Research Workshop Grants Program
- Online Workshop: Scientific Machine Learning, October 2020
- Online Workshop: Artificial Intelligence Applications to Agriculture, July 2020
- Workshop on Astronomical Data Science, February 2020
- PhD Research Workshop on Computational / Artificial Intelligence, September 2019
- Workshop on FPGAs in the Era of AI and Big Data, September 2019
- Workshop on Data Science/AI/ML in Education, April 2019
- Workshop on Operational Data Science, February 2019
Instructional Workshop and Tutorial Program
- Bring Your Own Data Workshops, multiple events, ongoing
- NVIDIA Deep Learning Institute for Computer Vision, multiple events, ongoing
- Data Science Webinars, multiple events, ongoing
- Tutorial on Iterating Between the Data World and the Real World to Find Answers in Big Data, October 2020
- Tutorial on Functional and Shape Data Analysis, September 2020
- Tutorial on Conformal Prediction, September 2020
- Tutorial Workshop on Gaussian Processes and Bayesian Optimization, September 2020
- Tutorial Workshop on Introduction to Deep Learning, June 2020
- Tutorial Workshop on Business Analytics – Strategic Issues and Solutions, May 2020
- Tutorial Workshop on Reinforcement Learning – Algorithms and Applications, April 2020
- Tutorial Workshop on Interpretable Machine Learning – Concepts and Techniques, February 2020
- Data Science Bootcamp, August 2019
Education Support Programs
- Ulisses Braga-Neto (Lead),Department of Electrical and Computer Engineering; Scientific Machine Learning.
- Fernando A. Luco Echeverría (Lead), Department of Economics; Data Science for Future Decision-Makers.
- Simon Foucart (Lead), Department of Mathematics; Topics in Mathematical Data Science.
- Ann McNamara (Lead), Department of Visualization; Derya Akleman, Department of Statistics; John Keyser, Department of Computer Science & Engineering; Data Visualization and Analytics.
- Vincent VanBuren (Lead), Department of Medical Education; Machine Learning with Python for Medical Applications.
- Xinyue Ye (Lead), Department of Landscape Architecture & Urban Planning; Urban Data Science.
- Shuang Zhang (Lead) & Darren W. Henrichs, Department of Oceanography; Applied Data Science in Geosciences.
Research Support Programs
- Raymundo Arroyave (PI), Department of Materials Science & Engineering, Development of a Software Platform For Accelerated Microstructure Design: From Data Generation to Curation and Analysis.
- Amir Behzadan (PI), Department of Construction Science, Theodora Chaspari (Co-PI),Department of Computer Science and Engineering, Preeti Zanwar (Collaborator): Department of Epidemiology & Biostatistics, CoFABS-Q: A dataset of face, body and speech cues in web-mined COVID-19 conversational vlogs.
- James Cai (PI), Department of Veterinary Integrative Biosciences, Enabling Single-Cell Data Resource to TAMU Investigators in Interdisciplinary Research.
- Xia Ben Hu(PI), Department of Computer Science and Engineering, AutoAD: Exploiting Automated Machine Learning for Anomaly Detection.
- Zhe Zhang (PI), Department of Geography, A Spatial Decision Support System for Cardiovascular Disease Risk Assessment in Response to the COVID-19 Crisis.
- Lei Zou (PI), Department of Geography, Jian Tao (Co-PI), Texas A&M Engineering Experiment Station, Ali Mostafavi (Co-PI), Departmental of Civil and Environmental Engineering, Tracking Social and Governmental Responses to Covid-19 Using Geospatial Big Data.
- Youngjib Ham (PI), Department of Construction Science, Theodora Chaspari (Co-PI), Computer Science & Engineering, Boosting Workplace Productivity; Data-driven Framework for Enhancing Occupant Environmental Comfort.
- Matthias Katzfuss (PI), Department of Statistics, Sparse Approximation of Dense Kernel Matrices for Scalable Data Science.
- Hye-Chung Kum (PI), Health Policy & Management, School of Public Health, Mark Fossett (Co-PI), Department of Sociology, Alva Ferdinand (Co-PI), Health Policy & Management, School of Public Health, Population Informatics: Data Science using Big Data about People in Social, Behavior, Economic,and Health Sciences.
- Yang Ni (PI), Department of Statistics, Irina Gaynanova (Co-PI), Department of Statistics, Robert Chapkin (Co-PI), Department of Nutrition & Food Science, Raymond Carroll (Co-PI), Department of Statistics, Studying Microbial Interactions and Host Heterogeneity via Data Integration.
- Shahin Shahrampour (PI), Industrial & Systems Engineering, Shallow Networks in Over-Parametrized Regimes: Rethinking Bias-Variance Tradeoff.
- Xiaoning Qian (PI), Electrical and Computer Engineering, Raymundo Arroyave (Co-PI), Materials Science & Engineering, Physics-Constrained Machine Learning for Intelligence Augmented Materials Discovery.
Products from work supported by TAMIDS Postdoc Project and Data Development Programs
- Attari, Vahid, Pejman Honarmandi, Thien Duong, Daniel J. Sauceda, Douglas Allaire, and Raymundo Arroyave. Uncertainty propagation in a multiscale CALPHAD-reinforced elasto-chemical phase-field model. Acta Materialia 183 (2020): 452-470.
- Feng K., Zanwar P., Behzadan A.H., Chaspari T (2020), Exploring Speech Cues in Web-mined COVID-19 Conversational Vlogs, Proceedings of the Joint Workshop on Aesthetic and Technical Quality Assessment of Multimedia and Media Analytics for Societal Trends (ATQAM/MAST’20), 28th ACM International Conference on Multimedia, Seattle, WA: https://dl.acm.org/doi/10.1145/3423268.3423584
- Osorio, D., Cai, J. (2020), Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA sequencing data quality control. Bioinformatics. https://doi.org/10.1093/bioinformatics/btaa751
- Osorio, D., Zhong, Y., Li, G., Huang, J., Cai, J. (2020) scTenifoldNet: a machine learning workflow for constructing and comparing transcriptome-wide gene regulatory networks from single-cell data. Patterns. https://doi.org/10.1016/j.patter.2020.100139
- Kevin Feng, Preeti Zanwar, Amir H. Behzadan, Theodora Chaspari, Exploring Speech Cues in Web-mined COVID-19 Conversational Vlogs, ACM Multimedia workshop on Media Analytics for Societal Trends (MAST), 2020.
- Osorio, D., Cai, J. (2020), scTenifoldNet: Construct and Compare scGRN from Single-Cell Transcriptomic Data https://cran.r-project.org/package=scTenifoldNet
- Osorio, D., Cai, J. (2020), scTenifoldKnk: In-Silico Knockout Experiments from Single-Cell Gene Regulatory Networks https://cran.r-project.org/package=scTenifoldKnk
- Hee Cheol Chung (2020), Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks, International conference CMStatistics, Dec 20, 2020
- J. Cai (2020), 3rd Workshop on Computational Advances for Single-Cell Omics Data Analysis (CASCODA 2020), 12/10/2020
- J. Cai (2020), 7th NCHU GEAR UP forum, 12/3/2020
- J. Cai (2020), TAMU-NCHU research forum, 11/29/2020
- J. Cai (2020), 1st Annual Gulf Coast Consortia (GCC) Single Cell Omics Cluster Symposium,10/8/2020
- J. Cai (2020), EUSTM-2020 on COVID-19 – 7th Annual Congress of the European Society for Translational Medicine on Covid-19, 9/25/2020
Conference presentations supported by TAMIDS Graduate Student Travel Program
- Zhengyang Wang (Computer Science and Engineering, Advisor: Shuiwang Ji), SIAM International Conference on Data Mining (SDM 2019), “Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions“
- Megnan Du (Computer Science and Engineering, Advisor: Ben Hu), IEEE International Conference on Data Mining (ICDM 2019), “Learning Credible Deep Neural Networks with Rationale Regularization“
- Hongyong Gao (Computer Science and Engineering, Advisor: Shuiwang Ji), International Confernece on Knowledge Discovery and Data Mining (SIGKDD 2019), “Graph Representation Learning via Hard and Channel-Wise Attention Networks“
- Imtiaz Ahmed (Industrial and Systems Engineering, Advisor: Yu Ding), IISE Annual Conference & Expo 2019, “Neighborhood Structure Assisted Non-negative Matrix Factorization and its Application in Unsupervised Point Anomaly Detection”.
- Jeff Martin (Wildlife & Fisheries, Advisor: Perry Barboza), American Society of Mammologists (ASM) 2019, “Drought and temperature influence spatial and temporal variation in growth of North American Bison”
- Rachel Short (Ecosystem Science & Management, Advisor: Michelle Lawing), North American Paleontologist Convention (NAPC) 2019, “Community limb morphology of Artiodactyla as an environmental predictor”
- Peter Ferguson (Physics and Astronomy, Advisor: Louis Strigari), RRL/CEP 2019- Frontiers of Classical Pulsators: Theory & Observations Conference 2019, “Three-dimensional structure of the Sagittarius dwarf spheroidal core from RR Lyrae”
- Daniel Osario (Electrical & Computer Engineering, Advisor: James Cai), Algorithms and Models for Single Cell Genomics Workshop 2019, “Single-Cell Expression Variability Implies Cell Function“
- Jingjia Li (Ecosystem Science and Management, Advisor: Claudia Casola), The Society for Molecular Biology & Evolution Conference 2019, “Identifying promoter DNA regulatory motifs associated with drought related genes”
- Megha Yadav (Computer Science and Engineering, Advisor: Theodora Chaspari), IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, 2019, “Speak Up! Studying the Interplay of Physiological Indices with Individual and Contextual Factors for Quantifying Public Speaking Anxiety”
- Elham Nikbakht (Educational Psychology, Advisor: Fuhui Tong), TESOL International Conference, 2019, “Investigating the interplay of translanguaging on bilingual learners’ reading-to-write tasks
- Anne Salvador (Molecular and Cellular Medicine, Advisor: David Threadgill), Training in Dr. Gudrun Brockman’s Lab in Berlin Germany