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 Management

Drew Casey

TAMIDS Assistant Director for Program Engagement 

Email: drew.casey@tamu.edu 

Location: BLOC 227E

Drew Casey is TAMIDS’s Assistant Director for Program Engagement. Drew has been with Texas A&M since 2017, previously working at the Institute for Engineering Education and Innovation and Texas Sea Grant. Prior to moving to College Station, Drew was a communications professor for Renmin University of China and Embry-Riddle Aeronautical University. He received a bachelor’s degree in Technical and Scientific Communication from Embry-Riddle Aeronautical University in 2009, and in 2011 he received a master’s degree in Asian Studies, with a focus on East-Asian security and technology issues, from Florida State University. Drew is currently working on a master’s in Public Service & Administration from the Texas A&M Bush School.

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.

Christina Retzer

Program Manager

Email: ceretzer@tamu.edu 

Location: BLOC 227B

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.

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, 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, Department of Nuclear Engineering, and 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.

Delany Baum

TAMIDS Program Specialist

Email: delany_baum@tamu.edu

Location: BLOC 223A

Delany joined TAMIDS as the Program Specialist in 2024 where she oversees communications efforts including social media, website updates, and outreach across campus. Before coming to TAMIDS, Delany served as a project coordinator in Texas A&M’s AgriLife Research agency. Delany received her Master’s in environmental science from the University of North Texas in 2020.


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.  

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

Associate Research Scientist & TAMIDS / GEOSAT Operational Data Science Lab Director

Email: piyalong@tamu.edu 

Website: https://piyalong.net/ 

Location: BLOC 221C

Dr. Yalong Pi is an Associate 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

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 Research Engineer III. Haoyu works 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.

Suphanut Jamonnak

Postdoctoral Research Associate, Urban AI Lab

Email: j.suphanut@tamu.edu

Location: BLOC 221B

Dr. Suphanut Jamonnak joined the TAMIDS Urban AI Lab in August 2023 as a Postdoctoral Research Associate working with Dr. Xinyue Ye, Lab director and Professor in the Department of Landscape Architecture and Urban Planning. His research interests include geospatial analysis, visual analytics, Human-computer interaction (HCI) and eXplainable AI (XAI). Dr. Suphanut received his Ph.D. degree in Computer Science from Kent State University in 2021. Before joining TAMIDS, Suphanut worked as Postdoctoral Research Scientists at Research and Technology Center North America, Robert Bosch LLC. His works have been published in multiple leading conferences and journals, e.g. IEEE TVCG, EuroVis, IJGIS and CVPR.

Snehashis Chakraborty

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 Research Engineer III. Snehashis works 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.  

Suparno Bhattacharyya

Postdoctoral Research Associate, Digital Twin Lab

Email: suparnob@tamu.edu

Location: BLOC 221B

Dr. Suparno Bhattacharyya holds a Ph.D. in Engineering Science and Mechanics from Penn State University, an M.Tech in Mechanical Engineering from the Indian Institute of Technology, Kanpur, and a BE in Mechanical Engineering from Jadavpur University, India.

His doctoral research centered on the model order reduction of dynamical systems using Proper Orthogonal Decomposition (POD). This work produced a novel physics-informed criterion that effectively determined the dimension of reduced-order models, ensuring accurate representation for both linear and nonlinear structural vibration systems.

Subsequent to his doctoral studies, Dr. Bhattacharyya undertook a postdoctoral position at Clemson University where he focused on topology optimization for bandgap maximization in 2D lattice structures, and purely data-driven model discovery of structural vibration systems using neural ordinary differential equations.

In August 2023, he transitioned to the TAMIDS Digital Twin Lab as a Postdoctoral Research Associate, working closely with Drs. Jian Tao, Jean Ragusa, and Eduardo Gildin on the reduced-order modeling of nonlinear systems. 

Outside of these research endeavors, Dr. Bhattacharyya has exhibited a commitment to professional growth, securing certifications in both machine learning and online teaching, further enhancing his multifaceted skill set. 

Beyond his academic achievements, Dr. Bhattacharyya is an Indian classical vocalist, reflecting his commitment to cultural traditions. Additionally, he possesses a keen passion for traveling, allowing him to immerse himself in diverse cultures and landscapes.


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

Professor, School of Performance, Visualization & Fine Arts

Associate Dean for Research & Creative Works

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 & Creative Works and Professor in the School of Performance, Visualization & Fine Arts 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.

Yalong Pi

TAMIDS / GEOSAT Operational Data Science Lab Director

See listing above

Lu Tang

TAMIDS Data Justice Lab Director 

Professor, Communications

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

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

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 Student Researchers

Jiaxin Du

Ph.D. Candidate, Department of Landscape Architecture and Urban Planning

TAMIDS Data Science Ambassador

Email: jiaxin.du@tamu.edu

Jiaxin Du is a PhD candidate in the Department of Landscape Architecture and Urban Planning. His research expertise includes GeoAI, urban informatics, and spatial decision support. During the past two years, he has published in six peer-reviewed journals such as the International Journal of Geographical Information Science, Environment and Planning B, and Transactions in GIS. Jiaxin received Robert Raskin Student Paper Award in AAG, Melbern G Glasscock Humanities Award in TAMU, and was a member of the second placed team in the TAMIDS 2023 Wildfire Data Science Challenge. He also serves as a Data Science Ambassador at the Texas A&M Institute of Data Science and received multiple university scholarships. He has been the lead Student Organizer for the 3rd-5th ACM SIGSPATIAL International Workshop on Advances in Resilient and Intelligent Cities. He is the Student Board Director for the Spatial Decision Support Consortium.

Connor Gooch

MS in Geography

Email: cgooch@tamu.edu

Connor Gooch graduated in May 2023 from Texas A&M University-Corpus Christi with a bachelor’s degree in Geographic Information Science. He joined Texas A&M in August 2023 and is pursuing a Master’s in Geography. His professional experience is with an internship with the Texas Department of Transportation Corpus Christi District Survey, working as a survey team member conducting field surveys, and working with the GIS department to create and upload GIS data. His research focuses on the utilization of GIS for Transportation, GeoAI, and Python coding.

At TAMIDS he is working on with Snehashis Chakraborty and Nick Duffield on geospatial analysis of public safety radio data in a NIST-funded collaboration with the Internet 2 Technology Center, the Department of Electrical & Computer Engineering, and the School of Performance, Visualization & Fine Arts.

Isaias Negassi

MS in Data Science, Electrical and Computer Engineering Track

Email: isaiasnegassi@tamu.edu

Isaias Negassi is a Masters student in the Data Science program at Texas A&M University. He is a graduate research assistant with TAMIDS working on Machine Learning and Computer Vision applications. Isaias is excited to join Dr. Nick Duffield and Dr. Yalong Pi on the point-based spore detection using P2PNet, and the Texas One Gulf projects.  

Isaias joined Texas A&M in the fall of 2022, after earning his Bachelor’s degree in Electrical and Electronics Engineering from the Higher Colleges of Technology in Abu Dhabi, United Arab Emirates. As an undergraduate student, he developed a smart car plate recognition gate that allowed or denied entrance, and a large-scale empirical formula for a 2.4 GHz outdoor wireless network. This work was published in IEEE. He also developed a real-time driver drowsiness detection system using deep learning which was published in the International Journal of Artificial Intelligence.

Janvita Reddy

MS in Data Science, Computer Science and Engineering Track

Email: janvita11@tamu.edu

Janvita Reddy joined Texas A&M University in the fall of 2023 to pursue a master’s in Data Science. She completed her undergrad in May 2023 in Mechanical Engineering from the National Institute of Technology, Surat. Janvita’s research interests include Machine Learning with a focus on Computer Vision. During her undergrad, Janvita worked on an industrial project to fully automate the welding process using object detection and also undertook a research internship on domain generalisation models using GANS. She worked with an astronomy research group which resulted in the publication of a paper in The Monthly Notices of the Royal Astronomical Society journal. Janvita is excited to work with Prof. Nick Duffield and Dr. Haoyu Niu on water stress prediction on cotton crops .

Jack Wooley

MS in Data Science, Computer Science & Engineering Track

Email: jwooley@tamu.edu

Jack Wooley graduated in April 2023 from Brigham Young University – Provo with a bachelor’s degree in statistical science and a minor in Spanish. He came to Texas A&M in August 2023 and is currently a student in the Master’s of Data Science program, with an emphasis in computer science and engineering. Jack spent the last year of his undergrad working as a data engineer and analyst for BYU Broadcasting, where he built data pipelines and visualizations and started work on the company’s first fully automated end-to-end ML pipeline, which was used for predicting viewer churn. Additionally, during Jack’s undergrad, he spent a summer as a research assistant for the BYU Physics & Astronomy Department and contributed to a publication in the journal The Monthly Notices of the Royal Astronomical Society.


TAMIDS Former Members

  • Mohsen Aghashahi (Research Engineer), Data Scientist, USAA
  • Bahareh Alizadeh (Research Engineer)
  • Jin Cao (Postdoc), Assistant Professor, Department of Statistics, University of Houston
  • Jisu Cao (Postdoc), Assistant Professor, Department of Information Systems, Arizona State University
  • Hee Cheol Chung (Postdoc), Assistant Professor, University of North Carolina at Charlotte
  • Sutanoy Dasgupta (Visiting Professor), Senior Data Scientist, Intuit
  • Liang Ding (Postdoc), Assistant Professor, Fudan University
  • Yu Ding (Associate Director for Research Engagement), Anderson-Interface Chair Professor, Georgia Institute of Technology
  • Brandon Green (Assistant Director for Industry Engagement) BlueForge Alliance
  • 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 (Postdoc) Assistant Professor, Binghamton University
  • Shahina Rahman (Coordinator for Student Initiatives & Faculty Fellow) AI Research Scientist, Amazon
  • Diego Rodriguez (Assistant Director for Educational Programs), Director, Multicultural & International Student Support and Engagement, University of Iowa
  • Carlie Schmidl (Administrative Associate), Event Coordinator, Infinity Hospitality, Nashville, TN
  • Siddhanth Reddy Sirgapoor (Student Technician), MS Data Science
  • Sree Kiran Prasad Vadaga (Research Specialist), AI/ML Engineer, PayPal
  • Yashaswini Yeramalli (Student Technician), MS Computer Science
  • 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