Biography - ACCESS Researcher Advisory Committee
Full Name | Website Link | Background |
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A. Murat Maga |
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Abhishek Srivastava | Abhishek is an Innovative Computational Scientist and Technology Leader with over 12 years of experience in physics-based computational modeling, mechanical engineering, and product development. He holds a PhD in Applied Mechanics from Cornell University where his research focused on membrane and adhesion mechanics. | |
Aniruddha Maiti |
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Badri Narayanan |
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Chang Liu | Dr. Chang Liu is an assistant professor at the University of Connecticut, School of Mechanical, Aerospace, and Manufacturing Engineering. His research group, FLUids, rEduction, Nonlinearity, and Turbulence (FLUENT) group, focuses on reduced-order modeling and analysis of fluid flows using various tools, including control theory, nonlinear dynamical systems, and optimization. Our group is interested in fluid dynamics problems arising from various applications, including aerospace engineering, naval and ocean engineering, atmosphere, and physical oceanography. | |
Changqing Cheng | Changqing Cheng is an Associate Professor with the School of Systems Science and Industrial Engineering, Binghamton University. His research interests include nonlinear dynamics analysis, statistical learning, simulation and modeling for process monitoring, quality control, and performance optimization of complex systems. | |
Dhara Trivedi | Dhara Trivedi is an Assistant Professor in the Physics Department at Clarkson University. Trivedi is a theoretician whose research focuses on developing new methods as applied to problems in nanotechnology, energy and charge transfer in complex condensed-phase chemical and biological environments, and properties of materials. Her past research work has also been concerned in the field of Spintronics, providing concise relations between the degrees of spin polarization and measured circular polarization for each of the dominant phonon-assisted optical transitions. | |
Dibakar Datta | Dr. Dibakar Datta is an Associate Professor in the Department of Mechanical and Industrial Engineering at the New Jersey Institute of Technology (NJIT). He earned his Ph.D. in 2015 from Brown University, where he specialized in Solid Mechanics with minors in Physics and Chemistry. His current research focuses on applying Generative AI to discover novel materials for next-generation energy, quantum, and biomedical applications. His research on energy storage has received international media coverage, and he is a recipient of the National Science Foundation (NSF) CAREER Award. | |
Donald Krieger | Don Krieger is a member of the Brain Trauma Research Center at the University of Pittsburgh. His work with supercomputing resources began in 1990 with the Cray Y-MP at the Pittsburgh Supercomputing Center. He served as user representative to the Open Science Grid Governing Council. His research is focused on understanding concussion in humans and in developing diagnostic neurophysiological measures using magnetoencephalography. | |
Gavin Fitzgerald |
| Gavin Fitzgerald is a STEM Coach and Biology faculty member at Morgan Community College, where he oversees undergraduate research across multiple departments. Trained in cellular and molecular biology, his research background includes viral gene editing as well as land and animal conservation. At MCC, he is dedicated to advancing student engagement in STEM by providing experiential learning opportunities, including field research and collaborations with leading scientific organizations. Currently, he mentors a student research team working with NASA on experiments aboard the International Space Station, investigating plant germination and gene expression in microgravity. Outside of academia, Gavin manages breeding programs for diverse poultry species and remains actively involved in applied conservation initiatives. |
George Ostrouchov | Performed research in computational statistics and data science since the mid 1980’s, including early parallel computing on the first commercial cluster computers. For the last two decades, concentrated on developing and using parallel computing packages and applications in the R software environment on various cluster systems ranging from midsize to the largest in the world. | |
Jack Skinner | Jack Skinner is a Postdoctoral Scholar at Caltech. His research focuses on numerical modeling of planetary atmospheres and oceans, with an emphasis on rotating and stratified fluids at high Reynolds number. He studies how vortices, turbulence, and wave–mean flow interactions shape the flows on exoplanets, Earth's atmosphere and oceans, solar system gas giants, and other astrophysical objects, and how these dynamics can be observed by current and next-generation missions. | |
James E Chapman |
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Kresimir Rupnik |
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Kristen Fichthorn |
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Kumaraswamy Naidu Chitrala |
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Kyle Godbey | Kyle Godbey is a research assistant professor at Michigan State University working at the Facility for Rare Isotope Beams on applications of advanced computing and data science to a variety of topics in basic and applied nuclear science. Kyle is also a co-founder of the Advanced Scientific Computing and Statistics Network, a community organization dedicated to broadening participation in advanced computing research. | |
Mahsa Dabaghmeshin | Dr. Mahsa Dabagh is an Associate Professor in University of Wisconsin-Milwaukee (UWM)’s Biomedical Engineering and Computer Science Departments. She is co-chair for Research subcommittee of Northwestern Mutual Data Science Institute and Richard and Joanne Grigg Faculty Fellow. Dr. Dabagh is interested in developing virtual human tissues to study cancer malignancy and mechanobiology in cancer. | |
Mohamed Abouelkhair | https://www.linkedin.com/in/mohamed-abouelkhair-dvm-ms-phd-dipl-acvm-62a401aa/ | My research began with host–pathogen interactions, including developing a patented vaccine composition against multidrug-resistant Staphylococcus pseudintermedius, and later directed diagnostic virology and immunology labs. Building on this microbial expertise, I now study the tumor microenvironment in companion animal cancers, exploring microbial proteins as therapeutics and immune modulators. My work integrates genomics, proteomics, CRISPR, and cloud computing to uncover novel targets and develop innovative immunotherapies for aggressive cancers. |
Pariksheet Nanda |
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Parisa Khodabakhshi | https://engineering.lehigh.edu/faculty/parisa-khodabakhshi
| Parisa is currently an Assistant Professor in the Department of Mechanical Engineering & Mechanics at Lehigh University. Her research lies at the intersection of computational mechanics, materials science, and scientific machine learning. |
Peter Couvares |
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Petr Krysl |
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Rajamani Narayanan | I have been performing research in the field of theoretical particle physics and quantum field theory since 1987. I use a technique called the lattice formalism of field theories and perform numerical analysis of large strongly interacting systems. | |
Roman Gerasimov | Dr. Roman Gerasimov is a postdoctoral researcher at the University of Notre Dame. His research uses the chemical compositions of ancient stars to reconstruct the history of our Galaxy and its neighbors. A long-time user of ACCESS resources, he applies high-performance computing to model the connection between stellar chemistry and observable properties. He also leverages ACCESS to train undergraduate students in computational stellar astrophysics. | |
Sameer Sameer | https://www.ou.edu/cas/physics-astronomy/people/directory/post-docs/sameer | Sameer is an observational astronomer and postdoctoral research associate at the University of Oklahoma, specializing in the study of the circumgalactic medium (CGM) - the diffuse gas surrounding galaxies. He earned his Ph.D. in Astronomy & Astrophysics from Pennsylvania State University in 2022, with a minor in Computer Science, focusing on innovative Bayesian modeling techniques to understand multiphase gas structures around galaxies. His research career spans over a decade, beginning as a mass spectroscopist at India's Physical Research Laboratory (2011-2016), where he studied meteorites and blazars, before transitioning to postdoctoral positions in Astronomy at Notre Dame (2022-2025) and now Oklahoma. He has secured competitive observing time on major telescopes including the Hubble Space Telescope, where he leads programs studying gas properties across cosmic history. Sameer is known for developing the cloud-by-cloud, multiphase, Bayesian modeling (CMBM) approach for analyzing astronomical absorption spectra. He has authored over 25 peer-reviewed publications with over 650 citations, and maintains an active research program using both observational data and computational modeling. |
Shaoming Cheng |
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Stefano Iacus |
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Steven Cutchin | https://www.boisestate.edu/coen-cs/people/faculty/steven-cutchin/ | Dr. Steve Cutchin joined the faculty at Boise State University in August 2013 From 2008 to 2013 he was manager of the KAUST Visualization Laboratory Core Facility and the Supercomputer Facility at King Abdullah’s University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. At KAUST he recruited a technical team of engineers and visualization scientists while managing the building of the state of the art scientific data visualization laboratory on the KAUST campus, forged relationships with international university and corporate partners, continued to improve the laboratory and recruit new staff. Prior to his work in Saudi Arabia, Dr. Cutchin worked at the University of California, San Diego (UCSD) first as manager of Visualization Services at the San Diego Supercomputer Center and later at California Institute for Telecommunications and Information Technology (Calit2). He has worked as a Sr. Software Engineer at Walt Disney Feature Animation developing software tools to improve animation production on feature films. He has published articles on Computer Graphics and Visualization, created animations for Discovery Channel and images for SIGGRAPH and Supercomputing conferences and journals. He received his doctorate from Purdue University in Computer Science. |
Surl-Hee (Shirley) Ahn | https://che.engineering.ucdavis.edu/people/surl-hee-shirley-ahn | Surl-Hee (Shirley) Ahn is an assistant professor in the Department of Chemical Engineering at the University of California Davis. She received her B.A. in Biochemistry and Mathematics, M.A. in Mathematics, and M.S. in Chemistry at the University of Pennsylvania in 2012 and her Ph.D. in Chemistry (Chemical Physics) at Stanford University, advised under Prof. Eric Darve, in 2018. Subsequently, she worked as a postdoctoral scholar in the Department of Chemistry and Biochemistry at the University of California, San Diego (UCSD), advised under Prof. J. Andrew McCammon and Prof. Rommie Amaro for four years, before starting her independent career at the University of California, Davis in July 2022. Shirley is interested in developing enhanced sampling methods for molecular dynamics simulations and applying those methods to study important biophysical phenomena. She was selected to participate in the 2018 MIT Rising Stars in Mechanical Engineering Workshop, was awarded the 2021 ACS PHYS Division Young Investigator Award, and was a finalist for the 2021 Chancellor's Outstanding Postdoctoral Scholar Award at UCSD. |
Tae Kim | Tae Kim is a research scientist at the Center for Space Plasma and Aeronomic Research (CSPAR) at the University of Alabama in Huntsville (UAH). Tae completed his PhD study in physics at UAH in 2014 and worked at CSPAR as a postdoc until 2018 before being promoted to the current position. He was an Air Force Office of Scientific Research Young Investigator Program awardee in 2018 for space weather research and received the NASA Group Achievement Award in 2023 for his contribution to the Parker Solar Probe team. His current research interests include developing a novel machine learning ready dataset to improve space weather forecasting, prediction of interplanetary disturbances (and possible auroras) at the outer planets (i.e., Jupiter, Saturn, Uranus, and Neptune), and modeling the solar wind flow throughout the global heliosphere to improve the understanding of the physical processes characterizing the distant heliosphere beyond the solar system. | |
Thai Le | Thai Le is an Assistant Professor of Computer Science at the Indiana University Luddy School of Informatics, Computing, and Engineering. Before joining Indiana University, he was an Assistant Professor at the University of Mississippi and an Applied Scientist at Amazon Alexa. He earned his Ph.D. from the iSchool at Penn State University under the supervision of Prof. Dongwon Lee, receiving an Excellent Research Award and a DAAD Fellowship. Le's research focuses on the trustworthiness of AI/ML, particularly generative AI models such as large language models (LLMs) . His mission is to enhance the robustness, safety, and transparency of AI technologies in various sociotechnical contexts, ensuring that society and internet users can harness their power with confidence and clarity. | |
Ulf Schiller | Ulf Schiller is currently an Associate Professor at the University of Delaware with a joint appointment in Computer and Information Sciences and Materials Science and Engineering. Dr. Schiller has broad expertise in high-performance computing for scientific discovery in materials science, soft matter physics, and computational biomedicine. His research group leverages large-scale simulations and AI/ML to support discovery and design of new materials and processing techniques such as emulsion templating and additive manufacturing of microstructured materials. Dr. Schiller also uses HPC systems as a platform to teach Parallel Computing and is an advocate for reproducibility and best practices in scientific computing. He has served on the ACCESS Researcher Advisory Committee since 2023. | |
Vasiliy Znamenskiy | Vasiliy S. Znamenskiy is an Adjunct Assistant Professor at the City University of New York (Science Department, BMCC; Physics Department, NYC College of Technology). His research spans computational physics and chemistry—molecular dynamics and quantum chemistry of water and biomolecular systems—as well as emerging neuromorphic concepts based on hydrogen-bond networks. An active user and advocate of cyberinfrastructure, he integrates ACCESS resources into coursework such as “Computer Methods in Science,” mentors student projects in high-performance computing (HPC), and develops open educational materials. As a member of the ACCESS Researcher Advisory Committee, he focuses on improving researcher onboarding, HPC-enabled pedagogy, and inclusive pathways for students and educators to adopt advanced CI tools. | |
Vojtech Vlcek | Dr. Vlcek received his PhD in 2016 jointly from The Hebrew University of Jerusalem (Israel) and University of Bayreuth (Germany), where he studied in chemistry and physics departments. His PhD was sponsored by Minerva Fellowship of the Max Planck society. From 2016 till 2018, Dr. Vlcek continued as a postdoctoral researcher at UCLA in the department of Chemistry and Biochemistry. He joined the faculty at UCSB in 2018. | |
Wayne Smith | I've done extensive IT work both in academia and industry. I'm in my fifth decade at California State University, Northridge. I use ACCESS resources for a myriad of data science-related tasks: mostly data engineering workflows, mathematical optimization, and Big Data statstical/ML computing. I mostly use R but use Python (e.g., RAPIDS) and Julia (e.g., JuMP) as needed. Perhaps more important, as a Campus Champion, I assist STEAHM faculty with their HPC applications with ACCESS resources providers as well as with NRP/Nautilus resources. I'll begin my first work directly on a Quantum computer (simulated annealing) next calendar year. | |
Wei Yang |
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Wenbin Zhang | Dr. Wenbin Zhang is an Assistant Professor in the Knight Foundation School of Computing & Information Sciences at Florida International University, and an Associate Member at the Te Ipu o te Mahara Artificial Intelligence Institute. His research investigates the theoretical foundations of machine learning with a focus on societal impact and welfare. In addition, he has worked in a number of application areas, highlighted by work on healthcare, digital forensics, geophysics, energy, transportation, forestry, and finance. He is a recipient of best paper awards/candidates at ECML PKDD'25, FAccT’23, ICDM’23, DAMI, and ICDM’21, as well as the NSF CRII Award and recognition in the AAAI’24 New Faculty Highlights. He also regularly serves on conference organizing committees and journal editorial boards across computer science and interdisciplinary venues, including as Travel Award Chair for AAAI'25, Volunteer Chair for WSDM’24, Associate Editor for ACM Computing Surveys, and Action Editor for Data Mining and Knowledge Discovery. | |
William Lai | William Lai is an Assistant Research Professor in the Department of Molecular Biology and Genetics. He works with the Pugh lab and is interested in principles of gene regulation. Dr. Lai’s research is directed towards understanding the fundamental mechanisms of gene regulation. DNA sequence, local and distal chromatin (protein), and RNA all play both cooperative and antagonistic roles in the decision of when and how often any particular gene is transcribed. Understanding how these biological networks make decisions is the key bottleneck in understanding how perturbations to these systems result in a disease phenotype. The primary methods used to undertake this is through a combination of classic biochemistry, next-generation sequencing assays, and machine-learning computational approaches to approach the eukaryotic genome in a holistic manner. Due to the high-level of conservation amongst eukaryotic organisms, model organisms of interest include yeast, mouse, and human. | |
Youzuo Lin | Youzuo Lin is an associate professor at the School of Data Science and Society after serving more than 12 years as a scientist at the Los Alamos National Laboratory. His areas of research focus on physics-informed machine learning, deep learning, computational methods, and their applications in computational imaging, signal and image analysis. Specifically, he has worked on subsurface imaging for energy exploration, medical imaging and cancer detection and time series classification for small earthquake detection. He holds a Ph.D. in mathematics from Arizona State University. | |
Yunji Zhang | I look at the dynamics and predictability of convectively driven severe weather and associated hazards, and how we can enhance our current capability to accurately predict them and better mitigate them by assimilating readily available, under-utilized observations. My primary research interests involve mesoscale severe convective weather, including what environmental and internal processes contribute to the hazards that they bring on, for how long can we accurately forecast them, and how can we improve our current forecast capabilities. A notable part of my research also focuses on ensemble-based data assimilation (e.g., ensemble Kalman filter) of remote-sensing observations from satellites and radars, especially those that are readily available from current observational platforms but are underutilized by operational global and regional numerical weather prediction models. My research combines high-resolution computer modeling, ensemble data assimilation and forecasting, remote sensing, and mesoscale meteorology. |