Data Mine Publications

Publications by Data Mine (or STAT-LLC) students,
and/or related to The Data Mine (or STAT-LLC)

Students from The Data Mine and/or STAT-LLC are indicated with one asterisk (*).
Mentors from The Data Mine and/or STAT-LLC are indicated with two asterisks (**).

    Accepted, submitted, or in preparation

  • Brandon Boor, Manjie Fu, and collaborators, The Infant Playpen Effect: Crawling-Induced Dust Resuspension as a Major Source of Particulate Matter in the Infant Breathing Zone, manuscript in preparation.
  • Frederi Viens**, Brian Kidd*, Mikaela Meyer*, Jacques Lemoalle, Otto Doering, Molly Brown, Carolyn Johnston, Nicole Kong, Attribution of factors in Lake Chad's variations: a Bayesian approach, in preparation.
  • H. Hall, P. Medina, J. Rounds, C. Vincent, R. Doerge, and V.M. Weake, Differential susceptibility of genes to transcriptional decline in aging Drosophila sensory neurons, submitted for publication.
  • Kent Gauen* and Xiao Wang**, Machine Learning Introduction With MNIST Dataset, manuscript in preparation.
  • Kent Gauen*, Zohar Kapach, Andrew Ulmer, Damini Rijhwani, Roopasree Naidu, Aparna Pidaparthi, Cailey Farrell*, Karthik Maiya, Meera Haridasa, Yung-Hsiang Lu**, Vinayak Rao, Mark Daniel Ward**, George K. Thiruvathukal, Linking Image Dataset Distinctiveness And Model Accuracy, submitted, 2018.

    2022

  • Jake Roach, Predicting Short-term Cryptocurrency Volatility using Twitter Data, Purdue Undergraduate Research Conference

    2021

  • Ethan Edwards, Interview with Mark Daniel Ward, Journal of Purdue Undergraduate Research, Volume 11, Fall 2021, pages 119-120.
  • Kiril Datchev and Nkhalo Malawo, Semiclassical resonance asymptotics for the delta potential on the half line, posted on arXiv

    2020

  • Garrett Mulcahy, Brady Atwood, Alexey Kuznetsov, Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states, PLOS ONE 15(2): e0228081
  • Joseph Ching, A Fork in the Road: Exploring Undecided Student Success, Journal of Purdue Undergraduate Research, Volume 10, Article 24
  • Maggie Betz, Peter Boyd, Emily Damone, Christina DeSantiago, Kent Gauen, Katie Lothrop, Mikaela Meyer, Kristen Mori, Ashley Peterson, Mark Daniel Ward, Research Experiences in the Statistics Living Learning Community, 12 pages, provisionally accepted pending minor revisions, for forthcoming book on the Future of Undergraduate Research in Math, to be published by the MAA in 2021.
  • Logan Bradley-Trietsch, Estimating Vehicular Traffic Intensity With Deep Learning and Semantic Segmentation, Journal of Purdue Undergraduate Research, volume 10, 2020
  • E. Gundlach and M. D. Ward, The Data Mine: Enabling Data Science Across the Curriculum, Journal of Statistics Education, 15 pages, accepted for publication (2020).
  • M. Betz, E. Gundlach, E. Hillery, J. Rickus, and M. D. Ward, The next wave: We will all be data scientists, Statistical Analysis and Data Mining, Volume TBA (2020), 4 pages.
  • Phillip Atiba Goff, Amelia M. Haviland, Tracey Lloyd, Mikaela Meyer, and Rachel Warren, How racism amplifies Covid-19 risk for everyone, Vox, https://www.vox.com/2020/10/26/21529323/police-covid-19-risk-race-racial-disparities

    2019

  • L. C. Parker and M. D. Ward, Purdue University: Statistics Living Learning Community, Aligning Institutional Support for Student Success: Case Studies of Sophomore-Year Initiatives, National Resource Center for The First-Year Experience & Students in Transition, University of South Carolina, edited by Tracy Skipper, September 2019.
  • Kristen Bellisario, Jack Vanschaik*, Zhao Zhao, Amandine Gasc, Hichem Omrani, Bryan Pijanowski**, Contributions of MIR to Soundscape Ecology. Part 2: Spectral timbral analysis for discriminating soundscape components, Ecological Informatics, volume 51, pages 1-14, 2019.
  • Alison Jeffries, Zeinab Aly, and Molly Cromer, Analysis of Manganese Accumulation in the Pituitary Gland and Hippocampus of Smelters Using High Resolution 3-D T1-Weighted MRI, Journal of Purdue Undergraduate Research, volume 9, in press, 2019.
  • Peter Boyd*, Brian Kidd*, Christopher Vincent*, Reaching the NFL Playoffs Based on Week One Results: A Probability Model with Simulation, Rose-Hulman Undergraduate Mathematics Journal, volume 20, issue 1, article 1, 12 pages (2019).
  • Erin Madden, Brian Kidd*, Owen Levin, Jonathon Peterson, Jacob Smith, Kevin Stangl, Upper and Lower Bounds on the Speed of a One-Dimensional Excited Random Walk, Involve, Vol. 12, No. 1, 97-115 (2019), pdf.
  • Sanjeev Lingam-Nattamai, Examining the Gender Pay Gap at Purdue University, Medium web link.
  • Oscar Sanchez, Agnes Mendonca, Alan Min, Jichang Liu, and Chongli Yuan, Monitoring Histone Methylation (H3K9me3) Changes in Live Cells, ACS Omega, 4, 8, 13250-13259, 2019.

    2018

  • Nan Kong**, Sameer Manchanda*, Mikaela Meyer*, On Comprehensive Mass Spectrometry Data Analysis for Proteome Profiling of Human Blood Samples, Journal of Healthcare Informatics Research, volume 2, pages 305--318, 2018 (web link).
  • Kristen Mori*, A Breakdown of the NFL's Dirtiest Matchups, Medium web link
  • Esteban Fernández-Juricic**, James Brand*, Bradley F. Blackwell, Thomas W. Seamans, and Travis L. DeVault, Species With Greater Aerial Maneuverability Have Higher Frequency of Collisions With Aircraft: A Comparative Study, Frontiers in Ecology and Evolution, volume 6 (2018). Journal link; pdf download; 2108 total views of the journal article link from Frontiers in Ecology and Evolution, as of February 9, 2019.
  • Dylan Martin and Vetria Byrd, Big Data Visualization: HoloLens Brings Meaningful Interaction to Lupus Medical Data, Journal for Purdue Undergraduate Research, volume 8, page 85, 2018.
  • Lauren Washington and Vetria Byrd, Visualizing Lupus Symptom Clusters Using D3, Journal for Purdue Undergraduate Research, volume 8, page 86, 2018.
  • Anup Mohan, Ahmed S. Kaseb, Kent W. Gauen*, Yung-Hsiang Lu**, Amy R. Reibman, Thomas J. Hacker, Determining the Necessary Frame Rate of Video Data for Object Tracking under Accuracy Constraints, IEEE International Conference on Multimedia Information Processing and Retrieval, 2018.
  • Kent Gauen*, Ryan Dailey, Yung-Hsiang Lu**, Eunbyung Park, Wei Liu, Alexander C. Berg, Yiran Chen, Three years of low-power image recognition challenge: Introduction to special session, Design, Automation, and Test in Europe (DATE), 2018.
  • Bret Benesh, Jamylle Carter, Deidra A. Coleman, Douglas G. Crabill, Jack H. Good, Michael A. Smith, Jennifer Travis, and Mark Daniel Ward, Periods in Subtraction Games, Proceedings of the International Conference on the Analysis of Algorithms, 2018
  • Mohamed S. A. Elsayed, Brittany Griggs, and Mark Cushman, Synthesis of Benzo[1,6]naphthyridinones Using the Catellani Reaction, Organic Letters, volume 20, pages 5228--5232 (2018) web link.
  • Luke Francisco, Out of the Box: The Wide World of Well-Being, Journal of Purdue Undergraduate Research, volume 8, pages 87--92, 2018.
  • Samira Pouyanfar, Yudong Tao, Anup Mohan, Haiman Tian, Ahmed S. Kaseb, Kent Gauen, Ryan Dailey, Sarah Aghajanzadeh, Yung-Hsiang Lu, Shu-Ching Chen, Mei-Ling Shyu, Dynamic Sampling in Convolutional Neural Networks for Imbalanced Data Classification, IEEE International Conference on Multimedia Information Processing and Retrieval, 2018.
  • Mikaela Meyer*, Statistics Student Awarded Truman Scholarship, Amstat News.
  • Fulya Gokalp Yavuz and Mark Daniel Ward**, Fostering Undergraduate Data Science, The American Statistician, in press, 2018.

    2017

  • Jack VanSchaik*, Amandine Gasc, Kristen Bellisario, and Bryan Pijanowski**, Spatial analysis of soundscapes of a Paleotropical rainforest, The Journal of the Acoustical Society of America, volume 141, page 3943, 2017.
  • Jack VanSchaik*, Spatial Soundscape Ecology: Application in a Paleotropical Rainforest, Journal of Purdue Undergraduate Research, volume 7, pages 65--71 (2017).
  • Kristen Bellisario, Jack Vanschaik*, Amandine Gasc, Carol Bedoya, Hichem Omrani, and Bryan Pijanowski**, Musicological Indices for Soundscape Ecological Analysis, The Journal of the Acoustical Society of America, volume 141, page 3944, 2017.
  • Bridget Curry, Teresa Kennelly*, Sara King, and Connor D. Rose, Out of the Box: Homegrown in Greater Lafayette, Journal of Purdue Undergraduate Research, volume 7, pages 92--95 (2017).
  • Mark Daniel Ward**, Building Bridges: The Role of an Undergraduate Mentor, The American Statistician, volume 71, pages 30--33 (2017); pdf download.
  • Donna LaLonde and Mark Daniel Ward**, Active Learning Focus of CBMS Joint Statement, Amstat News, issue 477, 26, Mar. 2017, pdf download, or online version.
  • Karan Samel*, Xiao Wang**, and Qiang Liu, Predicting Advertisement Clicks using Deep Networks, Journal of Purdue Undergraduate Research, volume 7, pages 50--56 (2017).
  • Abigael Johnson*, The Effects of an Empirically-Based Wise Intervention on Attitudes Toward Diversity; this was Abigael's Honors Thesis.
  • Abigael Johnson* and Dana Tomeh, The Bystander Effect: Societal and Academic Implications of a Neglected Sexuality, Journal of Purdue Undergraduate Research, volume 7, pages 73--74 (2017).
  • Bo Fu, Anup Mohan, Yifan Li, Sanghyun Cho, Kent Gauen*, and Yung-Hsiang Lu, Parallel Video Processing using Embedded Computer, IEEE Global Conference on Signal and Information Processing 2017
  • Kent Gauen*, Ryan Dailey, John Laiman, Yuxiang Zi, Nirmal Asokan, Yung-Hsiang Lu, George K. Thiruvathukal, Mei-Ling Shyu, and Shu-Ching Chen, Comparison of Visual Datasets for Machine Learning, Proceedings of IEEE Conference on Information Reuse and Integration 2017
  • Kent Gauen, Rohit Rangan, Anup Mohan, Yung-Hsiang Lu, Wei Liu, Alexander C Berg, Low-Power Image Recognition Challenge, Asia and South Pacific Design Automation Conference 2017
  • Anup Mohan, Kent Gauen, Yung-Hsiang Lu, Wei Wayne Li, Xuemin Chen, Internet of Video Things in 2030: a World with Many Cameras, IEEE International Symposium of Circuits and Systems 2017
  • Mikaela Meyer*, Creating a Scorecard for a Data Integration Product. Internal report written and submitted during Nielsen internship, 2017.
  • Rich Gorbett*, Viewing client Loan IQ bills in CLP. Internal report written and submitted to JP Morgan Chase and Co., 2017.
  • Stevie Norcross, Keelan Trull, Jordan Snaider, Sara Doan, Kiet Tat*, Libai Huang, and Mathew Tantama, Constructing Red-Shifted Fluorescent Protein Sensors of Cellular Redox Status, FASEB Journal, volume 31, April 2017, supplement 1.
  • Hana Hall, Patrick Medina, Daphne A. Cooper, Spencer E. Escobedo, Jeremiah Rounds, Kaelan J. Brennan, Christopher Vincent*, Pedro Miura, Rebecca Doerge**, and Vikki M. Weake, Transcriptome profiling of aging Drosophila photoreceptors reveals gene expression trends that correlate with visual senescence, BMC Genomics, 18:894, 18 pages, 2017.

    2016

  • Ashley Peterson* and Emily Martin* (faculty sponsor: Mark Daniel Ward**), Filling in the Gaps: Using Multiple Imputation to Improve Statistical Accuracy, Rose-Hulman Undergraduate Mathematics Journal, volume 17, issue 2, article 11, 25 pages (2016). pdf download.
  • Weston Phillips*, Peter Boyd* (faculty sponsor: Michael Baldwin**), Predicting Surface Temperatures of Roads: Utilizing a Decaying Average in Forecasting, Journal of Purdue Undergraduate Research, volume 6, pages 9--15 (2016); pdf download.
  • Peter Boyd*, A Longer Survey is Not Necessarily a Better Survey: A Time Series Analysis. Internal report written and submitted during Procter and Gamble internship, 2016.
  • Peter Boyd*, Cluster Analysis: A New Perspective on Product Ratings. Internal report written and submitted during Procter and Gamble internship, 2016.
  • Peter Boyd*, Introduction to RStudio: Statistical Analysis Methods. Internal report written and submitted during Procter and Gamble internship, 2016.
  • David Banks and Mark Daniel Ward**, Advice for Those Applying to Graduate School, Amstat News, issue 464, 31-33, Feb. 2016, pdf download.
  • K. Das, M. Jackson, S. Keller, D. LaLonde, S. Shipp, J. Utts, and M. D. Ward**, ASA Receives Grant to Establish Series of REUs, Amstat News, issue 466, 20-21, Apr. 2016, pdf download.
  • Mark Daniel Ward**, Peer-to-Peer Mentoring: How It Fits into the Statistics Living Learning Community at Purdue, Amstat News, issue 471, 28-31, Sep. 2016, pdf download, or online version.
  • Patrick Gallagher*, Bruce A. Craig**, Tim Luttermoser, and Grzegorz Buczkowski, Paired Competition Analysis using Mixed Models, Proceedings of the 2016 Conference on Applied Statistics in Agriculture, 65-73, 2016.

    2015

  • Manjie Fu*, Lingsong Zhang**, Azza Ahmed, Karen Plaut, David M. Haas, Kinga Szucs, and Theresa M. Casey, Does circadian disruption play a role in the metabolic-hormonal link to delayed lactogenesis II? Frontiers in Nutrition, volume 2, number 4 (2015). Journal link; pdf download; 6354 total views of the journal article link from Frontiers in Nutrition, as of February 9, 2019.
  • Mark Daniel Ward**, Learning communities and the undergraduate statistics curriculum (a response to "Mere renovation is too little too late" by George Cobb), The American Statistician, volume 69, posted as online article, in a supplement to issue 4 (2015); pdf download.
  • J. Hardin, R. Hoerl, N. J. Horton, and D. Nolan, with B. Baumer, O. Hall-Holt, P. Murrell, R. Peng, P. Roback, D. Temple Lang, and M. D. Ward**, Data Science in the Statistics Curricula: Preparing Students to "Think with Data," The American Statistician, volume 69, pages 343--353 (2015); pdf download.
  • Mark Daniel Ward** and Ellen Gundlach, Introduction to Probability (Freeman, 2015), book homepage.
  • Peter Boyd*, Analyzing the effect of traffic on wildlife viewings in Denali National Park: a regression analysis. Report submitted to Denali National Park. Report was also Peter Boyd's Honors Thesis.
  • Frederi Viens**, Brian Kidd*, Mikaela Meyer*, Jacques Lemoalle, Otto Doering, Molly Brown, Carolyn Johnston, Nicole Kong, Africa's Great Oasis: The Changing Environments of Lake Chad, preliminary report contained in the 2015 Annual Report for the Purdue Climate Change Research Center, pages 14-15, LakeChad.pdf.

Conference presentations by Data Mine (or STAT-LLC) students,
and/or posters arising from The Data Mine (or STAT-LLC)

Students from The Data Mine and/or STAT-LLC are indicated with one asterisk (*).
Mentors from The Data Mine and/or STAT-LLC are indicated with two asterisks (**).

    2020

  • Joseph Ching presented his research in the Institutional Data Assessment project at the Virtual Summer Research Symposium on July 31, 2020
  • Logan Bradley-Trietsch, Estimating Traffic Intensity with Semantic Segmentation, Pacific Northwest National Lab Virtual Research Symposium and also at the PNNL Data Science & Analytics Brown Bag, summer 2020

    2019

  • E. Hillery, M. D. Ward, J. Rickus, A. Younts, P. Smith, and E. Adams, Undergraduate Data Science and Diversity at Purdue University, PEARC '19: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines, July 2019, Article No. 88.
  • Logan Bradley-Trietsch, Estimating Traffic Intensity with Semantic Segmentation, Rose Hulman Undergraduate Mathematics Conference, April 2019
  • Jessica Gilbert, Diversity of forest structure across the United States, Rose Hulman Undergraduate Mathematics Conference, April 2019
  • Luke Francisco, Impact of the Economic Recession on Measures of Health, Rose Hulman Undergraduate Mathematics Conference, April 2019
  • Kali Lacy, presentation as a member of Computing4Change (C4C) team at the SuperComputing conference (SC18) in Dallas, Texas, November 2018
  • Kali Lacy, A computational approach to the structure of subtraction games, Rose Hulman Undergraduate Mathematics Conference, April 2019
  • Kevin LaMaster, Generating interest in Generating Functions (And more word play), Rose Hulman Undergraduate Mathematics Conference, April 2019
  • Garrett Mulcahy, Big Bad Matrices: A Constructive Approach, Rose Hulman Undergraduate Mathematics Conference, April 2019
  • Brent Ladd and Mark Daniel Ward, Training Students Concurrently in Data Science and Team Science: Results and Lessons Learned from Multi-Institutional Interdisciplinary Student-Led Research Teams 2012-2018, Joint Statistical Meetings, July 2019
  • Jordan-Taylor Harris and Azza Ahmed, Using Interactive Web-Based Monitoring to Increase Breastfeeding, Joint Statistical Meetings, July 2019
  • Garrett Mulcahy and Thomas Sinclair, Big, Bad Matrices: a Constructive Approach, Joint Statistical Meetings, July 2019
  • Logan Bradley-Trietsch and Xiao Wang, Predicting Traffic Intensity with Deep Learning and Semantic Segmentation, Joint Statistical Meetings, July 2019
  • Bret Benesh, Jamylle Carter, Deidra Coleman, Douglas Crabill, Jack Good, Kali Lacy, Michael Smith, Jennifer Travis, and Mark Daniel Ward, A Computational Approach to the Structure of Subtraction Games, Spring Central and Western Joint Sectional Meeting of the American Mathematical Society (in Honolulu, Hawaii), March 2019
  • Kali Lacy, Bret Benesh, Jamylle Carter, Deidra Coleman, Douglas Crabill, Jack Good, Michael Smith, Jennifer Travis, and Mark Daniel Ward, A Computational Approach to the Structure of Subtraction Games, Joint Statistical Meetings, July 2019
  • J. Gilbert, S. Fei, J. Knott, E. LaRue, and K. Potter, Diversity of Forest Structure Across the United States, Joint Statistical Meetings, July 2019
  • Haydn Schroader, Alejandro Strachan, Saaketh Desai, Juan Carlos Verduzco Gastelum, David Farache, Combining Materials and Data Science, Joint Statistical Meetings, July 2019
  • Samantha Smock, Alex Cohen, and Patrick Zollner, Modeling How Beach Characteristics, Predation, and Bird's Tolerance of Humans Affect Piping Plovers (Charadrius Melodus), Joint Statistical Meetings, July 2019
  • Jayla Langford, The Value of Mentors for Young Adults, Joint Statistical Meetings, July 2019
  • Alison Jeffries, Molly Cromer, Zeinab Aly, Ulrike Dydak, and Eric Cameron, Analysis of Manganese Accumulation in the Pituitary Gland, Olfactory Bulb, and Hippocampus of Smelter Workers Using High Resolution 3D T1-Weighted MRI, Joint Statistical Meetings, July 2019
  • Jun Kim and Anindya Bhadra, Optimization of Backpropagation Multilayer Neural Network, Joint Statistical Meetings, July 2019
  • Hayley Jordan and Jianxi Su, Two-Stage Predictive Models for Assessing Misrepresentation Risk on Self-Reported Tobacco Status in Health Insurance Ratemaking, Joint Statistical Meetings, July 2019
  • Jason Selbo and Jianxi Su, Time-Varying Copulas with Full-Range Dependence for Modeling Financial Data, Joint Statistical Meetings, July 2019
  • Menna Hassan and Yung Hsiang Lu, Dataset Bias in Machine Learning, Joint Statistical Meetings, July 2019
  • Katherine Brinkers, Water Fluoridation, Joint Statistical Meetings, July 2019
  • Kevin LaMaster and Mark Ward, Asymptotic Analysis of Wilf Partitions Using Generating Functions, Joint Statistical Meetings, July 2019
  • I'Yanna Scott, Patrick Zollner, Nerisa Taua, Cheyenne Gerdes, and Laura D'Acunto, Evaluating the Contribution Acoustic Monitors Have in Predicting Bat Mist Netting Success, Joint Statistical Meetings, July 2019
  • Z. Aly, M. Cromer, A. Jeffries, E. Cameron, U. Dydak, Analysis of Manganese Accumulation in the Pituitary Gland, Olfactory Bulb, and Hippocampus of Smelter Workers Using High Resolution 3D T1-Weighted MRI. 15th IUTOX International Congress of Toxicology (ICTXV), Honolulu, Hawaii, USA, July 15-18, 2019

    2018

  • Kristen M. Bellisario, Laura Jessup, John B. Dunning, Jack VanSchaik, Laura D'Acunto, Benjamin Gottesman, Cristian Graupe, and Bryan C. Pijanowski, A rapid assessment monitoring framework to characterize a loud sound event stressor on a vocalizing bird community in a US Midwestern prairie, presented at the International Eco-Acoustics Congress in Brisbane, Australia, in June/July 2018.
  • Amber Young*, Comparison of Statistical Procedures to Identify Technicians with Terminal Digit Preference in Blood Pressure Measurements, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 20, 2018, one of three overall conference prizes.
  • Jack VanSchaik*, A Real Variable Equivalence of the Riemann Zeta Hypothesis Using Step Functions, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 20, 2018.
  • Dylan Martin* and Vetria Byrd**, Big Data Visualization: HoloLens Transforms Users to Data Scientists, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2018.
  • Cailey Farrell*, Meera Haridasa*, Using Time and Location to Analyze the Effectivity of Machine Learning Algorithms, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2018, one of three overall conference prizes.
  • Namaluba Malawo*, Using Boosted Regression Trees to Predict Invasive Species Richness, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2018, one of three overall conference prizes.
  • Simon Langowski*, On the Computation of Wilf Partitions, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2018, one of two overall conference honorable mentions.
  • Chris Bryan*, Cell Data Mining and Phenotypic Classification Using Image Analysis of Epigenetic Modifications, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2018.
  • A. Bhalgat, R. Ali, M. Wendt, The impact of differential ligand engagement on downstream signaling of epidermal growth factor receptor, Purdue's Undergraduate Research Symposium, 2018
  • Avni Bhalgat, Arindam Bose, Huang Ling, Senthil Muthuswamy, Overcoming Chemotherapeutic Resistance in Pancreatic Cancer, poster at The Leadership Alliance National Symposium, 2018
  • Amber Young and George McCabe, Comparison of Statistical Procedures to Identify Technicians with Terminal Digit Preference in Blood Pressure Measurements, Purdue Undergraduate Research Conference, 2018.
  • Aaron Hoffman, Mikaela Meyer, Prateek Malik, Pablo Balcazar, Erin Hennes, Dwaine Jengelley, and Stefanie Walsh, How anxiety about Donald Drumpf influences news reporting, Presented at Midwest Political Science Association Annual Conference in Chicago, IL, April 5, 2018
  • Mikaela Meyer and David Johnson, Variability Analysis of Historic Flood Depth Returns in Coastal Louisiana, Presented at the Purdue Undergraduate Research Symposium, April 10, 2018.
  • Jackson Ball, Mikaela Meyer, Baylee Bunce, and David Johnson, Parametric Sensitivity Analysis of a Coastal Louisiana Flood Risk Model, Presented at the Purdue Undergraduate Research Symposium, April 10, 2018.
  • Luke Francisco, Lei Nie, Ryan Murphy, and Elliot Friedman, Impact of the Economic Recession on Measures of Health, Purdue Undergraduate Research Conference, 2018.
  • Elizabeth Bell, Dennis Buckmaster, Tyler Netherly, and Madison Trout, Impact of Rainfall on Crop Yield, Purdue Undergraduate Research Conference, 2018
  • Elizabeth Bell, Dennis Buckmaster, Tyler Netherly, and Madison Trout, Macroscopic Crop Yield Prediction Using Public Data, Purdue Statistics Symposium, 2018
  • Elizabeth Bell, Dennis Buckmaster, Tyler Netherly, and Madison Trout, Unearthing Correlations Between Crop Yields and Uncontrollable Factors, Joint Statistical Meetings, 2018
  • Mark Daniel Ward, Data Scraping, Parsing, Wrangling, and Cleaning, Joint Statistical Meetings, 2018
  • Mark Daniel Ward (Invited Panel), Are We (Academia) Producing Leaders with Necessary Statistical Skills?, Joint Statistical Meetings, 2018
  • Simon Langowski and Mark Daniel Ward, First Order Asymptotic Variance of a Leader Election Algorithm, Joint Statistical Meetings, 2018
  • Michael Smith, A Data-Driven Approach to Combinatorial Game Theory, AISC--2018 International Conference on Advances in Interdisciplinary Statistics and Combinatorics, 2018.
  • Amber Young, Sat Gupta, and Ryan Parks, A binary unrelated-question RRT model accounting for untruthful responding, Involve: A Journal of Mathematics, Volume 12, Number 7 (2019), 1163-1173.
  • Amber Young, Newer Variations of the Unrelated Question Binary RRT Model Examining the Impact of Untruthful Responding, AISC--2018 International Conference on Advances in Interdisciplinary Statistics and Combinatorics, 2018.
  • Stacey Miertschin and Amber Young, A Data-driven Approach to Predicting Diabetes and Cardiovascular Disease with Machine Learning, AISC--2018 International Conference on Advances in Interdisciplinary Statistics and Combinatorics, 2018.
  • Bret Benesh, Jamylle Carter, Deidra Coleman, Doug Crabill, Jack Good*, Michael Smith*, Jennifer Travis, and Mark Daniel Ward**, A Computational, Data-Driven Approach to Game Theory, presented at the Joint Statistical Meetings, 2018.
  • Hannah Bredikhin and Jun Xie, Secondary Data Analysis to Predict Therapeutic Outcome of Colorectal Cancer Patients, Joint Statistical Meetings, 2018
  • Namaluba Malawo, Gabriela Nunez, and Songlin Fei, Predicting Invasive Species Richness with Boosted Regression Trees, Joint Statistical Meetings, 2018
  • Hope Cullers and Mike Baldwin, Using Error Statistics to Improve Forecasts, Joint Statistical Meetings, 2018
  • Dylan Martin and Vetria Byrd, Big Data Visualization: User to Data Scientist, Joint Statistical Meetings, 2018
  • Timothy J. Park, Improving Object Detection with Image Preprocessing, Joint Statistical Meetings, 2018
  • Meera Haridasa and Cailey Farrell, Analyzing Bias in Object Detection Data Sets, Joint Statistical Meetings, 2018
  • Rafael Lovas and Tom Leinart, Full-Range Tail Dependence Copulas with Applications in Insurance, Joint Statistical Meetings, 2018
  • Lauren Taylor Washington and Vetria Byrd, Visualizing Lupus Symptom Clusters, Joint Statistical Meetings, 2018
  • Luke Francisco, Elliot Friedman, Ryan Murphy, and Lei Nie, Analyzing the Effect of the Great Recession (2007-2009) on Changes in Health, Joint Statistical Meetings, 2018
  • Chris Bryan, Single Cell Data Mining of Live Cell Epigenetic Modifications, Joint Statistical Meetings, 2018
  • James Marshall Reber, Markov Chains, Mixing Times, and Couplings, AISC--2018 International Conference on Advances in Interdisciplinary Statistics and Combinatorics, 2018.
  • James Marshall Reber, Mixing Times of Random Walks on Various Combinatorial Objects, Research Experience for Undergraduates Program Research Reports (from REU program at IU Bloomington), 2018
  • Dylan Martin and Vetria Byrd, Big Data Visualization: HoloLens Transforms Users to Data Scientists, Purdue University Undergraduate Research Symposium, April 2018
  • Dylan Martin and Vetria Byrd, Big Data Visualization: User to Data Scientist, Broadening Participation in Visualization (BPViz), June 2018

    2017

  • Oscar Sanchez, Chongli Yuan, and Alan Min, Assessing Novel H3K9me3 Probe Using Machine Learning, poster at AIChE International Conference on Epigenetics and Bioengineering, 2017, presented on December 13, 2017
  • Alan Min, Oscar Sanchez, and Chongli Yuan, Tracking Epigenetic Changes in Single Cells, poster at AIChE International Conference on Epigenetics and Bioengineering, 2017, presented on December 14, 2017
  • Oscar Sanchez, Alan Min, and Chongli Yuan, Assessing the Effects of Environmental Chemicals on Epigenetic Regulation Via Machine Learning, poster at AIChE International Conference on Epigenetics and Bioengineering, 2017, presented on December 13, 2017
  • Weake, V.M. et al. (includes Christopher Vincent* and Rebecca Doerge**) Age-related transcription changes in photoreceptor neurons are light-dependent. Genetics Society of America, Drosophila Meeting, San Diego, March 28-April 2, 2017.
  • Sameer Manchanda*, Mikaela Meyer*, Qianqian Li, Nan Kong**, Kai Liang and Yan Li, On Comprehensive Mass Spectrometry Data Analysis for Proteome Profiling of Human Blood Samples, presented at Data Mining for Medicine and Healthcare with SIAM Data Mining 2017 (SDM 2017), on April 29, 2017.
  • Weake, V.M. et al. (includes Christopher Vincent* and Rebecca Doerge**) Age-related transcription changes in photoreceptor neurons are light-dependent. ARVO, Baltimore, MD, May 8-11, 2017.
  • Weake, V.M. et al. (includes Christopher Vincent* and Rebecca Doerge**) Differential susceptibility of genes to transcriptional decline in aging Drosophila sensory neurons. Gordon Conference on Aging. Les Diablerets, Switzerland, July 9-14, 2017.
  • Graciany Lebron Rodriguez*, Vetria Byrd**, and Mark Daniel Ward**, Exploring Theoretical Foundations of the Underpinnings of Big Data Analytics for Visualizing Heterogeneous Systemic Lupus Erythematosus (SLE) Data, presented at Purdue University's Summer Research Opportunities Program (SROP), on July 26, 2017.
  • Bret Benesh, Jamylle Carter, Deidra Coleman, Jack Good*, Michael Smith*, Jennifer Travis, and Mark Daniel Ward**, Periodicity in Game Theory, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Maggie Christy*, David Ross**, Pazit Sankey**, Susan Scott**, Sarah Wang**, and Mark Daniel Ward**, Quality Control of Blood Sample Analysis for Transplant Patients, presented at the Joint Statistical Meetings, on July 31, 2017. Preliminary version also presented at the Midwest Women in Math Symposium on February 25, 2017 at IUPUI.
  • Brian French*, Nicole Markley*, Laszlo Csonka**, and Mark Daniel Ward**, Rates of DNA Mutation in Genes and Inte-Gene Regions, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Elle Tigner* and Jennifer Neville**, An Analysis of Network Discussion Trends in Twitter Using Hashtag Clusters, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Kent Gauen*, Yuxiang Zi, John Laiman, Nirmal Asokan and Yung-Hsiang Lu**, CAM2 Network Camera Object Detection Dataset and Analysis, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Brittany Griggs*, Swetha Ramadesikan, and Ruben Claudio Aguilar**, Changes in Cell Structure and Spreading from Lowe Syndrome, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Emma Beck*, Zoe Danielle Phillips*, and Bryan Pijanowski**, Soundscape Ecology and Daily Trends of Acoustic Indices, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Mark Daniel Ward** and Fulya Gokalp Yavuz, Fostering Undergraduate Data Science, presented at the Joint Statistical Meetings, on July 31, 2017.
  • Alan Min* and Doraiswami Ramkrishna**, Diffusion Dependent Methylation Mechanics, presented at the Joint Statistical Meetings, on August 1, 2017.
  • Manjie Fu*, Crawling-Induced Dust Resuspension as a Major Source of Particulate Matter in the Infant Breathing Zone, Undergraduate Research and Poster Symposium, April 11, 2017. (Best Poster Abstract Award in the Physical Sciences)
  • Abigael Johnson*, Alemán and Cervantes: Story Versus Argument, Undergraduate Research and Poster Symposium, April 11, 2017.
  • Abigael Johnson* and M. J. Monteith, The Effects of an Empirically-Based Wise Intervention on Attitudes Toward Diversity. Poster presented at the Purdue University 2017 Psychological Sciences Departmental Poster Session. Poster also displayed at Purdue University Honors College Medallion Ceremony, May 10, 2017.
  • Kristen Bellisario, Jack Vanschaik*, Zhao Zhao, Hichem Omrani, Amandine Gasc, Bryan Pijanowski**, Musicological Indices for Soundscape Ecological Analysis, Poster Presented at Acoustical Society of America Conference, June 2017.
  • Jack VanSchaik*, Kristen Bellisario, Amandine Gasc, and Bryan Pijanowski**, Spatial Soundscape Ecology: Application in a Paleotropical Rainforest, Research talk given at GSSN Conference, July 2016. Poster presented at Acoustical Society of America Conference, June 2017.
  • Jack VanSchaik* and Steve Bell, A Real Variable Equivlance of the Riemann Hypothesis Using Step Functions, Presentation for Purdue University's College of Science Alumni Board, 2017
  • Alan Min*, Yuzheng Hu, Thomas Ross, Elliot A. Stein, Betty Jo Salmeron, Human Subtypes Based on Static and Dynamic rsfMRI Data, poster presented at the NIH, summer 2017.
  • James Marshall Reber, Methods for Improving the Lower Bound of R(5,5), presented at MathFest 2017.
  • Bret Benesh, Jamylle Carter, Deidra Coleman, Jack Good*, Michael Smith*, Jennifer Travis, and Mark Daniel Ward**, Periodicity in Game Theory, presented at MathFest 2017.
  • Miranda Champion*, Applying Big Data Analysis to Particle Physics, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2017.
  • Brittany Griggs*, Changes in Cell Structure and Spreading from Lowe Syndrome, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2017.
  • Peyton Puckett*, Automating the Effective Fragment Potential Method, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 21, 2017.
  • Michael Smith* and Jack Good*, Periodicity of Subtraction Games, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 22, 2017, First Place (overall conference prize).
  • Amber Young*, Donglai Chen, and Jun Xie**, Reanalysis of Cancer Immunotherapy Clinical Data to Elucidate Genetic information of Immunotherapy Response, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 22, 2017, Second Place (overall conference prize).
  • Elizabeth Bell, Dennis Buckmaster, Tyler Netherly, and Madison Trout, Crop Yields Throughout the Decades, Chicago OATS Kickoff meeting (November 17, 2017).

    2016

  • Peter Boyd*, Brian Kidd*, Christopher Vincent*, Weston Phillips*, How Important Is Week One of the NFL Season? A Probability Model and Simulation, Undergraduate Research and Poster Symposium, April 12, 2016.
  • Felix Francisco-Sanchez*, McKeith Pearson II, Michael Young, Walid Sharabati, and R. Claudio Aguilar**, Classifying Yeast Cell Phenotypes Using Cell Morphology, Student Poster Session in Discovery Park at Purdue University, April 21, 2016.
  • Patrick Gallagher*, Bruce A Craig**, Tim Luttermoser, and Grzegorz Buczkowski, Paired Competition Analysis using Mixed Models, Undergraduate Research and Poster Symposium at Purdue University, April 12, 2016.
  • Patrick Gallagher*, Bruce A Craig**, Tim Luttermoser, and Grzegorz Buczkowski, Paired Competition Analysis using Mixed Models, Conference on Applied Statistics in Agriculture at Kansas State University, May 3, 2016.
  • Karly Rushmore, Aaron Brehm*, Laura E. D'Acunto, and Patrick Zollner**, Investigating the Impact of Local Versus Landscape-Level Variables on Bat Species Occupancy in Indiana, 8th Annual Midwest Bat Working Group meetings at The Ohio State University, April 21, 2016.
  • Kristen Mori* and Jack VanSchaik*, Statistical Soundscape Ecology: Entropy and Phase Transition Analysis of Big Sound Data, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 22, 2016.
  • Kent Gauen*, An Overview of Machine Learning using MNIST Dataset, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 23, 2016.
  • Alan Min*, Population Balance Model for DNA Methylation, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 23, 2016.
  • Karan Samel*, Predicting Advertisement Clicks Using Deep Learning, presented at the Rose Hulman Undergraduate Mathematics Conference, on April 23, 2016.
  • Sameer Manchanda*, Mikaela Meyer*, and Nan Kong**, On Comprehensive Mass Spectrometry Data Analysis for Proteomic Profiling of Biological Samples, presented at the Symposium on Big Data, Human Health and Statistics, at the University of Michigan, on July 21, 2016.
  • Kent Gauen*, Fundamental Supervised Machine Learning Models, presented at the Symposium on Big Data, Human Health and Statistics, at the University of Michigan, on July 21, 2016.
  • Erin Madden, Brian Kidd*, Owen Levin, Jonathon Peterson, Jacob Smith, Kevin Stangl, Upper and Lower Bounds on the Speed of a One Dimensional Excited Random Walk, presented at the Indiana Undergraduate Math Research Conference, on July 25, 2016.
  • Sameer Manchanda*, Mikaela Meyer*, Nan Kong**, Qianqian Li, Yan Li, On Comprehensive Mass Spectrometry Data Analysis for Quality Assessment of Biological Samples (Mass Spectrometry Data Analysis for Mass-to-Charge Signature Identification: Applications in Biosample Quality Control), 1 of 7 finalists for the 2016 INFORMS Undergraduate O.R. (Operations Research) Prize Competition, November 13, 2016.
  • Manjie Fu* and Brandon E. Boor, Infant Exposure to Resuspended Particles from Carpeted Flooring: Experimental Chamber Study with a Simplified Mechanical Crawling Infant, presented at Purdue University's Summer Undergraduate Research Fellowship (SURF) Symposium, on August 4, 2016.
  • Elizabeth Coppola, Sharon Christ**, and Abigael Johnson*, The Lasting Mental Health Burden of Experiencing Parental Psychological Neglect in Adolescence. Paper presented at the Add Health User's Conference, Bethesda, MD, in June 2016. Journal version in preparation.
  • Kent Gauen* and Xiao Wang**, Fundamental Unsupervised Machine Learning Models, presented at Undergraduate Mathematics Symposium, at University of Illinois at Chicago, on October 15, 2016
  • Kent Gauen* and Xiao Wang**, Fundamental Unsupervised Machine Learning Models, presented at the Undergraduate Statistical Conference, at Howard University, on September 24, 2016

    2015

  • Felix Francisco-Sanchez*, McKeith Pearson, Michael Young, Walid Sharabati, and R. Claudio Aguilar**, Quantitative Analysis of Yeast Cell Morphology Defects Induced by Gene De-Regulation, hosted on YouTube and presented at the Virtual Brown Bag Research Discussion Series, Center for Science of Information, March 31, 2016.
  • Abigail Vorhies* and Bailey O'Malley*, Linking Mesodinium Bloom Timing with River Flow Discharge and Estuarine Classification in the Columbia River Estuary, presented in summer 2015 at the NSF Center for Coastal Margin Observation and Prediction, in Portland, Oregon.
This material is based upon work supported by the National Science Foundation under Grant No. 1246818. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.