13 Rohan Pandey — Research Scientist & ML Engineer
Resume

Research Scientist & ML Engineer

Rohan Pandey

ML, mathematics & computational biology. Building at the intersection of reinforcement learning, cancer research, and systems that scale.

Now

Available for research collaborations
  • Building at DigitalOcean — cloud infrastructure & developer tools
  • Research in RL + symbolic systems (GNNs, PPO, verification)
  • Exploring EEG/NeuroAI visualization and realtime systems
LocationSeattle, WA
TimezoneAmerica/Los_Angeles
CurrentlyBS/MS ACMS @ UW
FocusRL · Systems · Bio/NeuroAI

About

I'm an incoming BS/MS student in Applied & Computational Mathematical Sciences (ACMS) at the University of Washington and a Research Scientist and ML Engineer. I minored in Neural Computation and Engineering, with a focus on AI in neuroscience.

My work spans reinforcement learning for polynomial synthesis (GNNs, PPO), cancer modeling for CAR T-cell therapy, and deep learning and adversarial ML for robust systems. I love building at the intersection of theory and applied systems.

When I'm not in the lab or building rockets, I'm on the tennis court or winning at Monopoly. I'm always up for collaborating and exploring new tech.

Skills & expertise

Reinforcement Learning Graph Neural Networks PPO · MCTS Deep Learning Cancer Research Mathematical Optimization PyTorch · TensorFlow Python · C++ · SQL

Experience

Software Engineer II · DigitalOcean Mar 2026 – Present

Building and scaling cloud infrastructure and developer tools at DigitalOcean.

  • Systems design, reliability, and performance work across production services
  • Developer experience improvements: APIs, tooling, and automation
Research Assistant · Math AI Lab, UW Sep 2025 – Present

Designing a reinforcement learning framework to synthesize efficient arithmetic circuits for polynomials, achieving ~70% success on degree-m polynomials.

  • PPO + GNNs with curriculum learning and symbolic verification; scaling to higher-degree synthesis with Monte Carlo Tree Search to improve sample efficiency
  • Preparing open-source benchmarks and targeting submission to ICLR/ICML/NeurIPS
ML Engineer · Mercor Dec 2025 – Mar 2026

Built and deployed an end-to-end ML pipeline for large-scale text sentiment analysis, enhancing prediction accuracy through strategic model selection.

  • Fine-tuned and evaluated transformer models on domain-specific data using custom scoring metrics
  • Owned data preprocessing, model validation, and inference automation for production-ready workflows
Cloud & Digital SAP Intern · PwC Jun – Aug 2025

Engineered high-performance Python data pipelines leveraging vectorization and parallel I/O to reduce latency; built a secure self-service web app for automated workflow configuration and monitoring.

Data Scientist Intern · Fred Hutch Aug 2024 – Jan 2026

Developed mathematical models of CAR T-cell and tumor interactions using systems of ODEs trained on patient-derived B-ALL data, applying regression and loss optimization to evaluate treatment efficacy.

ML Intern · Naval Surface Warfare Center Oct – Dec 2024

Built a reinforcement learning framework with DDPG agents in MATLAB and Simulink, optimizing aerodynamic performance on axial turbomachinery simulations under complex physical dynamics.

ML Intern · MINDCO LABS Sep – Dec 2024

Engineered a real-time eye-tracking system integrating EEG headset signals with deep learning to decode gaze to text, contributing to brain-computer interface (BCI) research.

Project Manager Intern · NASA L'SPACE May – Aug 2024

Lucy & Artemis; led team of 11 on lunar ice mapping rover; PDR, budget, programmatics.

Lead Engineer · SARP Oct 2022 – Jun 2024

ARES: GPS-guided recovery, drogue logic, telemetry in C++/Python.

Mission Control

Pilot the rocket through the asteroid fields.

Contact

Collaborate or say hi.