Ethan Fahimi

Astrophysics & Machine Learning

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Computer science is no more about computers than astronomy is about telescopes

— Edsger Dijkstra

About

I'm a trained researcher in physics, astronomy, and machine learning, with degrees from MIT and The Ohio State University. My passion lies in leveraging patterns within data to drive innovation and deepen our understanding of both the universe and artificial intelligence.

Outside of work, I can likely be found where there are cats, on a run, or speaking about Ohio to anyone who will listen.

Education

The Ohio State University

B.S. Physics & Astronomy, with Honors Distinction
Double Major, Persian Minor
GPA: 3.99/4.00
Summa Cum Laude

Massachusetts Institute of Technology

Master of Business Analytics
Data Science, Deep Learning, Optimization
GPA: 4.9/5.0

Experience

Accenture Research

Data Science Research Specialist
New York, NY | September 2024 – Present
  • Conducting applied ML/AI research, developing scalable, interpretable models for real-world impact
  • Collaborating across global research teams to advance efficient, data-driven solutions for Accenture's innovation initiatives
  • Leading partnership with MIT Analytics Capstone, bridging academic research and industry applications in machine learning and data science

Massachusetts Institute of Technology

Master's Capstone Project with Dr. Ilya Jackson and Lineage, Inc.
Cambridge, MA | February – August 2024
  • Applied SHAP explainability for model interpretation to validate hypotheses on drivers of profitability and energy inefficiencies across 450+ warehouses
  • Predicted customer profitability for 16M+ items using Gradient Boosted Trees and engineered interpretable features
  • Presented at the MIT Analytics Capstone Showcase

The Ohio State University

Undergraduate Research Assistant to Prof. Richard Hughes
Columbus, OH | December 2022 – May 2023
  • Built a scalable pipeline combining SciNCL/BERT embeddings with Leiden/Louvain community detection over 50K+ physics papers to quantify influence and novelty
  • Validated the approach on Higgs-boson discovery literature using Python and high performance computing resources

Louisiana State University

National Science Foundation REU Researcher to Prof. Matthew Penny
Baton Rouge, LA | July – September 2022
  • Conducted 12 nights of remote DECam observations on the Blanco 4m telescope of Omega Centauri via NOIRLab, within the MISHAPS collaboration
  • Extended time-series photometry and transit-detection pipeline in a maintained Python package; identified candidate exoplanets with methods to scale for 60 DECam fields
  • Derived a preliminary upper limit of 0.004 hot Jupiters per star (P = 0.8–3.4 d, 95% CI)

The Ohio State University - GENETIS Collaboration

Undergraduate Research Assistant to Prof. Amy Connolly & Dr. Julie Rolla (NASA JPL)
Columbus, OH | May 2020 – December 2022
  • Developed genetic algorithms (Python/C++) to evolve antenna gain patterns for neutrino detection via Askaryan effect
  • Built a simulation pipeline in Slurm and established upper bounds on detection efficiency in unconstrained geometries
  • Contributions resulted in co-authorship of publications in Physical Review D, ICRC2023, ICRC2021

Publications

Using evolutionary algorithms to design antennas with greater sensitivity to ultra-high energy neutrinos
Rolla, J.; Machtay, A.; Patton, A.; Banzhaf, W.; Connolly, A.; Debolt, R.; Deer, L.; Fahimi, E.; et al. (GENETIS)
Physical Review D 108(10) (2023)
Using genetic algorithms to evolve antenna gain patterns with greater sensitivity to ultra-high energy neutrinos
Reynolds, B.; Rolla, J.A.; Fahimi, E.; Banzhaf, W.; Calderon, D.; Chen, C.C.; Connolly, A.; et al. (GENETIS)
PoS(ICRC2023) 1177 (2023)
Evolving antennas for ultra-high energy neutrino detection
Rolla, J.A.; Arakaki, D.; Clowdus, M.; Connolly, A.; Debolt, R.; Deer, L.; Fahimi, E.; et al. (GENETIS)
PoS(ICRC2021) 1103 (2021)

Contact