TAMIDS Member Profiles

Nick Duffield

TAMIDS Director

Professor, Department of Electrical and Computer Engineering

Royce E Wisenbaker Professor I

Email: duffieldng@tamu.edu

Website: https://tx.ag/duffield

Location: BLOC 227G / WEB 332D

Phone: 979.845.7328

Dr. Nick Duffield is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, holder of the Royce E. Wisenbaker Professorship I, and Director of the Texas A&M Institute of Data Science. He is co-Director of the NSF TRIPODS Research Institute on the Foundations of Interdisciplinary Data Science at Texas A&M, serves on the Executive Committee of the Texas A&M Center for Geospatial Sciences, Applications and Technology (GEOSAT), and holds a courtesy appointment in the Texas A&M Department of Computer Science and Engineering. His research combines the foundations and applications of data science and computer networking, currently graph stream sampling, network measurement and resilience, and applications of data science to transportation, agriculture, hydrology, infrastructure and operations. In his TAMIDS role he directs the MS in Data Science in collaboration with the Colleges of Science and Engineering, He is an ACM Fellow, IEEE Fellow, and IET Fellow, and was a co-recipient of the ACM Sigmetrics Test of Time Award in both 2012 and 2013 for work in Network Tomography. From 1995 to 2013 Duffield worked at AT&T Labs, Florham Park, NJ, where he was a Distinguished Member of Technical Staff and an AT&T Fellow, and prior to that held faculty and postdoctoral positions in Germany and Ireland. He received his PhD in Physics from the University of London, UK in 1987 and the MMath and BA in Natural Sciences from the University of Cambridge, UK, in 1983 and 1982 respectively.


TAMIDS Program Directors

Yu Ding 

 TAMIDS Associate Director of Research Engagement

Mike and Sugar Barnes Professor, Industrial  & Systems Engineering 

Affiliated Faculty, Electrical & Computer Engineering

Email: yuding@tamu.edu 

Website: Yu Ding Profile  

Location: ETB 4016

Phone: 979.458.2343

Dr. Yu Ding is Associate Director for Research Engagement of Texas A&M Institute of Data Science and the Mike and Sugar Barnes Professor of Industrial & Systems Engineering at Texas A&M University.  Dr. Ding received his Ph.D. degree from the University of Michigan in 2001. His research interest is in data and quality science. Dr. Ding is a recipient of the 2018 Texas A&M Engineering Research Impact Award, the 2019 IISE Technical Innovation Award, the 2020 Texas A&M’s University-Level Distinguished Achievement Award in Research, and a Fellow of IISE and ASME.  Dr. Ding is serving as the Editor-in-Chief for IISE Transactions for the term of 2021-2024.

Simon Foucart

TAMIDS Associate Director of External Academic Engagement 

Professor, Department of Mathematics

Email: foucart@tamu.edu 

Website: Simon Foucart Profile 

Location: BLOC 502D

After earning a Masters of Engineering from Ecole Centrale Paris, Simon Foucart received his PhD in Mathematics from the University of Cambridge in 2006. He took two postdoctoral positions, at Vanderbilt University and at Paris 6 University, before joining Drexel University in 2010 and moving to the University of Georgia in 2013. Since 2015, he has been with Texas A&M University, where he became Professor and Presidential Impact Fellow in 2019. He also held short visiting appointments at University of Bonn, University of South Florida, Hong Kong University of Science and Technology, CNRS Toulouse, and University of Wisconsin-Madison.

Dr. Foucart’s most influential work to-date revolves around the field of Compressive Sensing. His contribution was recognized by the 2010 Best Paper Award from the Journal of Complexity. His current interests include the mathematical aspects of Metagenomics, Optimization, Deep Learning, and Data Science at large. He serves on the editorial board of Journal of Approximation Theory, of Journal of Numerical Mathematics, and of Sampling Theory, Signal Processing, and Data Analysis.

Aside from 50+ peer-reviewed research articles, Dr. Foucart has written two graduate-level textbooks: ‘A Mathematical Introduction to Compressive Sensing’ (with Holger Rauhut, Birkhauser) and ‘Mathematical Pictures at a Data Science Exhibition’ (to appear, Cambridge University Press).

Krishna Narayanan

TAMIDS Associate Director for Education Initiatives

Eric D. Rubin ’06 Professor, Department of Electrical and Computer Engineering

Email: krn@tamu.edu

Website: http://krishnanarayanan.wikidot.com/

Location: BLOC 221A

Phone: 979.422.9891

Dr. Krishna Narayanan is TAMIDS Associate Director for Education Initiatives and Eric D. Rubin ’06 Professor in the Department of Electrical & Computer Engineering. Dr. Narayanan leads the academic design of new education and training programs, both within TAMIDS and collaboratively with Texas A&M faculty and academic units.

After earning a Bachelor’s degree from Coimbatore Institute of Technology, Masters of Electrical Engineering degree from Iowa State University, Krishna Narayanan received his PhD in Electrical Engineering from the Georgia Institute of Technology in 1998. Since1998, he has been with Texas A&M University, where he became Professor in 2008 and Eric D. Rubin ’06 Professor in 2016., He also held short visiting appointments at University of California at Berkeley, Institut Eurecom, Sophia Antipolis, France and University of Illinois at Urbana Champaign. Dr. Narayanan’s research interests include coding theory and information theory, machine learning, signal processing for big data, next-generation wireless systems including 5G/6G cellular systems, Internet of Things, data storage, and distributed computing.

Aside from numerous publications, editorial positions, and invited talks, Dr. Narayanan has been recognized with a variety of prestigious awards for both his teaching and research including the 2014 Professional Progress in Engineering Award from the College of Engineering at Iowa State University, the 2018 Texas A&M Association of Former Students university-level teaching award, the 2009 Halliburton professorship, the 2020 and 2006 Best Paper Awards in data storage  from the IEEE communications society and the 2001 National Science Foundation CAREER award, and in 2015, Dr. Narayanan was elected IEEE Fellow for his research and educational contributions.

Brandon Green

TAMIDS Assistant Director for Industry Engagement

Email: brandon.green@tamu.edu

Location: BLOC 227E

Brandon Green joined the Texas A&M Institute of Data Science as Assistant Director for Industry Engagement. Brandon comes to us from TAMU Engineering where he has been part of the Texas A&M Engineering Experiment Station’s Professional Education group.  Before coming to TAMU 5 years ago, Brandon spent a variety of roles in Industry ranging from groups involved in education, entertainment, research as well as the medical community. Brandon obtained his undergraduate from Rice University and his Masters in Leadership in Higher Education from Pepperdine University.  Outside of work Brandon spends time with his 4 kids (Jackson 10, Olivia 8, Brody 6 & Guy 4) and wife Kara. Brandon enjoys sports and almost any outdoor activity.  Brandon is a native Texan and has expressed his excitement to join the TAMIDS team in helping advance the mission of TAMIDS and the people we serve in the State of Texas.

Jian Tao

TAMIDS Assistant Director for Project Development & TAMIDS Digital Twin Lab Director

Assistant Professor, Visual Computing and Creative Media Section, School of Performance, Visualization & Fine Arts

Affiliated Faculty, Electrical and Computing Engineering, Nuclear Engineering, and Multidisciplinary Engineering, College of Engineering

 Email: jtao@tamu.edu 

 Website: Jian Tao Profile 

 Location: BLOC 224C / ARCA 314

Dr. Jian Tao is an Assistant Professor in the School of Performance, Visualization and Fine Arts at Texas A&M University. Dr. Tao also holds courtesy appointments at the Department of Electrical & Computer Engineering, the Department of Nuclear Engineering, and the Department of Multidisciplinary Engineering. Dr. Tao has been a key contributor to TAMIDS programs in education, training, and research engagement, and served as the Associate Director of TAMIDS SciML Lab. At TAMIDS, Dr. Tao leads the development and execution of Data Science collaboration between TAMIDS and Texas A&M academic and operational partners.

Tao received his Ph.D. in Computational Astrophysics from Washington University in St. Louis in 2008 and worked on computational frameworks for numerical relativity, computational fluid dynamics, coastal modeling, and other applications at Louisiana State University before he joined Texas A&M in 2016. In 2018, Tao led the Texas A&M team to the final of both the ASC18 and SC18 student cluster competitions. He currently serves as a faculty advisor of the Texas A&M 12th Unmanned Team for the SAE/GM AutoDrive Challenge Competition and leads a project funded by the Department of Commerce to build a digital twin for the Disaster City at Texas A&M University. Tao is an NVIDIA DLI University Ambassador and XSEDE Campus Champion at Texas A&M and a contributor to the SPEC CPU 2017 benchmark suite.

His research interests include numerical modeling, machine learning, data analytics, distributed computing, visualization, digital twin, and workflow management.


TAMIDS Administration 

Jennifer South

Senior Administrative Coordinator II 

Email: jsouth@tamu.edu 

Location: BLOC 227F

Phone: 979.220.3868

Jennifer South is Senior Administrative Coordinator II at TAMIDS. Jennifer has worked at TAMIDS since December 2018, where she coordinates TAMIDS many programs and events, administers its operations, and is the liaison with our organizational partners throughout Texas A&M. Jennifer joined TAMU in 1989. Prior to joining TAMIDS, Jennifer spent the past 18 years working as Assistant to the Department Head (2000-2014) and Assistant to the Director for Online Programs and MS Analytics program (2014-2018) for the Department of Statistics. Jennifer’s vast experience in her past roles in coordinating administrative support, project management in the area of development and distance education, make her an invaluable member of our staff.  

Christina Retzer

Program Manager

Email: ceretzer@tamu.edu 

Location: BLOC 227B

Christi Retzer joined TAMIDS as Program Coordinator II. Christi coordinates TAMIDS Educational Programs, including the new MS in Data Science program which will welcome its first cohort of students in Fall 2021. Christi has been working in higher education for the past twelve years. She worked at the University of Houston for five years as an international transfer credit analyst and then spent seven years at the University of Texas Medical Branch as a graduate admissions coordinator for the School of Nursing, and as a graduate program coordinator for the Institute for Medical Humanities. Christi received her Bachelor’s Degree in Applied Design/Visual Arts from the University of Houston-Clear Lake, and her MBA from Texas Woman’s University. Outside of work Christi enjoys traveling, wine tasting, home and art projects, and spending time with her three nephews.

Angie Rollins

Administrative Coordinator I

Email: a-rollins@tamu.edu

Location: BLOC Suite 227

Angie Rollins joined the Texas A&M Institute of Data Science (TAMIDS) team on November 1, 2022 as Administrative Coordinator I. In this position, Angie will provide administrative support to TAMIDS leadership and staff, provide general office support and assist with event coordination and planning. Angie comes to us from the Department of Entomology, Texas A&M Agrilife, where she worked in administrative positions for the past 13 years. Outside of work, Angie enjoys spending time with her family and stays busy trying to keep up with her 11yr old daughter, Summer. Angie is passionate about cooking, spontaneous getaways with family & friends and her cats! Welcome to TAMIDS Angie! We are excited to have you on board!

Allie Saxton

Student Web Developer

Allie Saxton is a Computer Science Student at Texas A&M, and has been working with TAMIDS since May 2022 as a student technician. Alongside maintaining the TAMIDS website, Allie helps out with the Coffee Connections program by matching participants. In her free time, she loves baking and going on hikes.


TAMIDS Research Staff

Yalong Pi

Assistant Research Scientist, Operational Data Science

Email: piyalong@tamu.edu 

Website: https://piyalong.net/ 

Location: BLOC 221C

Dr. Yalong Pi is an Assistant Research Scientist in the Texas A&M Institute of Data Science (TAMIDS) at Texas A&M University since 2020. During 2013-2016, he worked as a project manager at Gree Real Estate Co. Ltd, Zhuhai City, China. He also worked as a junior architect at Shanghai Water&Rock Group in 2017. He obtained a Ph.D. in Architecture from Texas A&M University (2020), a Master’s Degree of Civil Engineering (2013) from Wuhan Institute of Technology, and a Bachelor Degree of Mechanical Engineering (2011) from Wuhan Textile University. He is a certified Architectural Engineer in mainland China. His research focuses on machine learning (computer vision) and data mining, applications in domains including disaster reconnaissance, transportation, construction automation, and building information modeling.

Haoyu Niu

TEES Research Engineer III

Email: hniu@tamu.edu

Location: BLOC 221E

Dr. Haoyu Niu joined the Texas A&M Institute of Data Science (TAMIDS) on January 1, 2023,as a TEES Research Engineer III. Haoyu will work at the intesection of Data Science and cyberinfrastructure for smart agriculture. He joins a team of researchers from TAMIDS, Texas A&M’s Department of Electrical & Computer Engineering, AgriLife Research, AgriLife Extension, and the School of Performance, Visualization and Fine Arts on a project to develop data-driven infrastructure that enables efficient irrigation using AI-derived crop-growth model based in UAS imaging and environmental data.

Haoyu received his Ph.D. in Electrical Engineering and Computer Science from the University of California, Merced in 2022.  Among many honors and awards, most recently Haoyu won first place for the 2021 CITRIS Aviation Prize and in 2020 was awarded the GRAD-EXCEL Award for Peer Mentorship. Haoyu’s research interests are in Machine Learning, Deep Learning, Big Data, Precision Agriculture, and sUAS Remote Sensing/Application, such as water stress detection, early detection of nematodes, yield estimation, and evapotranspiration (ET) estimation.

Snehashis Chakraborty

TEES Research Engineer III

Email: snehashisc@tamu.edu

Location: BLOC 221F

Website: Snehashis Chakraborty Profile

Snehashis Chakraborty joined the Texas A&M Institute of Data Science (TAMIDS) on February 1, 2023, as a TEES Research Engineer III. Snehashis will work to develop innovative Data Science and AI applications for infrastructure and operational project, including a NIST-supported collaboration to develop data and tools for planning for Public Safety Radio services.

Snehashis received his Masters in Statistics from the Indian Statistical Institute, Kolkata in 2014. He worked as a data scientist in industry from 2014 to 2018 for a ride-sharing start up, as well as multinational banks. More recently, Snehashis spent the last four years as an Industry Research Fellow at the National University of Singapore. Among his many achievements, Snehashis won the best project award at ICICI Bank for location based intelligence models in 2015. Snehashis research interests lie in statistical modeling, text mining, machine learning and computer vision.  


TAMIDS Thematic Lab Directors

Ulisses Braga-Neto 

TAMIDS SciML Lab Director

Professor, Electrical and Computing Engineering 

Email: ulisses@tamu.edu 

Website: Ulisses Braga-Neto Profile 

Location: WEB 236B

Phone: 979.862.6441

Dr. Ulisses Braga-Neto is a Professor at the Electrical and Computer Engineering Department of Texas A&M University. He received his Ph.D. in Electrical and Computer Engineering from The Johns Hopkins University in 2002. His research focuses on Statistical Signal Processing and Machine Learning, with applications in diverse scientific and engineering problems. Dr. Braga-Neto has proposed novel algorithms in these areas, such as the Bolstered Classifier Error Estimator, the Boolean Kalman Filter, and Self-Adaptive Physics-Informed Neural Networks. He is Director of the Scientific Machine Learning Lab at the Texas A&M Institute of Data Science (TAMIDS). He is currently Associate Editor of the IEEE Signal Processing Magazine and a member of the Machine Learning for Signal Processing Technical Committee at the IEEE Signal Processing Society (SPS). He is a former President of the Mid-South Computational Biology and Bioinformatics Society (MCBIOS). Dr. Braga-Neto has authored more than 140 peer-reviewed publications, including two books. He received the NSF CAREER Award in 2009 and the Outstanding Professor Award from the Department of Electrical and Computer Engineering at Texas A&M University in 2013.

Ann McNamara 

TAMIDS VIVID Lab Director

Associate Professor, Visualization

Associate Dean for Research, College of Architecture

Email: ann@viz.tamu.edu 

Website: Ann McNamara’s Profile

Location: SCTS 105

Phone: 979.845.4715 

Dr. Ann McNamara is the Associate Dean for Research in the College of Architecture and an Associate professor in the Department of Visualization at Texas A&M University. Her research focuses on advancing computer graphics and data visualization through novel approaches for optimizing an individual’s experience when creating, viewing, and interacting with data, particularly using new paradigms for immersive virtual and augmented spaces.

Lu Tang

TAMIDS Data Justice Lab Director 

Associate Professor, Communication

Email: ltang@tamu.edu

Website: Lu Tang Profile

Location: BLTN 209D

Phone: 979.845.5500

Dr. Lu Tang is an Associate Professor of Health Communication at the Department of Communication, Texas A&M University. She received her doctorate in communication from the Annenberg School for Communication and Journalism at the University of Southern California. She taught at University of Tennessee, Knoxville, and the University of Alabama before joining TAMU in 2017.

Her research shows how people understand and communicate about health and illness and how such understanding and communication are enabled and constrained by social, political, cultural, and technological factors. Currently, her research focuses on the spread of health misinformation on social media, especially misinformation related to vaccines. Her work has been covered in major news outlets including CNBC, Time, Bloomberg Law, and Houston Chronicle.

Jian Tao

TAMIDS Digital Twin Lab Director & TAMIDS Assistant Director for Project Development

See listing above

Xinyue Ye

TAMIDS Urban Artificial Intelligence Lab Director

Associate Professor, Landscape Architecture & Urban Planning

Email: xinyue.ye@tamu.edu

Website: Xinyue Ye Profile

Location: ARCA A 306

Phone: 979.485.4306

Dr. Xinyue Ye holds Harold Adams Endowed Professorship at Department of Landscape Architecture and Urban Planning at Texas A&M University. His research focuses on geospatial artificial intelligence, big data, smart cities, and urban computing. According to Google Scholar Citation Global Ranking, Dr. Ye is ranked as: Urban Informatics (#7) and Spatial Econometrics (#11). Because of his innovative research on integrating geography, planning, and computational science, Dr. Ye was the most junior faculty and only the second planning faculty elected as a Fellow of the American Association of Geographers (AAG).

Prof. Ye received the Regional Development and Planning Distinguished Scholar Award from AAG in 2022. He was the recipient of annual research awards from both computational science (New Jersey Institute of Technology) and Geography (Kent State University). He was named one of the top 10 young scientists by The World Geospatial Developers Conference 2021. His work has been funded by National Science Foundation, National Institute of Justice, Department of Commerce, Department of Energy, Department of Transportation, Department of Health and Human Services, Microsoft, and Canada Social Sciences and Humanities Research Council.

Prof. Ye directs the focus of smart cities and transportation in the PhD program of Urban and Regional Science at Texas A&M University. At TAMIDS, he leads Urban Artificial Intelligence Lab. In addition, he is supported by Data Science Course Development Grant Program and Faculty Research Collaboration Program by TAMIDS.


TAMIDS Associate Staff

Jian Cao

Postdoctoral Research Associate

Department of Statistics (Mentor: Matthias Katzfuss)

TAMIDS Postdoc Project Program

Email: jian.cao@tamu.edu

Dr. Jian Cao joined the Department of Statistics, College of Science, in May 2021 as Postdoctoral Researcher with Dr. Matthias Katzfuss, Associate Professor, supported in part by the TAMIDS Postdoc Project Program. Dr. Cao obtained his Ph.D. degree in Statistics from King Abdullah University of Science and Technology (KAUST) in 2020. In 2018, he won the Student Paper Award from the Statistics Computing Section of the American Statistical Association. Dr. Cao’s main research interests include high-dimensional Gaussian processes, computational statistics, low-rank methods, and scientific computing. For his TAMIDS activities, Dr. Cao collaborates with Dr. Katzfuss and Dr. Seth Murray, Professor and Butler Chair for Corn Breeding and Genetics, Department of Soil and Crop Sciences, on statistical modeling and prediction for corn-field growth.

Matthew Hielsberg

Research Specialist V

Department of Mathematics & Institute for Scientific Computation

TAMIDS Research Support

Email: hielsber@tamu.edu 

Website: https://www.math.tamu.edu/~hielsber/ 

Location: BLOC 608E 

Matthew Hielsberg is a Research Specialist V currently employed full-time by the Mathematics Department at Texas A&M University and is affiliated with the Institute for Scientific Computation (ISC) and the Institute of Data Science (TAMIDS).  Over the past 19 years, Mr. Hielsberg has worked to support many research efforts with graphics software, simulation, tool generation and support, cluster support and administration as well as student mentoring and training.  He has also collaborated with many researchers from several universities and businesses, and made contributions to many successful MURI’s, SBIR’s, STTR’s and other projects.  

From 2002 to 2010 Mr. Hielsberg worked for the Interdisciplinary Mathematics Institute at the University of South Carolina.  During his time at USC Mr. Hielsberg focused on creation of visualization tools, custom research applications and algorithm development.  He created tools for the real-time manipulation of molecules in Visual Molecular Dynamics (VMD) using USC’s stereographic CAVE and 6D mouse.  As part of the AVCAAF program he designed and developed several packages for feature tracking, structure from motion (SFM), and the real-time approximation of terrain from large point cloud data sets using mathematical learning theory.  Additionally, he created the USC Simulator, which enabled researchers to use common tools, including Matlab and the USC CAVE, to place simulated cameras and lidar-like sensors in 3D virtual environments for data generation and scenario development.  

Mr. Hielsberg was loaned to Texas A&M University in the fall of 2009 for the purpose of designing and developing both algorithms and software for hybrid implicit/explicit terrain learning from point clouds.  In 2010 Texas A&M University hired Mr. Hielsberg as an Associate Research Specialist.  Since that time he has worked with the Group for Analysis, Imaging and Numerics (GAIN) to develop software for visualizing and analyzing hyperspectral lidar, constrained optimization, parameter estimation of elliptic pde’s, data assimilation, compressive sensing, and deep learning.  He has also developed an introductory video series on the R programming language for the TAMIDS Biomedical Data Science Online Training Program, as well as a Python series directed towards the Math Graduate Program.  He has made contributions to the TAMU visualization center and to the PCL community, where he organized and maintained a repository of freely available research data and software.  In 2020 Mr. Hielsberg took over as administrator of the Whistler Computing Cluster for the Numerical Analysis and Scientific Computation group within the Mathematics Department.

Shaogang Ren

Postdoctoral Research Associate

Department of Electrical & Computer Engineering (Mentor: Xiaoning Qian)

TAMIDS Postdoc Project Program

Email: renshaogang@gmail.com  

Dr. Shaogang Ren joined the Department of Electrical & Computer Engineering in Oct. 2022 as a Postdoctoral Researcher with Prof. Xiaoning Qian. Dr. Ren received his Ph.D. degree in computer engineering from Texas A&M University in 2017. His research interests include deep generative models, causal inference using neural networks, optimization, and their applications in computer vision, medical data analysis, bioinformatics, etc. His works have been published in multiple leading conferences and journals, e.g. NeurIPS, AIStats, TPAMI, WWW, KDD, and so on.


TAMIDS Former Members

  • Mohsen Aghashahi (Research Engineer), Data Scientist, Sysco
  • Jisu Cao (associated postdoc), Assistant Professor, School of Business, University of Connecticut
  • Hee Cheol Chung (associated postdoc), Assistant Professor, University of North Carolina at Charlotte
  • Sutanoy Dasgupta (Visiting Professor), Senior Data Scientist, Intuit
  • Liang Ding (associated postdoc), Assistant Professor, Fudan University
  • Zachary Handshoe (student web developer), Software Engineer, ExxonMobil
  • Jianhua Huang (Associate Director), Associate Dean and Presidential Professor Chair, Chinese University of Hong Kong, Shenzhen
  • Dehao Liu (associated postdoc) Assistant Professor, Binghamton University
  • Shahina Rahman, (Coordinator for Student Initiatives & Faculty Fellow) AI Research Scientist, Amazon
  • Carlie Schmidl (Administrative Associate), Event Coordinator, Infinity Hospitality, Nashville, TN
  • Ming Zhong, (Assistant Research Scientist) Assistant Professor, Illinois Institute of Technology
    • Research Interests: Scientific Machine Learning, Inverse Problems, Image/Signal Processing, Numerical ODE/PDE, Modeling and Simulation. In his new role, Ming continues to collaborate with TAMIDS SciML Lab, working with Prof. Braga-Neto on his recently awarded NSF grant on Bayesian PDE with Physics Informed Machine Learning, with Prof. Lifan Wang and Prof. Braga-Neto on using Physics Informed Machine Learning for applications in astrophysics, and with Prof. Braga-Neto and Prof. Elaine Oran and her former postdoc on using Physics Informed Machine Learning for applications in aerospace engineering