Experience
Feb 2026 - Present
Rockville, MD
Temple Allen Industries
Machine Learning Intern
- Architected reinforcement learning control pipeline in Python and OpenAI Gym to minimize actuator motion variance under external disturbances, reducing positional discrepancy by 38%.
- Evaluated and fine-tuned computer vision detection models for aircraft component recognition using PyTorch and OpenCV, improving classification accuracy by 14% across validation datasets.
- Developed simulation and inference testing framework with NumPy and real-time sensor feedback analysis to benchmark actuator stability and vision model robustness under dynamic operating conditions.
University of Maryland
Computational Number Theory Researcher
- Co-author of 2 accepted ACM SIGACT News open problems and arXiv paper on congruence monoid and Gaussian primes.
- Built custom sieving algorithms and modular filters achieving 3% MAPE and derived 2 prime density formulas validated via nonlinear least-squares regression.
- Optimized Miller-Rabin tests with Numba, cutting per-check latency ~40% on 10⁹+ candidates and verified densities using a Python/NumPy analysis framework.
University of Maryland
Computational Game Theory Researcher
- First author of University of Maryland-accepted paper analyzing player skill and ideal positions in imperfect Nim through 10⁶+ Monte Carlo simulations in Java.
- Designed 4 strategy models with up to 100% accuracy using algorithms for move optimization, win detection, and stochastic modeling.
- Applied NumPy, SciPy, and Matplotlib for data analysis; leveraged virtual CPUs, parallel processing, and Gaussian smoothing to optimize runtime by ~26% and process 10⁹+ 3D points.
Nov 2024 - Present
Washington, DC
The George Washington University
Computational Linguistics Researcher
- First author of manuscript quantifying semantic drift during COVID-19 via 6-trait NLP pipeline on 22.2k Reddit Q&A pairs (2019-2023).
- Implemented GPT-4o few-shot classifier generating 133.3k Likert scores, achieving 0.82 Krippendorff's alpha and 15% higher calibration accuracy using isotonic regression.
- Applied Bayesian change-point detection, PELT, and causal impact forecasting to identify post-2020 linguistic shifts with NumPy and scikit-learn.
Education
Cornell University
Computer Science · 4.0 GPA
Expected graduation: 2029
Courses: OOP I, OOP II, Calculus I, Calculus II, Data Structures & Algorithms
Working in Cornell’s Co MSAIL Lab on using reinforcement learning agents for fluid dynamics.
I’m Rohan Sinha, a computer science student at Cornell University working on machine learning, AI systems, and computational research. My projects span reinforcement learning, distributed systems, and privacy-preserving clinical NLP.
Projects
Adaptive gRPC Compression
Go / gRPC / LinUCB / Contextual Bandits+
- Reduced p95 RPC latency 61.7% across 161K calls by training LinUCB to select gzip/zstd from runtime context.
- Saved 863.7M payload bytes (56.7%) across 161K RPCs by adapting compression to entropy and CPU load.
- Achieved 1.38 µs decision latency by embedding bounded LinUCB inference in Go and streaming gRPC interceptors.
View on GitHub↗ML CI Test Conflict Detection Scheduler
Rust / eBPF / Python / Go / Postgres+
- Instrumented 280 pytest cases for CI conflicts by tracing files, sockets, ports, DBs, and processes with Rust eBPF.
- Scheduled CI across 8 workers with 3 risk policies using conflict probability, overlap duration, and LPT placement.
- Built a Rust eBPF/Python/Go/Postgres pipeline to trace 280 tests, predict conflicts, and schedule workers.
View on GitHub↗GroundSense
React / TypeScript / Supabase / Deno / Gemini+
- Architected React/TypeScript + Supabase/Postgres platform with RLS, Edge Functions, and a source-audit ledger.
- Built Deno ETL normalizing 2K+ BLS/EIA/FRED/UN records with Gemini-assisted claim extraction pipelines.
- Mapped external shocks to calibrated exposure scores and mitigation measures across 5+ supply-chain workflows.
View on GitHub↗Federated Learning for Clinical NLP
PyTorch / Flower / Opacus / ClinicalBERT+
- Built PyTorch + Flower (FedAvg) simulation across hospital nodes over 50-100 rounds; applied Opacus differential privacy (ε 1.5-3.0) and secured via TLS 1.3, AES-256, and JWT auth.
- Trained ClinicalBERT/mBERT (~110M params); reached 80%+ F1 on holdout with under 15% communication overhead vs centralized baseline, robust to client dropout and label noise.
View on GitHub↗More projectsFewer projects+
Multi-Agent RL for Energy Distribution
Ray RLlib / PyTorch / Gymnasium+
- Developed multi-agent PPO system with a custom 2-3 home + 1 battery environment and peak/off-peak pricing; ran ~1e6 env steps with 8-16 rollout workers and AMP fp16.
- Delivered 15-20% cost reduction vs baseline across 100 eval episodes with under 1% reward variance; resilient under 2x demand surges at ~25k env-steps/s throughput.
View on GitHub↗Cross-Lingual Medical NLP
Transformers / LoRA / Gradio+
- Built a clinical NLP transfer framework using Hugging Face Transformers, PyTorch, LoRA, and Gradio.
- Fine-tuned mBERT on 10k+ English medical NER samples and adapted it to Spanish with 200 labeled examples for low-resource transfer.
View on GitHub↗Skills
Languages
- Python
- Java
- C
- C++
- JavaScript
- TypeScript
- SQL
- HTML/CSS
- R
- Go
ML / AI
- PyTorch
- scikit-learn
- Hugging Face
- OpenCV
- Gymnasium
- Stable-Baselines3
- Ray RLlib
- MLflow
- Opacus
Tools & methods
- NumPy
- pandas
- SciPy
- Jenkins
- Maven
- Git
- Linux
- Postgres
- Deno
- Vue.js
- Agile