Benjamin Berol
01

Hi, I’m Ben.

I’m studying computer science at Georgia Tech, with a minor in physics. I like problems where the two overlap, especially when machine learning can help us understand or build something in the real world.

At Argonne National Laboratory, I work on reinforcement learning for molecular discovery. At Georgia Tech, I benchmark scientific computing tools and program autonomous robots with RoboJackets.

B.S. in Computer Science, Minor in Physics · May 20284.0 GPA

Looking for research and software engineering internships for summer 2027.

02

Research

Reinforcement learning
for molecular discovery

NSF REU Research Intern

I fine-tune a molecular diffusion model to generate metal-organic frameworks that could help with carbon capture and energy storage.

1465%Successful MOF assembly
90%Less assembly runtime

I redesigned how generated candidates are evaluated and parallelized the assembly and evaluation workloads across 72 CPU cores.

Presenting my reinforcement learning research poster at UIUC
Presenting my research at UIUC · Summer 2026
Reinforcement learningPyTorchParallel computing

Scientific computing benchmarks

PURA Scholar & Undergraduate Researcher

I implement and benchmark sparse algorithms such as linear solvers and GCN inference on problems ranging from megabytes to terabytes to find the fastest frameworks.

3,773benchmark problems
Explore the project

I also build Array API–compliant infrastructure, automated data pipelines, and visualizations to compare runtime and coverage across NumPy, PyTorch, SciPy, and PyData Sparse.

Browse the benchmark source ↗
Numerical methodsPythonSparse arrays
03

Engineering

Autonomous RoboWrestling

Software Engineer & Operator

I’m the lead programmer for our 500g and 3kg robots. I write C++ for autonomous strategy and systems integration, and use physics simulations to test robot geometries before we build them.

A match from competition.Open video ↗
Team’s software ↗
C++Autonomous systemsSimulation

ML for physics simulations

Founder & ML Developer · Klaus Startup Challenge

Through the Klaus Startup Challenge, I built Newtonic to explore how machine learning could improve physics simulations. I developed graph neural network and LLM-based tools for performance, scalability, and automated analysis.

Graph neural networksMachine learningScientific computing
04

Off the clock

I play a lot of beach volleyball, like to ski and lift, and am a huge Washington Commanders fan. I’m also always up for poker night or a concert.

With the volleyball friends I met while researching at UIUC
Volleyball at UIUCThe friends I made after lab hours.
Skiing in Park City, Utah
Park CityA few days in the mountains.
My view of Bruno Mars performing live
Bruno MarsEven better live.