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Presented by National Science Foundation (NSF) Mathematical Sciences Graduate Internship (MSGI) Program. NSF MSGI is funded by the Division of Mathematical Sciences.

Welcome to the 2023 NSF MSGI Summer Research Symposium

The 2023 Symposium was held August 22nd - 23rd, 2023

This unique two-day virtual event showcased the research and learning experiences of 2023 MSGI doctoral student interns spending their summer at Department of Energy (DOE) and other federal national laboratories across the country. Presentations highlighted the diverse areas of applied mathematics, pure mathematics, and statistics.

Scheduled topics included research-focused traditional style presentations. This event also featured two panel discussions involving current mentors and former MSGI interns.

Highlights of the event:

  • NSF Welcome, An overview of the NSF MSGI program and its initiative to strengthen the next generation of mathematical scientists by applying advanced mathematical and statistical techniques to “real world” problems.
  • Mentor Panel, Distinguished panelists from national laboratories will highlight the role of mathematics and statistics graduate education in preparing students for careers in science and industry, and the distinctive contribution of the MSGI internship.
  • Alumni Panel, Former participants will share how the NSF-MSGI program has impacted their career development.
  • Presentations, Current participants will present the results of their research for the Division of Mathematical Sciences.


All times are in Eastern Daylight Time 




Dr. Tim Hodges, Program Officer, Algebra and Number Theory Program, National Science Foundation

  • Program Responsibilities include:

    • Algebra and Number Theory
    • Secure and Trustworthy Cyberspace
    • NSF Mathematical Sciences Graduate Internship

    Dr. Hodges is Professor Emeritus of Mathematics at the University of Cincinnati. He is currently on a temporary assignment as an NSF Program Officer in the Algebra and Number Theory Program. His areas of research interest include noncommutative algebra and geometry, quantum symmetry and cryptography.



Dr. Jeremy Tyson, Program Director, Division of Mathematical Sciences, National Science Foundation

  • Program Responsibilities include:

    • Analysis
    • Division of Mathematical Sciences International Collaborations
    • NSF Mathematical Sciences Graduate Internship (MSGI, INTERN)
    • Quantum Information Science and Engineering Working Group

    Dr. Tyson is a Professor of Mathematics at the University of Illinois at Urbana-Champaign. Dr. Tyson is currently on a temporary assignment as an NSF Program Officer in the Analysis Program. His areas of research interest include analysis in metric spaces, geometric mapping theory, geometric measure theory, fractal geometry, and sub-Riemannian geometry. Dr. Tyson is particularly interested in notions of first-order differential calculus and differential geometry in metric measure spaces lacking any a priori Euclidean or Riemannian structure.


Dr. Swatee Naik, Program Director, Division of Mathematical Sciences, National Science Foundation

  • Program Responsibilities include:

    • Conferences and Workshops in the Mathematical Sciences
    • Focused Research Groups in Mathematical Sciences
    • Geometric Analysis
    • Mathematical Sciences Graduate Internship
    • Mathematical Sciences Postdoctoral Fellowships
    • MPS-Ascend Postdoctoral Fellowships
    • Research Training Groups
    • Topology

    Dr. Naik’s research interests are in low dimensional topology. She is a permanent program officer at NSF in the disciplinary programs Topology and Geometric Analysis. Her experience at NSF has included management teams for the Graduate Research Fellowships, NSF Research Traineeships, Research Experience for Undergraduates, Research Training Groups, and Mathematical Science Infrastructure program. Dr. Naik is also an Emeritus Professor at the University of Nevada, Reno.



Dr. Sushant Mehan, Assistant Professor of Water Resources Engineering in the Department of Agricultural and Biosystems Engineering at South Dakota State University

  • Sushant Mehan earned his bachelor’s degree (2011) and master’s degree (2014) in agricultural engineering from Punjab Agricultural University, India. At Purdue University in 2018, he earned a Ph.D. in agricultural and biological engineering, and he currently is an Assistant Professor of Water Resources Engineering in the Department of Agricultural and Biosystems Engineering at South Dakota State University, Brookings, SD. His research plan entails advancing the field of water resources management through geospatial analysis, hydrologic modeling, remote sensing products, wireless sensor networks, data analytics, integrated watershed modeling, and the development of decision support systems. He has published 19 peer-reviewed journal articles and four book chapters and received an international patent for a soy-based filtration system. He was named Early Career Engineer of the Year in 2022 by the Association of Agricultural, Biological, and Food Engineers of Indian Origin. Promoting Diversity, Equity, Inclusion, and Belonging is fundamental to Mehan’s personal and professional philosophy.



Dr. Ahmed Zamzam, Senior Research Scientist at the National Renewable Energy Laboratory(NREL)

  • Dr. Ahmed Zamzam is a senior research scientist at the National Renewable Energy Laboratory, where he has been part of the energy systems control and optimization group since 2019. Before that, he obtained his Ph.D. in electrical engineering from the university of Minnesota. He has obtained his MSc and BSc from Nile University and Cairo University in 2015 and 2013, respectively. His research interests span machine learning and optimization from managing distributed energy resources in the energy systems, tensor decompositions, and data-driven protection and control of power systems.


Dr. Benjamin Lienhard, SNSF Postdoctoral Research Fellow at Princeton University

  • Dr. Benjamin Lienhard is an SNSF postdoctoral research fellow at Princeton University, where he focuses on efficient quantum processor calibration and control. He received his PhD from the Electrical Engineering and Computer Science Department at MIT and an MS and BS from the Department of Information Technology and Electrical Engineering at ETH Zurich. While at MIT, Ben worked on logical qubits using solid-state quantum emitters and readout and control of superconducting qubits. He was an executive member of MIT's Interdisciplinary Quantum Information Science and Engineering program and part of the graduate student advisory group to MIT's dean of engineering.


Dr. John Lu, Mathematical Statistician at National Institute of Standards and Technology (NIST)

  • Dr. John Lu is a mathematical statistician at National Institute of Standards and Technology (NIST), where he collaborates with scientists, developing innovative statistical solutions to physical and chemical measurement problems, including statistical methods for imaging and spectral-type data. His interdisciplinary research interests in the past have carried over from chaos in physics to numerical weather prediction, and from time series to hydrology runoff prediction. In recent years he mostly worked on statistical issues related to standard developments in medical imaging including CT and optical imaging. He is also getting interested in some challenging inferential issues facing data sciences and AI, and forensic sciences.


Mentor Panel


Dr. Emily Casleton, Deputy Group Leader of the Statistical Sciences Group, Los Alamos National Laboratory

  • Emily Casleton is currently the deputy group leader of the statistical sciences group, but was recruited to LANL as a summer student at the 2012 Conference on Data Analysis (CoDA). She joined the Lab as a post doc in 2014 after earning her PhD in Statistics from Iowa State University. Since converting to staff in 2015, Emily has routinely collaborated with seismologists, nuclear engineers, physicists, geologists, chemists, and computer scientists on a wide variety of cool data-driven projects. Most recently, she has been the PI of a data analytics project under the NA-22 venture MINOS; co-organizer of the invited CCS-6 seminar series; and co-chair of CoDA, the conference that brought her here a decade ago.


Dr. Bri-Mathias Hodge, Associate Professor, Department of Electrical, Computer and Energy Engineering and an Associate Director and Fellow of the Renewable and Sustainable Energy Institute (RASEI) at the University of Colorado Boulder

  • Bri-Mathias Hodge is an Associate Professor in the Department of Electrical, Computer and Energy Engineering and an Associate Director and Fellow of the Renewable and Sustainable Energy Institute (RASEI) at the University of Colorado Boulder. He is also a Chief Scientist and a Distinguished Member of the Research Staff in the Power Systems Design & Planning Group at the National Renewable Energy Laboratory (NREL). His research focuses on the modeling and simulation of power and energy systems, with an emphasis on the operational and planning challenges posed by the integration of renewable energy sources, such as wind and solar power. He is an author on over 100 journal articles in this area and has received five best paper awards at the IEEE Power & Energy Society General Meeting. At NREL he has received Outstanding Mentor Awards on five occasions, the NREL President’s Award in 2016, the NREL Outstanding Performance Award and Director's Publication Impact Award in 2019, and the NREL Chairman's Award in 2020. Dr. Hodge also received a Fulbright Fellowship in 2016 for a sabbatical at VTT in Finland.


Dr. Gabriel Perdue, Quantum Simulation for Physics, Fermi National Accelerator Laboratory

  • Gabriel Perdue received a PhD in physics from the University of Chicago in 2008, studying matter-antimatter asymmetries in rate neutral meson decays. He subsequently worked as a Postdoctoral Fellow at the University of Rochester on MINERvA, working to measure neutrino cross sections. He joined Fermilab in 2013 to continue work on neutrino cross sections at MINERvA and as part of the GENIE event generator collaboration. He subsequently shifted into applied machine learning and from there into quantum computing. Today he works primarily in quantum simulation for physics and on the application of machine learning to the control and optimization of quantum computers.


Dr. Panos Stinis, Lead, Computational Mathematics Group, Pacific Northwest National Laboratory

  • Panos Stinis specializes in scientific computing with application interests in model reduction of complex systems, multiscale modeling, uncertainty quantification, and machine learning. Stinis studied aeronautical engineering at the Technical University of Athens, Greece. He earned his PhD in applied mathematics in 2003, from Columbia University in New York, in the area of model reduction. He began his career at Lawrence Berkeley National Laboratory and the Stanford Center for Turbulence Research, where he worked on applying model reduction methods to hyperbolic systems and in developing techniques for locating and tracking singularities of partial differential equations. In 2008, he became a faculty member at the Mathematics Department at the University of Minnesota, where he worked on renormalization, mesh refinement, particle filtering and optimization. He moved to PNNL in 2014, where he is currently leading the Computational Mathematics group. He serves as the co-director of the Physics-Informed Learning Machines (PhILMs) multi-institution collaboration and leads the Digital Twin Component Development thrust of the Energy Storing Materials Initiative.

Alumni Panel


Dr. Kristine Gierz

  • Kristine Gierz completed her undergraduate education at the University of California, Los Angeles as a Biology major and was inspired by an environmental conservation internship in Fiji to pursue graduate studies in Biostatistics. She participated in the National Science Foundation’s Mathematical Sciences Graduate Internship in the summer of 2018 at the National Institute of Standards and Technology, and went on to be awarded the Department of Defense’s SMART Scholarship for Service program. She completed her PhD in December of 2020 and fulfilled her service at the Secretary of the Air Force’s Studies, Analyses, and Assessments division in the Pentagon, and then returned to NIST as a Mathematical Statistician. She lives in College Park with her husband and three dogs, enjoys all types of outdoor activities (including volunteering at a horse therapy site for special needs children), is a reluctant distance runner, and an extremely amateur ukulele player.


Dr. Anthony Gruber

  • Anthony Gruber is the John von Neumann fellow in computational science at Sandia National Laboratories in Albuquerque, New Mexico, where he develops structure-informed surrogate models of large-scale dynamical systems. He received a Ph.D. in Mathematics from Texas Tech University in 2019, after completing an NSF-MSGI internship at Oak Ridge National Laboratory in 2018.  His research interests are relatively broad, as reflected by publications in subjects ranging from pure and applied mathematics to various areas of computer science, physics, and engineering.


Dr. Ratna Khatri

  • Ratna Khatri is a Research Scientist in the Optical Sciences Division at the U.S. Naval Research Laboratory (NRL), and currently serving as the Vice President of the SIAM Washington-Baltimore Section. She joined NRL as the Jerome and Isabella Karle Distinguished Scholar Fellow in 2021, after getting her PhD in Mathematics from George Mason University in 2020. As a graduate student, she spent two summers at Argonne National Laboratory as an NSF MSGI Fellow in 2017, and Givens Associate Research Intern in 2018. Her area of research is the intersection of PDE-constrained optimization, deep learning, and inverse problems in imaging science.


Dr. Chul Moon

  • Chul Moon is an assistant professor of the Department of Statistics and Data Science at Southern Methodist University. He received his Ph.D. in Statistics from the University of Georgia in 2018. In 2017, he participated in the NSF-MSGI internship at Sandia National Laboratories in Albuquerque, New Mexico.


Dr. Matea Santiago

  • Matea Santiago is a Postdoctoral Research Associate at the University of Arizona. She graduated with her PhD from the University of California, Merced in 2021. Her research focuses on computational fluid dynamics applied to biological organisms.