Samuel C. Hoover
Chemical engineering Ph.D., PPG Fellow, polymer physicist, and computational modeler.
Projects
CV | Resume
About Me
Programmer by choice, chemical engineer by compulsion (I’m joking, I’m joking!).
I am actively looking for full-time positions! Open to relocation, including Canada and the EU.
I am a PPG Fellow and Chemical Engineering Ph.D. from UMass Amherst. In the Muthukumar Group, I studied the phase behavior of complex polymer systems using theory, simulation, and machine learning to investigate the fundamental physics driving aberrant aggregations like cataracts and those implicated in neurodegenerative diseases. My dissertation is entitled ‘‘Study of Charged Macromolecule Phase Behavior using Conventional and Modern Modeling Methods’’.
Outside of the lab, my hobbies include cooking and baking (especially when it is for my girlfriend), studying computer science, data science, and molecular/structural biology, reading Cold War and modern era (post-WWII) history, and hanging out with my cats Leo, Lou Lou, and Ariel.
You can find more about my ongoing and completed projects by visiting my projects page.
Education
Ph.D., Chemical Engineering
B.S., Chemical Engineering
Minors in Mathematics and International & Cross-Cultural Perspectives
Selected Research Experience
Prof. M. Muthukumar, University of Massachusetts Amherst
Studying physics underlying aggregation in synthetic and biological systems using
molecular dynamics, explainable machine learning, and numerical analysis
Prof. Peng Bai, University of Massachusetts Amherst
Applied convolutional neural networks to predict material properties of
nanoporous materials
Industrial Experience
Triton Systems, Inc.
Led development of electromagnetic components for a viral detection device for
a DHS SBIR project
SI Group
Implemented PI Asset Framework, conducted root cause analysis on company loss
events, and led group intern project
Publications & ongoing work
Hoover, S. C.; Li, S.-F.; M. Muthukumar. Learning the sequence effects on the microphase separation transition of charged heteropolymers. In preparation.
Hoover, S. C.; Margossian, K. O.; M. Muthukumar. Theory and quantitative assessment of pH-responsive polyzwitterion-polyelectrolyte complexation. Soft Matter 20, 7199-7213 (2024). doi: 10.1039/D4SM00575A.
Liu, Y.; Perez, G.; Cheng, Z.; Sun, A.; Hoover, S. C.; Fan, W.; Maji, S.; Bai, P. ZeoNet: 3D convolutional neural networks for predicting adsorption in nanoporous zeolites. Journal of Materials Chemistry A 11, 17570–17580 (2023). doi: 10.1039/D3TA01911J.
Skills
Python, SQL (SQLite, Postgres), Rust, C/C++, MATLAB, HTML, Bash
PyTorch, scikit-learn, XGBoost, pandas, Polars, NumPy, SciPy, Matplotlib, seaborn
Computer vision, regression, natural language processing, large language models, supervised learning, regression, classification, dimensionality reduction, clustering
GROMACS, OpenMM, LAMMPS, VMD, PyMOL, Schrödinger