Mathematics Industrial Immersion Program (IIP)
IIP program provides eligible Mathematics students an opportunity to explore research in interdisciplinary and non-academic settings. The program started in 2016 and has been growing since then.
Students selected by the program get immersed in an environment where they develop skills and gain experience that prepare them for careers in the business, industry and government sectors, as well as academia. They become part of interdisciplinary teams of scientists and complete research projects jointly mentored by GMU faculty and at least one external collaborator.
We are partially supported by the Provost office and collaborate with several research centers on campus.
We are always looking for new joint projects with national labs or industry. If you would like to partner with us, or if you are a student looking for a collaborative project, please start by contacting us.
Program Highlights
November 2020:
IIP student Sayomi Kamimoto got awarded COS Outstanding student award given to only two COS graduating students each term and a prestigious National Research Council Associate Fellowship. The National Academies of Sciences, Engineering, and Medicine’s Fellowships Office has conducted the NRC Research Associateship Programs in cooperation with sponsoring federal laboratories and other research organizations approved for participation since 1954. Through national competitions, the Fellowships Office recommends and makes NRC Research Associateship awards to outstanding postdoctoral and senior scientists and engineers for tenure as guest researchers at participating laboratories.
Sayomi has spent part of her time in the last 2.5 years of her studies collaborating with Ira Schwartz, who is the head of nonlinear dynamics section at plasma physics division of NRL. She has graduated in Fall 2020 with a record number of publications and is starting her NRC postdoctoral research associateship tenure at NRL in January 2021.
IIP Participants and Partners
2022 Participants
- Tracey Oellerich: joint project with CAPMM and NIH. Mentors: Maria Emelianenko (GMU), Lance Liotta (NIH, CAPMM), Maria Pierobon (CAPMM)
- Jessica Masterson: joint project with NIST. Mentors: Daniel Anderson (GMU), A. Kearsley (NIST)
- Long Nguyen: joint project with University of Colorado, Boulder. Mentor: Padhu Seshaiyer (GMU), Maziar Raissi (University of Colorado, Boulder)
- Shraddha Rajpal: joint project with NIST. Mentors: T. Berry (Math, GMU), Zeeshan Ahmed (NIST)
- Alonso Ogueda. Mentor: Padhu Seshaiyer
- Matthew Kearney: joint project with Max Planck Institute for Mathematics in the Sciences. Mentors: Benjamin Schweinhart (Math, GMU), Erika Roldan (Max Planck Institute for Mathematics in the Sciences)
- Aleyah Dawkins:joint project with West Point Military Academy. Mentors: Geir Agnarsson (Math, GMU), Elie Alhajjar (West Point Military Academy and Army Cyber Institute)
2021 Participants
- Jessica Masterson: joint project with NIST. Mentors: Daniel Anderson (GMU), A. Kearsley (NIST)
- Cigole Thomas: joint project with NRL. Mentors: Sean Lawton (GMU), Jeff Byers (NRL)
- Tracey Oellerich: joint project with CAPMM and NIH. Mentors: Maria Emelianenko (GMU), Lance Liotta (NIH, CAPMM), Maria Pierobon (CAPMM)
- Long Nguyen: joint project with University of Colorado, Boulder. Mentor: Padhu Seshaiyer (GMU), Maziar Raissi (University of Colorado, Boulder)
- Quincy Frias: join project with NIH. Mentor: Gregoire Altan-Bonnet (NIH)
- Don Brusaferro: joint project with BancLab. Mentors: Igor Griva (GMU), Michael Libman (BancLab)
- Savannah Crawford: joint project with BancLab. Mentors: Igor Griva (GMU), Michael Libman (BancLab)
- Michael Merkle: joint project with West Point Military Academy. Mentor: Elie Alhajjar (West Point Military Academy and Army Cyber Institute)
- Tenzin Zomkyi: joint project with West Point Military Academy. Mentor: Elie Alhajjar (West Point Military Academy and Army Cyber Institute)
- Aleyah Dawkins: joint project with Mosaic ATM. Mentors: Maria Emelianenko (GMU Math), Ming Tian (GMU Physics) and Fred Wieland (Mosaic ATM)
- Vincent Vu: joint project with Mosaic ATM. Mentors: Maria Emelianenko (GMU Math), Ming Tian (GMU Physics) and Fred Wieland (Mosaic ATM)
- Duy Nguyen: joint project with Mosaic ATM. Mentors: Maria Emelianenko (GMU Math), Ming Tian (GMU Physics) and Fred Wieland (Mosaic ATM)
- Patrick Bishop: joint project with Georgia Tech Research Institute. Mentors: Evelyn Sander (GMU Math) and Anne Costolanski (Georgia Tech Research Institute)
2020 Participants
- Sayomi Kamimoto: joint project with NRL. Mentors: Evelyn Sander (GMU), Ira Schwartz (NRL)
- Cigole Thomas: joint project with NRL. Mentors: Sean Lawton (GMU), Jeff Byers (NRL)
- Tracey Oellerich: joint project with CAPMM and NIH. Mentors: Maria Emelianenko (GMU), Lance Liotta (NIH, CAPMM), Maria Pierobon (CAPMM)
- Mahendra Panagoda. Mentors: Tyrus Berry and Harbir Antil
- Long Nguyen: joint project with University of Colorado, Boulder. Mentor: Padhu Seshaiyer (GMU), Maziar Raissi (University of Colorado, Boulder)
Partial List of Past/Present Projects:
- Parameter-dependent dynamics of spatial-temporal systems (NRL)
- Learning varieties from samples (NRL)
- Adaptation in Biological systems (NIH)
- Quantum-inspired algorithms for Hamiltonian simulation (BAH)
- Statistically optimal configurations for cyber-security models (Federal Reserve)
- Density Based Clustering and its Application to Image Segmentation (NIST)
- Stochastic Enumeration with importance sampling (NIST)
- Cluster Identification via a New Distance function on Vertices in Networkoint project with Mosaic ATM. Mentors: M. Emelianenko (GMU Math), Ming Tian (GMU Physics) and Fred Wieland (Mosaic ATM)s (NIST)
- Analyzing and Extending the Discrete-to-Measure Gradient Flow Using Higher Order Voronoi Diagrams (Spaceflight Industries)
- Matrix Completion Problem - Algorithms and Analysis
- Mathematical Models and Simulation of Multiphysics in Enclosed Spaces (U. of Colorado, Boulder)
- Biological Networks: Mathematical Conditions for Adaptation and Beyond
- Algebraic Varieties and Neural Networks (NRL)
- Inferring Dynamics of Biological Systems
- Efficient Physics Informed Computational Methods for solving coupled multi physics problems (U. of Colorado, Boulder)
- Modeling Phase Change of a Pure Material (NIST)
- UMAP: Topological Aspects to Data Science (NIH)
- Classifying Text Through Machine Learning (BancLab)
- Magnitude Functions of Graphs (West Point Military Academy and Army Cyber Institute)
- A Survey on Numerical Semigroup (West Point Military Academy and Army Cyber Institute)
- Quantum algorithms for Unmanned Air Vehicles (UAV) trajectory optimization (Mosaic ATM)
- Modeling Phase Change of a Binary Material (NIST)
- Using Weighted Birkhoff Averages to Differentiate Chaos and Regularity (Georgia Tech Research Institute)
- Efficient Physics Informed Neural Networks coupled with Domain Decomposition Methods for Solving Coupled Multi-Physics Problems (U. of Colorado, Boulder)
- Maker-Breaker Percolation Games (University of Colorado, Boulder)
- The complexity of cyber attacks in layered-security models (West Point Military Academy)
- Data Assimilation for Quantum NV Diamond Spectroscopy (NIST)
Alumni
Elie Alhajjar
Project: Cluster Identification via a New Distance function on Vertices in Networks
Mentors: Jim Lawrence (GMU), Isabel Beichl (NIST), Fern Hunt (NIST)
Graduation: Spring 2017
Placement: Research scientist, Army Cyber Institute
Elie has been supported by the program in 2016-2017. He worked with a group at NIST led by Dr. Hunt and Dr. Beichl, and was advised by Dr. Jim Lawrence at GMU. His project was focused on identifying optimal target sets in network models. He was hired as faculty at West Point academy right after graduation and is also employed as Army Cyber Institute's research scientist.
Alathea Jensen
Project: Stochastic Enumeration with importance sampling
Mentors: Jim Lawrence (GMU), Isabel Beichl (NIST)
Graduation: Spring 2018
Placement: Tenure-track Assistant Professor, Susquehanna University
Alathea was a student of Dr. Lawrence who worked with Isabel Beichl at NIST in 2016-2018. She worked on generalizing the Stochastic Enumeration algorithm and proving its correctness and bounds on variance. She accepted a tenure-track position at Susquehanna University starting Fall 2018.
Ratna Khatri
Project: Inverse Problems with Nonlocal Operators and Classification Problems in Deep Learning
Mentors: Harbir Antil (GMU), Zichao (Wendy) Di (Argonne National Lab)
Graduation: 2020
Placement: Staff Scientist, NRL
Ratna was part of the IIP program in 2018-2020. She worked on deep learning and imaging problems collaborating with colleagues from several national labs. During summer, she worked at Argonne as part of the NSF MSGI graduate internship program. She is a recipient of the prestigious Givens Fellowship and was a runner up for Wilkinson and von Neumann Fellowships. She received several offers from Sandia National Lab and Laurence Livermore National Lab and chose to accept a staff position at Naval Research Lab in 2020.
Patrick O'Neil
Project: Analyzing and Extending the Discrete-to-Measure Gradient Flow Using Higher Order Voronoi Diagrams
Mentors: Tom Wanner (GMU), Spaceflight Industries team
Graduation: 2017
Placement: Lead Data Scientist, Spaceflight Industries
Patrick was supported by the program in 2016-2017, working jointly with Dr. Tom Wanner and a team at Spaceflight Industries, a DC-area based geospatial intelligence company focused on providing low cost satellite imagery. He developed smoothing algorithms and tested them on LiDAR data provided by the company. He graduated in Spring 2017 and assumed a position as Lead Data Scientist at Spaceflight Industries.
Marilyn Vazquez
Project: Density Based Clustering and its Application to Image Segmentation
Mentors: Tim Sauer (GMU), Gunay Dogan (NIST)
Graduation: Summer 2018
Placement: Postdoc at ICERM, Brown University
Marilyn was part of the program in years 2016-2018. She spent one day a week as a guest researcher at NIST, adapting the image segmentation algorithms she developed as part of her dissertation to materials design problems. Her Python codes have been incorporated into NIST-owned widely used OOF package for analyzing materials microstructure. She graduated in Summer 2018 and accepted a postdoctoral researcher position at Brown University's ICERM center, one of the most prestigious applied math research centers in US.
