C.V.
Click here for a recent pdf version or check out my google scholar profile.
EDUCATION
Ph.D., Statistics, Cornell University (2015)
M.S., Statistics, Cornell University (2013)
B.S., Mathematics, Bucknell University (2010)
Ph.D., Statistics, Cornell University (2015)
M.S., Statistics, Cornell University (2013)
B.S., Mathematics, Bucknell University (2010)
PUBLICATIONS
Siyu Zhou and Lucas Mentch. (2021+) “Trees, Forests, Chickens, and Eggs: When and Why to Prune Trees in a Random Forest.” Under Review. arXiv Researchers.One
Lucas Mentch and Siyu Zhou. (2021+) “Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance.” Under Review. arXiv Researchers.One
Wei Peng, Tim Coleman, and Lucas Mentch. (2021+) “Rates of Convergence for Random Forests via Generalized U-statistics.” Under Review. arXiv
Tim Coleman, Wei Peng, and Lucas Mentch. (2021+) “Scalable and Efficient Hypothesis Testing with Random Forests.” Under Review. arXiv
Wei Peng, Lucas Mentch, and Len Stefanski. (2021+) "Bias, Consistency, and Alternative Perspectives of the Infinitesimal Jackknife." Under Review. arXiv
Lucas Mentch, Nick Kissel. (2021+) “Forward Stability and Model Path Selection.” Under Review. arXiv Researchers.One
Giles Hooker, Lucas Mentch, and Siyu Zhou. (2021) "Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance." Statistics and Computing. Just Accepted. arXiv
Zhengze Zhou, Lucas Mentch, and Giles Hooker. (2021) “V-Statistics and Variance Estimation.” Journal of Machine Learning Research. Just Conditionally Accepted. arXiv
Lucas Mentch and Giles Hooker. (2021) “Bridging Breiman’s Brook: From Algorithmic Modeling to Statistical Learning”. Observational Studies: Commentaries on the 20th anniversary of the publication of Leo Breiman’s “Statistical Modeling: The Two Cultures”. arXiv
Wallace ML, Coleman TS, Mentch LK, Buysse DJ, Graves JL, Hagen EW, Hall MH, Stone KL, Redline S, Peppard PE. (2021) “Physiological Sleep Measures Predict Time to 15-Year Mortality in Community Adults: Application of a Novel Machine Learning Framework.” Journal of Sleep Research. e13386. JoSR
Ashely Griffin, Feng-Chang Lin, Lucas Mentch, and Arlene Chung. (2021) “Precision VISSTA Study: mHealth Physical Activity Patterns and Patient-Reported Outcomes in Patients with Inflammatory Bowel Diseases.” AMIA 2021 Annual Symposium.
Lucas Mentch and Siyu Zhou. (2020) “Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success.” Journal of Machine Learning Research. 21(171), pp. 1-36. JMLR arXiv
Tim Coleman, Kimberly Kaufeld, Mary Frances Dorn, and Lucas Mentch. (2020) “Locally Optimized Random Forests.” STAT. Just Accepted. arXiv
Taehee Jung, Dongyeop Kang, Hua Cheng, Lucas Mentch, and Thomas Schaaf. “Posterior Calibrated Training on Sentence Classification Tasks.” 2020 Annual Conference of the Association for Computational Linguistics. 2020.acl-main.242, 2723–2730. arXiv ACL
Tim Coleman, Lucas Mentch, Daniel Fink, Frank La Sorte, David Winkler, Giles Hooker, and Wesley Hochachka. (2020) "Statistical Inference on Tree Swallow Migration with Random Forests." Journal of the Royal Statistical Society, Series C. 69(4), 973-989. arXiv JRSS-C
Richard McAlexander and Lucas Mentch. (2020) “Predictive Inference with Random Forests: A New Perspective on Classical Analyses.” Research and Politics. 7(1), 2053168020905487. R&P
Lucas Mentch. (2020) “On Racial Disparities in Recent Fatal Police Shootings.” Statistics and Public Policy. 7(1), 9-18. arXiv SPP (#1 SPP Most read article of 2020)
Taehee Jung, Dongyeop Kang, Lucas Mentch, and Eduard Hovy. (2019) “Earlier Isn’t Always Better: Studying Corpus Biases in Summarization.” Empirical Methods in Natural Language Processing (EMNLP) 2019. D19-1327, 3324–3335. arXiv EMNLP
Tim Coleman, Lucas Mentch, Kimberly Glass, David Gotz, Nils Gehlenborg, and Arlene Chung. (2019) “Precision VISSTA: Machine Learning Prediction and Inference for Bring-Your-Own-Device (BYOD) mHealth Data”. AMIA 2019 Annual Symposium. AMIA
Arlene Chung, Kimberly Glass, Jacob Leisey-Bartsch, Lucas Mentch, Nils Gehlenborg, and David Gotz. (2019) “Precision VISSTA: a BYOD mHealth Cohort for Precision Health”. AMIA 2019 Annual Symposium. AMIA
Robin Richter, Carsten Gottschlich, Lucas Mentch, Duy H. Thai, and Stephan Huckemann. (2019) “A Quality Estimator for Fingerprints and its Validation Scheme.” IEEE Transactions on Information Forensics & Security. 14(8), 1963-1974. IEEE
Duy Hoang Thai and Lucas Mentch. (2018) "Multiphase Segmentation for Simultaneously Homogeneous and Textural Images.'' Applied Mathematics and Computation, 335, 146-181. AM&C arXiv
Oliver Lindhiem, Isaac T. Petersen, Lucas Mentch, and Eric A. Youngstrom. (2018) “The Importance of Calibration in Clinical Psychology.” Assessment. 1073191117752055. SAGE
Hooker, G., & Mentch, L. (2018). "Bootstrap bias corrections for ensemble methods." Statistics and Computing, 28(1), 77-86. S&C arXiv
Mentch, L., & Hooker, G. (2017). "Formal Hypothesis Tests for Additive Structure in Random Forests." Journal of Computational and Graphical Statistics, 26(3), 589-597. JCGS arXiv
Mehrmohamadi, M., Mentch, L. K., Clark, A. G., & Locasale, J. W. (2016). Integrative modelling of tumour DNA methylation quantifies the contribution of metabolism. Nature communications, 7, 13666. NatureComm bioRXiv
Giles Hooker and Lucas Mentch, (2016) "Comments on: A Random Forest Guided Tour." TEST, 25(2), pp. 254-260. TEST
Lucas Mentch and Giles Hooker. (2016) "Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests." The Journal of Machine Learning Research. 17(26), pp. 1-41. JMLR arXiv
Bar, Haim, and Lucas Mentch. (2017) "R-CMap—An open-source software for concept mapping." Evaluation and Program Planning 60 (2017): 284-292. EPP PubMed
Frey, M.R., Miller, A.L., Mentch, L.K., and Grahm, J. (2010) "Score Operators of a Qubit with Applications", Quantum Information Processing, 9(5), 629. QIP
Frey, M.R., Coffey, L.E., Mentch, L.K., Miller, A.L., and Rubin, S.S. (2010) "Correlation Identification in Bipartite Pauli Channels", International Journal of Quantum Information, 8(7). IJQI
Frey, M.R., Coffey, L.K., Mentch, L.K., Miller, A.L. and Rubin, S.S. (2010) "Pauli channels exhibit a transition effect in memory estimation above a parametric threshold," Proceedings of SPIE, Quantum Information and Computation VIII, E.J. Donkor, A.R. Pirich, and H.E. Brandt, eds., April 2010.
Book Chapters:
Maria Cuellar, Lucas Mentch, and Cliff Spiegelman. “Association Does not Imply Discrimination: Flawed Analyses that Lead to Misinterpretations and Wrongful Convictions.” Handbook of Forensic Statistics. Chapman & Hall / CRC Handbooks of Modern Statistical Methods. Eds David Banks, Karen Kafadar, and David Kaye.
Short Conference Publications, Technical Reports, & Op-Eds:
Lucas Mentch. “Don’t Throw the Baby out with the Pandemic: A Comment on “Naive Probabilism” by Harry Crane.” Researchers.One. February 23, 2021.
ML Wallace, E Hagan, Tim Coleman, Lucas Mentch, DJ Buysse, MH Hall, S Redline, P Peppard. “Self-report And Polysomnography Sleep and Mortality in Adults: A Machine Learning Replication Analysis.” SLEEP 2020, 34th Annual Meeting of the Associated Professional Sleep Societies, LLC (APSS). Philadelphia, PA, June 17, 2020.
Siyu Zhou and Lucas Mentch. "Explaining the Practical Success of Random Forests." 2020 Symposium on Statistics and Data Science (SDSS). Pittsburgh, PA, June 5, 2020.
Tim Coleman and Lucas Mentch. "Locally Optimized Random Forests, a Solution to Forecasting Severe Hurricane Power Outages." 2020 Symposium on Statistics and Data Science (SDSS). Pittsburgh, PA, June 5, 2020.
Kim Beals, Karen A. Keenan, Nicholas J. Kissel, Lucas Mentch, Wuxin Yang*, Bradley C. Nindl, and Qi Mi. “Prediction of Lower Extremity Musculoskeletal In- juries for Naval Special Warfare Operators: A Machine Learning Approach.” Medicine and Science in Sports and Exercise, Volume 50:5 Supplement. Presented at: World Congress on Exercise is Medicine and World Congress on the Basic Science of Muscle Hypertrophy and Atrophy of the American College of Sports Medicine. Minneapolis, MN, June 1, 2018.
Nicholas J. Kissel and Lucas Mentch. “The Role of HbA1c in Hospital Readmission of Diabetic Patients.” Presented at the ACC Meeting of the Minds Conference. Boston College University, Chestnut Hill, MA, April 6-8, 2018.
Zachary Fulker, Tyler Folta, and Lucas Mentch. “Investigation of Advanced NBA Metrics.” Carnegie Mellon University Sports Analytics Conference. Abstract Accepted. October 28, 2017.
Lucas Mentch, Maria Cuellar, William Thompson, and Cliff Spiegelman. "The Next Page: Four experts explain why forensic analysis of crime scenes is not as reliable as you might think.'' Pittsburgh Post Gazette. March 13, 2016.
William Thompson, Lucas Mentch, Maria Cuellar, and Cliff Spiegelman. "Who should control Houston's crime lab?'' Houston Chronicle. May 31, 2016.
Frey, M.R., Graham, J., Mentch, L.K., and, Miller, A.L., "Robust Probe for the Quantum Pauli Channel," Proceedings of the Physical and Engineering Sciences Section, 2010 Joint Statistical Meetings, Vancouver, August 3-7, 2010.
Lucas Mentch and Siyu Zhou. (2021+) “Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance.” Under Review. arXiv Researchers.One
Wei Peng, Tim Coleman, and Lucas Mentch. (2021+) “Rates of Convergence for Random Forests via Generalized U-statistics.” Under Review. arXiv
Tim Coleman, Wei Peng, and Lucas Mentch. (2021+) “Scalable and Efficient Hypothesis Testing with Random Forests.” Under Review. arXiv
Wei Peng, Lucas Mentch, and Len Stefanski. (2021+) "Bias, Consistency, and Alternative Perspectives of the Infinitesimal Jackknife." Under Review. arXiv
Lucas Mentch, Nick Kissel. (2021+) “Forward Stability and Model Path Selection.” Under Review. arXiv Researchers.One
Giles Hooker, Lucas Mentch, and Siyu Zhou. (2021) "Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance." Statistics and Computing. Just Accepted. arXiv
Zhengze Zhou, Lucas Mentch, and Giles Hooker. (2021) “V-Statistics and Variance Estimation.” Journal of Machine Learning Research. Just Conditionally Accepted. arXiv
Lucas Mentch and Giles Hooker. (2021) “Bridging Breiman’s Brook: From Algorithmic Modeling to Statistical Learning”. Observational Studies: Commentaries on the 20th anniversary of the publication of Leo Breiman’s “Statistical Modeling: The Two Cultures”. arXiv
Wallace ML, Coleman TS, Mentch LK, Buysse DJ, Graves JL, Hagen EW, Hall MH, Stone KL, Redline S, Peppard PE. (2021) “Physiological Sleep Measures Predict Time to 15-Year Mortality in Community Adults: Application of a Novel Machine Learning Framework.” Journal of Sleep Research. e13386. JoSR
Ashely Griffin, Feng-Chang Lin, Lucas Mentch, and Arlene Chung. (2021) “Precision VISSTA Study: mHealth Physical Activity Patterns and Patient-Reported Outcomes in Patients with Inflammatory Bowel Diseases.” AMIA 2021 Annual Symposium.
Lucas Mentch and Siyu Zhou. (2020) “Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success.” Journal of Machine Learning Research. 21(171), pp. 1-36. JMLR arXiv
Tim Coleman, Kimberly Kaufeld, Mary Frances Dorn, and Lucas Mentch. (2020) “Locally Optimized Random Forests.” STAT. Just Accepted. arXiv
Taehee Jung, Dongyeop Kang, Hua Cheng, Lucas Mentch, and Thomas Schaaf. “Posterior Calibrated Training on Sentence Classification Tasks.” 2020 Annual Conference of the Association for Computational Linguistics. 2020.acl-main.242, 2723–2730. arXiv ACL
Tim Coleman, Lucas Mentch, Daniel Fink, Frank La Sorte, David Winkler, Giles Hooker, and Wesley Hochachka. (2020) "Statistical Inference on Tree Swallow Migration with Random Forests." Journal of the Royal Statistical Society, Series C. 69(4), 973-989. arXiv JRSS-C
Richard McAlexander and Lucas Mentch. (2020) “Predictive Inference with Random Forests: A New Perspective on Classical Analyses.” Research and Politics. 7(1), 2053168020905487. R&P
Lucas Mentch. (2020) “On Racial Disparities in Recent Fatal Police Shootings.” Statistics and Public Policy. 7(1), 9-18. arXiv SPP (#1 SPP Most read article of 2020)
Taehee Jung, Dongyeop Kang, Lucas Mentch, and Eduard Hovy. (2019) “Earlier Isn’t Always Better: Studying Corpus Biases in Summarization.” Empirical Methods in Natural Language Processing (EMNLP) 2019. D19-1327, 3324–3335. arXiv EMNLP
Tim Coleman, Lucas Mentch, Kimberly Glass, David Gotz, Nils Gehlenborg, and Arlene Chung. (2019) “Precision VISSTA: Machine Learning Prediction and Inference for Bring-Your-Own-Device (BYOD) mHealth Data”. AMIA 2019 Annual Symposium. AMIA
Arlene Chung, Kimberly Glass, Jacob Leisey-Bartsch, Lucas Mentch, Nils Gehlenborg, and David Gotz. (2019) “Precision VISSTA: a BYOD mHealth Cohort for Precision Health”. AMIA 2019 Annual Symposium. AMIA
Robin Richter, Carsten Gottschlich, Lucas Mentch, Duy H. Thai, and Stephan Huckemann. (2019) “A Quality Estimator for Fingerprints and its Validation Scheme.” IEEE Transactions on Information Forensics & Security. 14(8), 1963-1974. IEEE
Duy Hoang Thai and Lucas Mentch. (2018) "Multiphase Segmentation for Simultaneously Homogeneous and Textural Images.'' Applied Mathematics and Computation, 335, 146-181. AM&C arXiv
Oliver Lindhiem, Isaac T. Petersen, Lucas Mentch, and Eric A. Youngstrom. (2018) “The Importance of Calibration in Clinical Psychology.” Assessment. 1073191117752055. SAGE
Hooker, G., & Mentch, L. (2018). "Bootstrap bias corrections for ensemble methods." Statistics and Computing, 28(1), 77-86. S&C arXiv
Mentch, L., & Hooker, G. (2017). "Formal Hypothesis Tests for Additive Structure in Random Forests." Journal of Computational and Graphical Statistics, 26(3), 589-597. JCGS arXiv
Mehrmohamadi, M., Mentch, L. K., Clark, A. G., & Locasale, J. W. (2016). Integrative modelling of tumour DNA methylation quantifies the contribution of metabolism. Nature communications, 7, 13666. NatureComm bioRXiv
Giles Hooker and Lucas Mentch, (2016) "Comments on: A Random Forest Guided Tour." TEST, 25(2), pp. 254-260. TEST
Lucas Mentch and Giles Hooker. (2016) "Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests." The Journal of Machine Learning Research. 17(26), pp. 1-41. JMLR arXiv
Bar, Haim, and Lucas Mentch. (2017) "R-CMap—An open-source software for concept mapping." Evaluation and Program Planning 60 (2017): 284-292. EPP PubMed
Frey, M.R., Miller, A.L., Mentch, L.K., and Grahm, J. (2010) "Score Operators of a Qubit with Applications", Quantum Information Processing, 9(5), 629. QIP
Frey, M.R., Coffey, L.E., Mentch, L.K., Miller, A.L., and Rubin, S.S. (2010) "Correlation Identification in Bipartite Pauli Channels", International Journal of Quantum Information, 8(7). IJQI
Frey, M.R., Coffey, L.K., Mentch, L.K., Miller, A.L. and Rubin, S.S. (2010) "Pauli channels exhibit a transition effect in memory estimation above a parametric threshold," Proceedings of SPIE, Quantum Information and Computation VIII, E.J. Donkor, A.R. Pirich, and H.E. Brandt, eds., April 2010.
Book Chapters:
Maria Cuellar, Lucas Mentch, and Cliff Spiegelman. “Association Does not Imply Discrimination: Flawed Analyses that Lead to Misinterpretations and Wrongful Convictions.” Handbook of Forensic Statistics. Chapman & Hall / CRC Handbooks of Modern Statistical Methods. Eds David Banks, Karen Kafadar, and David Kaye.
Short Conference Publications, Technical Reports, & Op-Eds:
Lucas Mentch. “Don’t Throw the Baby out with the Pandemic: A Comment on “Naive Probabilism” by Harry Crane.” Researchers.One. February 23, 2021.
ML Wallace, E Hagan, Tim Coleman, Lucas Mentch, DJ Buysse, MH Hall, S Redline, P Peppard. “Self-report And Polysomnography Sleep and Mortality in Adults: A Machine Learning Replication Analysis.” SLEEP 2020, 34th Annual Meeting of the Associated Professional Sleep Societies, LLC (APSS). Philadelphia, PA, June 17, 2020.
Siyu Zhou and Lucas Mentch. "Explaining the Practical Success of Random Forests." 2020 Symposium on Statistics and Data Science (SDSS). Pittsburgh, PA, June 5, 2020.
Tim Coleman and Lucas Mentch. "Locally Optimized Random Forests, a Solution to Forecasting Severe Hurricane Power Outages." 2020 Symposium on Statistics and Data Science (SDSS). Pittsburgh, PA, June 5, 2020.
Kim Beals, Karen A. Keenan, Nicholas J. Kissel, Lucas Mentch, Wuxin Yang*, Bradley C. Nindl, and Qi Mi. “Prediction of Lower Extremity Musculoskeletal In- juries for Naval Special Warfare Operators: A Machine Learning Approach.” Medicine and Science in Sports and Exercise, Volume 50:5 Supplement. Presented at: World Congress on Exercise is Medicine and World Congress on the Basic Science of Muscle Hypertrophy and Atrophy of the American College of Sports Medicine. Minneapolis, MN, June 1, 2018.
Nicholas J. Kissel and Lucas Mentch. “The Role of HbA1c in Hospital Readmission of Diabetic Patients.” Presented at the ACC Meeting of the Minds Conference. Boston College University, Chestnut Hill, MA, April 6-8, 2018.
Zachary Fulker, Tyler Folta, and Lucas Mentch. “Investigation of Advanced NBA Metrics.” Carnegie Mellon University Sports Analytics Conference. Abstract Accepted. October 28, 2017.
Lucas Mentch, Maria Cuellar, William Thompson, and Cliff Spiegelman. "The Next Page: Four experts explain why forensic analysis of crime scenes is not as reliable as you might think.'' Pittsburgh Post Gazette. March 13, 2016.
William Thompson, Lucas Mentch, Maria Cuellar, and Cliff Spiegelman. "Who should control Houston's crime lab?'' Houston Chronicle. May 31, 2016.
Frey, M.R., Graham, J., Mentch, L.K., and, Miller, A.L., "Robust Probe for the Quantum Pauli Channel," Proceedings of the Physical and Engineering Sciences Section, 2010 Joint Statistical Meetings, Vancouver, August 3-7, 2010.
GRANTS & CONTRACTS
- NIH 2RF1 AG056331-04A1, 2021-2026: "Sleep Health Profiles and Prospective Health Outcomes in Older Adults: Extending Novel Statistical Methods in Multi-cohort Applications", $3,530,678 ($332,415), co-I
- NSF DMS-2015400, 2017-2020: "Black-Box Science: Ideas and Insights for Learning-Based Statistical Inference", $160,000, PI
- NIH R01EB025024, 2017-2020: "QuBBD: Statistical and Visualization Methods for PGHD to Enable Precision Medicine", $917,806 ($149,788), co-I
- NSF DMS-1712041, 2017-2020: “Collaborative Research: Statistical Inference Using Random Forests and Related Methods”, $335,078 ($119,802), PI
- dB-SERC Course Transformation Award, 2017-2018. “An Interdisciplinary Data Science Design for Undergraduate Students.” $10,000. PI
TALKS, WORKSHOPS & PRESENTATIONS
- Michigan State University, Department of Statistics, Invited Seminar (September 2021)
- Plenary Talk, German Statistical Society Annual Meeting (September 2021)
- Joint Statistical Meetings, Introductory Overview Lecture (August 2021)
- Joint Statistical Meetings, Invited Session (August 2021)
- Science Revealed Public Lecture Series, University of Pittsburgh (April 2021)
- AI Seminar, Cornell University, Invited Seminar (March 2021)
- Wright State University, Department of Computer Science, Invited Seminar (October 2020)
- International Indian Statistical Association, Invited Talk (July 2020)
- Symposium on Data Science and Statistics, Invited Talk (June 2020)
- Classification Society Annual Meeting, Bucknell University, Invited Talk (June 2020)
- AMS Eastern Sectional Meeting, Binghamton University, Invited Talk (October 2019)
- Joint Statistical Meetings, Invited Opening Session Poster (August 2019)
- Joint Statistical Meetings, Invited Session (August 2019)
- Workshop on Random Forest Inference, NC State University (March 2019)
- CMStatistics, University of Pisa, Invited Session (December 2018)
- Joint Statistical Meetings, Invited Session (August 2018)
- Department of Mathematics, Indiana University of Pennsylvania (March 2018)
- Department of Biostatistics, University of Pittsburgh (March 2018)
- Banff International Research Station, Workshop co-organizer (January 2018)
- CMStatistics, Invited Session (December 2017)
- Department of Industrial Engineering, University of Pittsburgh (September 2017)
- Joint Statistical Meetings, Invited Session (August 2017)
- West Virginia University, Department of Forensic and Investigative Sciences (February 2017)
- Carnegie Mellon University, Center for Statistics and Application in Forensic Evidence (November 2016)
- University of Pittsburgh Statistics Seminar (September 2016)
- Carnegie Mellon University, Statistics and Machine Learning Research Group (September 2016)
- Joint Statistical Meetings, Topic Contributed Session. (August 2016)
- IMS New Researchers Conference (July 2016)
- SAMSI Undergraduate Workshop. (May 2016)
- SAMSI Transition Workshop. (May 2016)
- SAMSI Postdoc Seminar. (April 2016)
- SAMSI Undergraduate Workshop. (February 2016)
- SAMSI Undergraduate Workshop Tutorial. (February 2016)
- SAMSI Postdoc Seminar. (October 2015)
- NC State, Statistics Seminar. (March 2015)
- ENAR 2015 Spring Meeting, Invited Session. (March 2015)
- University of Pittsburgh, Statistics Seminar. (February 2015)
- Kansas State University, Statistics Seminar. (February 2015)
- U. of Central Florida, Statistics Seminar. (February 2015)
- William & Mary, Statistics Seminar. (January 2015).
- Wake Forest University, Statistics Seminar. (January 2015)
- University of Arkansas, Statistics Seminar. (December 2014)
- University of Michigan, Statistics Seminar. (November 2014)
- Artificial Intelligence Seminar, Cornell University. (September 2014)
- Graduate Student Seminar, Cornell University. (September 2014)
- Lab of Ornithology Seminar, Cornell University. (September 2014)
- Joint Statistical Meetings, Contributed Session. (August 2014)
- Joint Statistical Meetings, Contributed Session. (August 2013)
- Graduate Student Seminar, Cornell University. (April 2013)
- Biostatistics Research Group, Cornell University. (March 2013)
AWARDS, FELLOWSHIPS & RECOGNITION
- Interview/Article with the Pitt Center for Research Computing (CRC). "Opening the Machine Learning Black Box." LINK
- Interview/Article with The University Times. "Teaching Heroes: Mentch Helping Meld Statistics and Data Science." LINK
- Interview/Article with the Pitt Pride. "Mentoring the Future Gatekeepers of Science." LINK
- SAMSI Postdoctoral Fellowship (2015)
- SUNY Graduate Fellowship (2010)
- Phi Beta Kappa, Bucknell U. (2010)
- Pi Mu Epsilon, Bucknell U. (2008)
- William Bucknell Scholarship (2008)
- The President's Award for Distinguished Academic Achievement (2007)
- Alpha Lambda Delta, Bucknell U. (2006)
TEACHING
All courses taught at the University of Pittsburgh unless otherwise noted
*Indicates a course that was newly developed
*Indicates a course that was newly developed
- STAT 1361*: Statistical Learning and Data Science (SP 2018-2022)
- STAT 2360*: Statistical Learning and Data Science (SP 2019-2022)
- HONORS 1510*: Datajam: Using Big Data for Community Good (SP 2019)
- STAT 2270: Data Mining (FA 2019-2021)
- STAT 1291: Topics in Applied Statistics, Statistics and Data Science (SP 2017)
- STAT 1151: Introduction to Probability (FA 2016)
- ST 371: Introduction to Probability & Distribution Theory (SU 2016, NC State)
- ORIE 6700: Statistical Principles (FA 2012, Cornell University, Teaching Assistant)
- BTRY 3520*: Statistical Computing (SP 2012, Cornell University, Teaching Assistant)
- ILRST 2100: Introductory Statistics (FA 2011, Cornell University, Teaching Assistant)