Hi, I'm Rohan Cherukuri · machine learning + security
I build ML systems that survive production — probabilistic pricing models serving live FX quotes, NLP pipelines that rewrite screenplays, and forecasts that hold up out-of-sample — with a side of security, because I like knowing how things break.
psst — click anywhere to fire a forward pass · red pulses don't make it through
01 · About
It started with FRC robotics on Team 2338, training neural nets to run on a Raspberry Pi strapped to a robot. That led me deeper into machine learning: teaching 200+ students as a UMN teaching assistant, training DQN autoscalers as a CGI intern, and along the way falling for security — how systems fail, how models get fooled, and what they leak about their data (that Modern Cryptography course stuck with me).
Today I'm a founding quant engineer at Crebit, building probabilistic pricing models that serve live FX quotes — full lifecycle work, from wrangling the data to training and evaluating honestly to shipping to production. Based in Chicago; building solutions to any problem that interests me.
Based in Chicago, IL
Toolbox
02 · Projects
Deep-learning forecasts of crop futures prices from NOAA and USDA climate data — temperature anomalies, precipitation indices, drought severity. An attention-based multi-stream LSTM beat PatchTST baselines: 5.9 vs 5.1 Sharpe over a 2-year out-of-sample period.
A two-stage NLP pipeline that classifies character personality in film & TV scripts and rewrites it. LoRA fine-tuning cut trainable parameters by 90%, enabling Qwen2.5-32B on a single A100 with 4-bit quantization — 0.493 PAS / 0.838 BERTScore on personality transfer.
An MLP + RNN drafting agent for professional League of Legends — trained on webscraped match data, it reaches 70% similarity with professional drafts from Worlds 2025.
The drafting system's next iteration: an agentic RAG layer where an LLM grounded in matchup data explains every pick in plain language. Explainability as a feature, not an afterthought.
03 · Experience
Jun. 2026 — Present
Summers 2024 & 2025
Aug. 2025 — May 2026
Aug. 2023 — May 2026
04 · Field notes
Every few weeks I evaluate a new forecasting model for the crop futures project, and every time I re-learn the same lesson: the interesting bugs are in the backtest, not the model. These are the
Why this site exists, and how to add your own posts in about thirty seconds.
The stack behind this portfolio: an interactive neural-network canvas, hash identicons, markdown posts, and a Next.js static export on GitHub Pages.
05 · Contact
Signal over noise — whether it's ML, quant systems, security, or something at the intersection, I'd love to hear about it. Email is fastest; I usually reply within a day.
public channels