A. Invited Talks:

[38] Automated Geometric Shape Deviation Modeling for Cyber-Physical Additive Manufacturing Systems via Bayesian Neural Networks - University of Southern California, Los Angeles, CA, March 21, 2018.

[37] Input Correction Algorithms to Produce Better Quality Parts - Second Foundation of Accuracy Control for Additive Manufacturing Workshop (FACAM 2018), Los Angeles, CA, February 8, 2018.

[36] Deviation Modeling Across Different Process Conditions and Shapes in Additive Manufacturing Systems - Second Foundation of Accuracy Control for Additive Manufacturing Workshop (FACAM 2018), Los Angeles, CA, February 8, 2018.

[35] Model Transfer Across Additive Manufacturing Processes via Mean Effect Equivalence of Lurking Variables - University of Louisville Department of Bioinformatics and Biostatistics Seminar Series, Louisville, KY, February 2, 2018.

[34] Predictive Model Building Across Different Process Conditions and Shapes in 3D Printing - INFORMS 2017 Annual Meeting, Houston, TX, October 22, 2017.

[33] Predictive Model Building Across Different Process Conditions and Shapes in Additive Manufacturing - Sandia National Laboratories Statistical Sciences Colloquium, Albuquerque, NM, September 21, 2017.

[32] Predictive Model Building Across Different Process Conditions and Shapes in Additive Manufacturing - Accelerating NSF Research in Additive Manufacturing toward Industrial Applications Workshop, Pittsburgh, PA, August 18, 2017.

[31] Deformation Model Transfer via Equivalent Effects of Lurking Variables in Additive Manufacturing - 2017 Joint Statistical Meetings, Baltimore, MD, August 2017.

[30] Predictive Model Building Across Different Process Conditions and Shapes in 3D Printing - 24th Annual ASA/IMS Spring Research Conference on Statistics in Industry and Technology, New Brunswick, NJ, May 18, 2017.

[29] Deformation Model Transfer via Equivalent Effects of Lurking Variables in Additive Manufacturing - Purdue University School of Industrial Engineering Seminar Series, West Lafayette, IN, February 8, 2017.

[28] Deformation Model Transfer via Equivalent Effects of Lurking Variables in Additive Manufacturing - INFORMS 2016 Annual Meeting, Nashville, TN, November 13, 2016.

[27] Model Transfer via Equivalent Effects of Lurking Variables - 2016 NIC-ASA and ICSA Midwest Joint Fall Meeting, Lincolnshire, IL, November 11, 2016.

[26] Smart Calibration Through Deep Learning for High-Confidence and Interoperable Cyber-Physical Additive Manufacturing Systems - 2016 National Science Foundation Cyber-Physical Systems Program Principal Investigators Meeting , Arlington, VA, October 31, 2016.

[25] Hidden Connections Between Different Projections under the Linear-Quadratic Parameterization - 2016 International Conference on Advances in Interdisciplinary Statistics and Combinatorics, Greensboro, NC, September 30, 2016.

[24] Predictive Model Building Across Different Process Conditions and Shapes in 3D Printing - Twelfth Annual IEEE International Conference on Automation Science and Engineering, Forth Worth, TX, August 23, 2016.

[23] Discussion of Powerful Experimental Designs for Non-Gaussian Responses Invited Session - 2016 Joint Statistical Meetings, Chicago, IL, August 3, 2016.

[22] Partial Aliasing Relations in Mixed Two- and Three-Level Designs - 2016 ICSA Applied Statistics Symposium, Atlanta, GA, June 14, 2016.

[21] Causal Model Transfer via Equivalent Effects of Lurking Variables - 23nd Annual ASA/IMS Spring Research Conference on Statistics in Industry and Technology, Chicago, IL, May 25, 2016.

[20] Causal Model Transfer via Equivalent Effects of Lurking Variables - Theoretical Foundations for Accuracy Control in Additive Manufacturing Workshop (FACAM 2016), Los Angeles, CA, January 18, 2016.

[19] Model Building from Small Samples of Disparate Data in 3D Printing - Theoretical Foundations for Accuracy Control in Additive Manufacturing Workshop (FACAM 2016), Los Angeles, CA, January 18, 2016.

[18] New Perspectives on Tests for Co-Primary and Secondary Endpoints - Epstein Institute Seminar, Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA, November 17, 2015.

[17] Partial Aliasing Relations in Mixed Two- and Three-Level Designs - INFORMS 2015 Annual Meeting, Philadelphia, PA, November 4, 2015.

[16] Bayesian Additive Modeling for Quality Control of 3D Printed Products - INFORMS 2015 Annual Meeting, Philadelphia, PA, November 1, 2015.

[15] Bayesian Additive Modeling for Quality Control of 3D Printed Products - Eleventh Annual IEEE International Conference on Automation Science and Engineering (CASE 2015), Gothenburg, Sweden, August 26, 2015.

[14] New Perspectives on Randomization Tests for Co-Primary and Secondary Endpoints - 2015 Joint Statistical Meetings, Seattle, WA, August 10, 2015.

[13] Hidden Connections Between Different Projections under the Linear-Quadratic Parameterization - 60th ISI World Statistics Congress, Rio de Janeiro, Brazil, July 27, 2015.

[12] Hidden Connections Between Different Projections under the Linear-Quadratic Parameterization - 32nd Quality & Productivity Research Conference, Raleigh, NC, June 11, 2015.

[11] Bayesian Additive Modeling for Quality Control of 3D Printed Products - 32nd Quality & Productivity Research Conference, Raleigh, NC, June 10, 2015.

[10] Inference for Deformation and Interference in 3D Printing - 2nd Workshop on Predictive Modeling and Control of Additive Manufacturing, Epstein Institute at the Viterbi School of Engineering, University of Southern California, Los Angeles, CA, November 13, 2014.

[9] Projection Properties of Three-Level Fractional Factorial Designs under the Linear-Quadratic System - INFORMS 2014 Annual Meeting, San Francisco, CA, November 9, 2014.

[8] Interference in Deformation Compensation for 3D Printing - NASA Engineering and Safety Center's (NESC) Engineering Statistics Team, May 21, 2014.

[7] The Power of Potential Outcomes in Experimental Design: From the Neyman-Fisher Controversy to 3D Printing - Department of Statistics, Purdue University, West Lafayette, IN, February 26, 2014.

[6] Posterior Predictive Checks for Interference in a 3D Printing Experiment - 2014 ASA Conference on Statistical Practice, Tampa, FL, February 22, 2014.

[5] Expeditions in Modern Experimental Design: Partial Aliasing and Interference - Department of Statistics, Stanford University, Stanford, CA, February 11, 2014.

[4] Expeditions in Modern Experimental Design: Partial Aliasing and Interference - Department of Statistics, University of California Berkeley, Berkeley, CA, February 5, 2014.

[3] The Power of Potential Outcomes in Experimental Design: From the Neyman-Fisher Controversy to 3D Printing - Booth School of Business, University of Chicago, Chicago, IL, January 30, 2014.

[2] The Power of Potential Outcomes in Experimental Design: From the Neyman-Fisher Controversy to 3D Printing - Department of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, January 23, 2014.

[1] Inference for Deformation and Interference in 3D Printing - Stuart School of Business, Illinois Institute of Technology, Chicago, IL, October 22, 2013.


B. Contributed Talks:

[7] Bayesian Additive Modeling for Quality Control of 3D Printed Products - 22nd Annual ASA/IMS Spring Research Conference on Statistics in Industry and Technology, Cincinnati, OH, May 21, 2015.

[6] Interference in Deformation Compensation for 3D Printing - 16th Meeting of New Researchers in Statistics and Probability, Cambridge, MA, August 1, 2014.

[5] Inference With Interference And Interference For Inference in a 3D Printing Experiment - INFORMS 2013 Annual Meeting, Minneapolis, MN, October 9, 2013.

[4] Indicator Functions and the Algebra of the Linear-Quadratic Parametrization - INFORMS 2013 Annual Meeting, Minneapolis, MN, October 7, 2013.

[3] Inference with Interference and Interference for Inference: Modeling Potential Outcomes and Interference in a 3D Printing Experiment - 2013 Joint Statistical Meetings, Montreal, Canada, August 5, 2013.

[2] Interesting Insights in Indicators: Indicator Functions and the Algebra of the Linear-Quadratic Parametrization - 20th Annual ASA/IMS Spring Research Conference on Statistics in Industry and Technology, Los Angeles, CA, June 22, 2013.

[1] Inference with Interference and Interference for Inference: Modeling Potential Outcomes and Interference in a 3D Printing Experiment - 30th Quality and Productivity Research Conference, Niskayuna, NY, June 5, 2013.


C. Purdue Statistics Talks:

[5] Sports and Statistics, or, a Bayesian is Better at Betting on Basketball - 2017 Cary Quadrangle Talks, West Lafayette, IN, September 26, 2017.

[4] Challenges and Opportunities in Statistical Quality Control for 3D Printing - Statistics Living-Learning Community Spring 2015 Seminar (STAT 290: Rising Above the Gathering Storm), West Lafayette, IN, October 27, 2015.

[3] Challenges and Opportunities in Statistical Quality Control for 3D Printing - Exploring Statistical Sciences Research Seminar, West Lafayette, IN, September 23, 2015.

[2] Causal Inference under the Potential Outcomes Framework: History, Applications, Challenges - Statistics Living-Learning Community Spring 2015 Seminar (STAT 290: What is the Big Idea?), West Lafayette, IN, March 10, 2015.

[1] Causal Inference under the Potential Outcomes Framework: History, Applications, Challenges - Exploring Statistical Sciences Research Seminar, West Lafayette, IN, October 8, 2014.


D. Contributed Posters:

[6] Automated Geometric Shape Deviation Modeling for Additive Manufacturing Processes via Bayesian Neural Networks - 2017 National Science Foundation Cyber-Physical Systems Program Principal Investigators Meeting, Arlington, VA, November 13, 2017.

[5] An Algebra for Conditional Main Effects - The Design and Analysis of Experiments (DAE 2017), Los Angeles, CA, October 12, 2017.

[4] Learning and Recalibration With Small Sets of Shapes for 3D Printing - 2016 National Science Foundation Cyber-Physical Systems Program Principal Investigators Meeting, Arlington, VA, October 31, 2016.

[3] Interference in Deformation Compensation for 3D Printing - 16th Meeting of New Researchers in Statistics and Probability, Cambridge, MA, August 1, 2014.

[2] Indicator Functions under the Linear-Quadratic Parametrization - 19th Annual ASA/IMS Spring Research Conference on Statistics in Industry and Technology, Cambridge, MA, June 13, 2012.

[1] Who was Right about ANOVA for Latin Squares: Neyman or Fisher? - 2012 Atlantic Causal Inference Conference, Baltimore, MD, May 24, 2012.


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