Open Positions: Undergraduate and graduate students interested in research opportunities should contact me (ie Scott). For students applying to our PhD program, please choose the interdisciplinary PhD program “Engineering & Applied Science – Computational Science option”. I’m happy to discuss aspects of this program with prospective students.
Student research interests are diverse and include gravitational-wave physics, modeling, numerical analysis, computing, and machine learning. Current students and alumni have come from a variety of departments including mathematics, physics, data science, and mechanical engineering. Our group’s ongoing projects are carried out with an equally diverse set of external collaborators as can be seen from our recent publications. One prominent theme of our work is the development of numerical methods and models for gravitational-wave science, and many collaborations are with members of the LSC, LISA, and the Simulating eXtreme Spacetimes collaboration.
Current Students
- Som Dev Bishoyi (IISER Kolkata). Internship. Alternative theories of gravity.
- Brian Cornet. MSc. Machine learning. Dynamical systems.
- Connor Kenyon. EAS PhD. High-performance computing. Wave phenomena. Computational Relativity.
- Feroz Shaik . MSc. (2019), EAS PhD. Impact of subdominant modes on the interpretation of gravitational-wave signals. Surrogate modeling. Bayesian Inference.
- Manas Vishal EAS PhD. Previously summer internship (IISER Kolkata). Gravitational Waves, Numerical Relativity, Nodal Discontinuous Galerkin Methods, and High-Performance Computing.
Alumni
PhD and masters thesis
- Tousif Islam. PhD 2023. Connecting numerical relativity, perturbation theory, and gravitational wave astrophysics (dissertation). Tousif is currently a KITP Postdoctoral Scholar at the Kavli Institute for Theoretical Physics, University of California, Santa Barbara.
- Tyson George. BS 2022, MSc 2023. Building Numerical Relativity Surrogate Models with Neural Networks (thesis). Tyson is currently in a PhD program (Computational Mathematics & Modeling) at Virginia Tech.
- Katie Rink. MSc 2022. Computationally Efficient Methods for Modelling Binary Black Holes: Intermediate to Extreme Mass-Ratio Limit (thesis). Katie is currently in a PhD program at UT Austin with a Provost’s Fellowship.
- Kevin Gonzalez-Quesada. MSc 2022. Scalar and Gravitational Transient Hair for Near-Extremal Black Holes. Co-advised with Gaurav Khanna (primary advisor). Kevin is currently in a PhD program at Case Western University.
- Dwyer Deighan. 4+1 BSc/MSc, UMassD, 2021. Genetic-algorithm-optimized neural networks for gravitational wave classification (paper). Dwyer is currently in a PhD program at the University of Buffalo.
- Colin Brown. MSc, UMassD, 2021. Reproducible Notebooks: A Study in the Replicability and Reproducibility of Computational Notebooks (thesis). Colin is currently in a PhD program at the Northern Illinois University.
- Nur Rifat. MSc, UMassD, 2019. A Surrogate Model for Gravitational Wave Signals from Comparable- to Large-Mass-Ratio Black Hole Binaries (paper and thesis). Some of Nur’s work has been featured in local news articles. Nur won the Physics Graduate Research (MS) award for outstanding performance. Nur is currently in a PhD program at the University of Virginia.
- Aakash Kardam. MSc, UMassD, 2018. A Comparison of Nodal Discontinuous Galerkin Schemes for Hypersonic Flow Over a Blunt Body (thesis). After graduating Aakash joined Microway Inc as a high-performance computing software engineer, specializing in ML/AI performance assurance.
MSc capstone projects
- Divya Sreenivasan. MSc, UMassD, 2019. Training optimizations for CNN classifiers. After graduating Divya joined Randstad Healthcare working in health analytics.
Undergraduates thesis and honors projects
- Rebecca Rodrigues. BSc, UMassD, 2023. A Python package for near-field-to-far-field algorithms. After graduating Rebecca began her PhD program at RIT in computational mathematics.
- Keigan Cullen. BSc, UMassD, 2023. Neural Ordinary Differential Equations with Applications to Gravitational Wave Modeling.
- Trevor Robertson. BSc, UMassD, 2020. Interpolatory Kernels for the Teleportation of Gravitational Waves to the Far Field. After graduating Trevor began a PhD program at the University of Maine in physics education.
- Kimberly Matsuda. BSc, UMassD, 2019. A Convolution Method for the Teleportation of Gravitational Waves to the Far Field. After graduating
Kimberly began her PhD program at RPI in applied and computational mathematics.
- Derek Marshall. BSc (Honors), UMassD, 2018. Transcription Factors and Feature Reduction Methods to Determine Drug Response in Cancer Cells. After graduating Derek joined CapitalOne’s data analytic divisions in Austin, Texas. He now works at CapitalOne as a Senior Business Analyst.
- Jason Kaye. BSc, Brown University, 2012. The interpolation of gravitational waveforms. Co-advised with Jan Hesthaven. Jason is currently a Flatiron Associate Research Scientist.
- Michael Wagman BSc, Brown University, 2012. Simulating Turduckened Black Holes with a Discontinuous Galerkin Scheme. Co-advised with Jan Hesthaven. Michael is currently an Associate Scientist at Fermilab in the Theoretical Physics group.
MSc, undergraduate, internships, and high school projects
- Ed McClain. Nodal Discontinuous Galerkin Methods. Distributional equations. When not working on DG methods, Ed is busy planning the next Chandra science missions.
- Estuti Shukla (IISER Kolkata; intern Summer 2021). Remnant surrogate models for EMRIs. Estuti is currently in a PhD program at Penn State.
- Sayem Khan. UMassD, 2021. Physics Informed Deep Learning. Sayem is currently in a PhD program at the University of Buffalo.
- Vishal Tiwari. MSc, UMassD, 2020. Vishal’s primary advisor was Bob Fisher. As a secondary project, Vishal helped us assess the performance of convolutional neural networks for gravitational-wave classification. Vishal is currently a PhD student at Georgia Tech.
- Emerson Maccarone. High School. 2019. Scientific computing with Python. Emerson is continuing her studies in physics at Villanova University.
- Devin Viegas. MSc, UMassD, 2018. Simulating Orbital Resonance With a Python-based N-body Code. Devin works for the Seabra Group.
- David Manning. BSc, UMassD, 2018. Poisson disc sampling techniques. Dave is now a Learning Coordinator at Amazon.
- Dominic Gastaldo. MSc, UMassD, 2017. A Pseudospectral Approach to Scalar Collapse. Dominic is now a Software Engineer at Intel.
- Matt Wise. BSc, UMassD, 2017. Convolutional Neural Networks for Gravity Wave Detection. After graduating Matt joined MorphoTrust as a machine learning specialist.
- Sohan Vartak and Jay LeFebvre. BSc, University of Maryland, 2013. Evolution of Rotation Curve Models for NGC 3198.
