Atlanta, Georgia, 2011.

135. K. Higgins, J.H. Kalivas, C.A. Georgiou: “Using Net Analyte Signal (NAS) to Identify an

Adulterant in Extra Virgin Olive Oil”, Pittcon, Atlanta, Georgia, 2011.

26

136. J.H. Kalivas, M.R. Kunz, J. Ottaway, C.A. Georgiou, G.A. Mousdis: “Updating a Synchronous

Fluorescence Spectroscopic Virgin Olive Oil adulteration Calibration to a New Geographic

Region”, American Oil Chemists Society Annual Meeting and Expo, Cincinnati, Ohio, 2011.

137. K. Higgins, J.H. Kalivas: “Application of Spatial Angular Measurements for Classification

Purposes”, Conferentia Chemometrica, Hungary, 2011.

138. J. Farrell, J. Ottaway, J.H. Kalivas: “Multivariate Calibration by Updating an Analyte Pure

Component Spectrum to the Current Sample Matrix”, Federation of Analytical Chemistry and

Spectroscopy Societies (FACSS), Reno, Nevada, 2011.

139. K. Higgins, J.H. Kalivas: “Model Updating by Adjusting the Model Magnitude”, Federation of

Analytical Chemistry and Spectroscopy Societies (FACSS), Reno, Nevada, 2011.

140. J.H. Kalivas, C.A. Georgiou, M. Mira, I. Tsafaras, G.A. Mousdis, E. Petrakis: “Multivariate

Calibration for Extra Virgin Olive Oil Adulteration without Reference Samples”, Federation of

Analytical Chemistry and Spectroscopy Societies (FACSS), Reno, Nevada, 2011.

141. J.H. Kalivas, K. Higgins: “A New Use of Target Factor Analysis (TFA)”, Eighth Winter

Symposium on Chemometrics, Drakino, Russia, 2012.

142. J.H. Kalivas, K. Higgins, C.A. Georgiou, M. Mira, I. Tsafaras, G.A. Mousdis, E. Petrakis:

“Development of a Spatial Angular Measurement for Extra Virgin Olive Oil Classification

Followed by Multivariate Calibration without Reference Samples”, American Oil Chemists

Society Annual Meeting and Expo, Long Beach, California, 2012.

143. J.A. Farrell, J. Ottaway, J.H. Kalivas: “Multivariate Calibration and Maintenance Using No

Reference Samples”, Council on Undergraduate Research (CUR) Undergraduate Poster Session on

Capitol Hill, Washington DC, 2012.

144. J.H. Kalivas, J. Palmer: “Algorithm Development of the Net Analyte Signal Geometry as a

Prediction Error Proxy for Multivariate Calibration Model Selection”, XIII Chemometrics in

Analytical Chemistry, Budapest, Hungary, 2012.

145. K. Higgins, J.H. Kalivas: “Assessment of Sample Selection Methods for Local Modeling”, SciX

2102, Kansas City, Missouri, 2012.

146. J. Palmer, J.H. Kalivas: “Localized Model Selection for Multivariate Calibration Using Tikhonov

Regularization with Net Analyte Signal”, SciX 2102, Kansas City, Missouri, 2012.

147. T. O’Loughlin, J.H. Kalivas, P. Shahbazikhah: “Multivariate Calibration and Maintenance Using

Principal Component Selection”, SciX 2102, Kansas City, Missouri, 2012.

148. J.H. Kalivas, J.A. Farrell, J. Ottaway: “Calibration and Maintenance without Laboratory Prepared

or Determined Reference Analyte Values”, SciX 2102, Kansas City, Missouri, 2012.

27

149. J.H. Kalivas, E. Andries: “Obtaining Net Analyte Signal Preprocessing Simultaneously with

Calibration using Tikhonov Regularization”, PittCon 2013, Philadelphia, Pennsylvania, 2013.

150. K. Higgins, J.H. Kalivas: “Assessment of a New Similarity Measure for Local Calibration”,

Council on Undergraduate Research (CUR) Undergraduate Poster Session on Capitol Hill,

Washington DC, 2013.

151. J. Palmer, J.H. Kalivas: “Net Analyte Signal Geometry Facilitates Model Selection for

Multivariate Calibration with Ridge Regression and Partial Least Squares”, SciX 2013,

Milwaukee, Wisconsin, 2013.

152. J.H. Kalivas: “An Overview of Tikhonov Regularization Processes for Multivariate Calibration”,

Southwest Analytical Professors Meeting 2014, Phoenix, Arizona.

153. A.J. Tencate, J.H. Kalivas, E. Andries: “Regularization Processes for Combining Roughness and

Smoothing in a Multivariate Calibration Model”, XIV Chemometrics in Analytical Chemistry,

Richmond, Virginia, 2014.

154. B.R. Brownfield, J.H. Kalivas: “Improving Outlier Detection by Fusion of Outlier Detection

Merits Using Sum of Ranking Differences”, XIV Chemometrics in Analytical Chemistry,

Richmond, Virginia, 2014.

155. A.J. Tencate, J.H. Kalivas, E. Andries: “Regularization Processes for Combining Roughness and

Smoothing in a Spectroscopic Multivariate Calibration Model”, SciX 2014, Reno, Nevada.

156. B.R. Brownfield, J.H. Kalivas: “Outlier Detection by Fusion of Multiple X and y Merits Using

Sum of Ranking Differences”, SciX 2014, Reno, Nevada.

157. A.J. White, J.H. Kalivas: “Development of Sum of Ranking Differences (SRD) for Automatic

Selection of Multiple Tuning Parameters in Spectroscopic Multivariate Calibration Maintenance”,

SciX 2014, Reno, Nevada.

158. B.J. Karki, J.H. Kalivas: “Adapting Multivariate Calibration Model to New Spectral

Interferences”, SciX 2014, Reno, Nevada.

159. O.J. Carrillo, J.H. Kalivas: “Localizing a Global Spectroscopic Multivariate Calibration Model”,

SciX 2014, Reno, Nevada.

160. J.H. Kalivas, K. Héberger, E. Andries: “Multivariate Calibration Tuning Parameter Selection by

Sum of Ranking Differences (SRD) with Multiple Merits”, SciX 2014, Reno, Nevada.

161. I. Unobe, J.H. Kalivas, R. Rodriguez, A. Sorensen, L. Lau, J. Davis: “Infrared Thermal Imaging

for Use in Restoration of Defaced Serial Numbers”, International Association for Spectral Imaging

(IASIM), Rome, Italy, December 2014.

28

162. I. Unobe, R. Rodriguez, J.H. Kalivas, A. Sorensen, L. Lau, J. Davis: “Defaced Serial Number

Recovery Using Infrared Thermography”, Association of Firearm and Tool Mark Examiners,

Dallas, Texas, May 2015.

163. B.R. Brownfield, J.H. Kalivas: “Outlier Detection and Quality Control by Fusion of Multiple

Merits”, American Chemical Society Northwest Regional Meeting 2015, Pocatello, Idaho.

164. A.J. Tencate, J.H. Kalivas, E. Andries: “Development and Assessment of Tikhonov Regularization

and PLS to Form Smoothed Multivariate Calibration Models”, American Chemical Society

Northwest Regional Meeting 2015, Pocatello, Idaho.

165. A.J. Tencate, J.H. Kalivas, A.J. White: “Development of Multiple Merit Ranking Methods for

Automatic Selection of Multiple Tuning Parameters in Multivariate Calibration and Maintenance”,

SciX 2015, Providence, Rhode Island, 2015.

166. Kalivas. L. Lau: “Recovery of Defaced Serial Numbers

Using Lock-in Infrared Thermography”, Idaho Academy of Science, Boise, 2016.

167. J.H. Kalivas, J. Ferré, A.J. Tencate: “Selectivity-Relaxed Classical and Inverse Least Squares

Calibration and Selectivity Measures”, Chemometrics in Analytical Chemistry, Barcelona, Spain,

2016.

168. T. Lemos, J.H. Kalivas: “An Ensemble of Multiple Linear Regression Models for Easy

Wavelength Selection”, SciX 2016, Minneapolis, Minnesota, 2016.

169. A. Gurung, J.H. Kalivas, E. Andries: “Regularization Adaption Processes with Labeled and

Unlabeled Data for Multivariate Calibration Maintenance”, SciX 2016, Minneapolis, Minnesota,

2016.

170. W. Spence, J.H. Kalivas: “Reducing Spectral Analyte Prediction Error with Penalties on

Interferents”, SciX 2016, Minneapolis, Minnesota, 2016.

171. A. Gurung, J.H. Kalivas, E.Andries: “Regularization Adaption Processes for Multivariate

Calibration Maintenance”, Idaho Conference on Undergraduate Research, Boise, Idaho, 2016.

http://scholarworks.boisestate.edu/icur/2016/Poster_Session/49/

172. W. Spence, J.H. Kalivas: “Reducing Spectral Analyte Prediction Error with Penalties on

Interferents”, Idaho Conference on Undergraduate Research, Boise, Idaho, 2016.


173. I.D. Unobe, R.Rodriguez, A. Sorenson, J. Kalivas, L. Lau: “Potential of Lock-in Infrared

Thermography for the Recovery of Defaced Serial Numbers”, International Congress of

Technology, Management and Social Sciences, Toronto, Canada, 2016.



29

174. I.D. Unobe, R.Rodriguez, J. Kalivas, A. Sorenson, L. Lau: “Recovery and Validation of Defaced

Serial Numbers Using Infrared Thermal Imaging”, Association of Firearm and Tool Mark

Examiners, Denver, Colorado, May 2017.

175. A. Gurung, J.H. Kalivas, E.Andries: “Fine Tuning Model Updating for Multivariate Calibration

Maintenance”, Idaho Conference on Undergraduate Research, Boise, Idaho, 2017.


176. T. Lemos, J.H. Kalivas: “Leveraging Multiple Linear Regression for Wavelength Selection”,

Idaho Conference on Undergraduate Research, Boise, Idaho, 2017.


177. T. Stokes, M. Foteini, B. Brownfield, J.H. Kalivas, G. Mousdisc, A. Amined, C. Georgioub:

“Fusion of Synchronous Fluorescence Spectra with Application to Argan Oil for Adulteration

Analysis”, Idaho Conference on Undergraduate Research, Boise, Idaho, 2017.


178. J. Kalivas, B. Brownfield: “Rethinking the Classification Process with Data Fusion”, SciX 2017,

Reno, Nevada, 2017.

179. T. Lemos, J. Kalivas: “Leveraging Multiple Linear Regression for Wavelength Selection”, SciX

2017, Reno, Nevada, 2017.

180. A. Gurung, J. Kalivas, E. Andries: “Fine Tuning Model Updating for Multivariate Calibration

Maintenance”, SciX 2017, Reno, Nevada, 2017.

181. J.H. Kalivas, I.D. Unobe, R.Rodriguez, A. Sorenson, L. Lau: “Non-Destructive Identification of

Defaced Serial Numbers on Metal Surfaces”, International Caparica Conference in Translational

Forensics 2017, Caparica-Lisbon, Portugal, November 2017.

182. J. Kalivas, B. Brownfield, T. Lemos: “Consensus Classification Using Non-Optimized Models”,

Society of Western Analytical Professors Annual Meeting, Seattle, Washington, January 2018.

183. I.D. Unobe, L. Lau, R.Rodriguez, J. Kalivas, A. Sorenson: “Recovery of Defaced Serial Numbers

Using Lock-In Thermography”, PittCon, Orlando, Florida, February - March 2018.

184. E. Andries, J.H. Kalivas, A. Gurung: “Transductive Calibration Updating”, Chemometrics in

Analytical Chemistry, Halifax, Canada, June 2018.

185. T. Lemos, J.H. Kalivas: “Classification Using Sum of Ranking Differences of Outlier Measures”,

Idaho Conference on Undergraduate Research, Boise, Idaho, 2018.

https://scholarworks.boisestate.edu/icur/2018/Poster_Session/164/

186. B. Chabuka, J.H. Kalivas: “Raman Spectroscopy and Fusion Classification to

Identify Plastic Recyclables Targeting Microplastics”, Idaho Conference on Undergraduate

Research, Boise, Idaho, 2018. https://scholarworks.boisestate.edu/icur/2018/Poster_Session/24/






30

187. J.H. Kalivas, R. Emerson, T. Lemos: “Assessing the Degree of a Sample Matrix Match

(Chemically, Physically, and Instrumentally) to a Calibration Set”, SciX 2018, Atlanta, Georgia,

2018.

188. T. Lemos, J.H. Kalivas: “One-Class Classification using Sum of Ranking Differences of Outlier

Measures with Application to Food Authentication”, SciX 2018, Atlanta, Georgia, 2018.

189. T. Lemos, J.H. Kalivas: “Enhanced Food Authentication with Data Fusion Processes”, SciX 2018,

Atlanta, Georgia, 2018.

190. J.H. Kalivas, T. Lemos: “Transforming the Classification Process with Data Fusion of Non-

Optimized Classifiers”, Pittcon, Philadelphia, Pennsylvania, March 2019.

191. E. Andries, J.H. Kalivas: “Calibration Updating Using Unlabeled Secondary Samples”,

Scandinavian Symposium on Chemometrics (SSC16), Oslo, Norway, 2019.

192. C. Norby, J.H. Kalivas: “Fusion of Similarity Measures to Characterize Differences in Sample

Spectral Matrix Effects”, American Chemical Society Northwest Regional Meeting 2019,

Portland, Oregon.

193. C. Norby, J.H. Kalivas: “Fusion of Similarity Measures to Characterize Differences in Sample

Matrix Effects”, Idaho Conference on Undergraduate Research, Boise, Idaho, 2019.


194. R. Spiers, J.H. Kalivas: “Harnessing Model Diversity and Prediction Similarity for Selecting

Multivariate Calibration Tuning Parameters”, Idaho Conference on Undergraduate Research,

Boise, Idaho, 2019. https://scholarworks.boisestate.edu/icur/2019/Poster_Session/135/

195. R. Spiers, J.H. Kalivas, “Using Model Diversity and Prediction Similarities of Unlabeled Samples

for Model Selection of Multivariate Calibration Updating Methods”, SciX 2019, Palm Springs,

Calif., 2019.

196. C. Norby, J.H. Kalivas, “Fusion of Similarity Measures as an Indicator of Spectral Uniqueness

(ISU) to Characterize Differences in Sample Matrix Effects”, SciX 2019, Palm Springs, Calif.,

2019.

197. A. Pahlavan, S. Khodadadi, J. Kalivas, H. Abdollahi, “Local Calibration Using Multivariate Curve

Resolution Methods”, SciX 2019, Palm Springs, Calif., 2019.

198. R.Spiers, J.H. Kalivas, “Multivariate Calibration Domain Adaptation with Unlabeled Data”, Idaho

Conference on Undergraduate Research (on-line), Boise, Idaho, 2020.

199. R. Spiers, J.H. Kalivas, “Model Updating and Selection Frameworks without Reference Values

(Calibration Standards)”, Selected for Broadcast Session. National Meeting of the American

Chemical Society (on-line), San Francisco, California, 2020.



VITAE...VITAE John Herschell Kalivas Address: Department of Chemistry Idaho State University...

Documents

Transcript of VITAE...VITAE John Herschell Kalivas Address: Department of Chemistry Idaho State University...