Projects

SteamLens

What do Steam reviews actually praise and criticize and how much trust should you place in the answer? SteamLens is an evaluation-first review analysis system planned across four milestones, the first two delivered. It turns unstructured reviews into measured, aspect-level evidence, then builds the product around a labeler whose quality, cost, and failure modes are published.

  1. The Instrument Around the Modelextraction + evaluationThe measuring device before the product: a census labeled for $3.80, and its error measured against human judgment rather than asserted.
  2. Sampling Without Random Accessthe sampling studyHow few reviews a report actually needs: a size rule validated on games it never trained on, with the distance from uniform sampling measured and priced instead of pretended away.
  3. The Deployed Productunder constructionPut the measured pipeline behind a public URL: per-game reports, traceable evidence, budget controls, and an evaluation gate deciding what is allowed to ship.
  4. Interrogating the Reportunder constructionA grounded chat over labeled structure and verbatim evidence, allowing a finished report to be questioned without letting the model invent its statistics.
Code

Blackjack RL

A four-part research arc: a measurement instrument that had to earn trust first, then one question asked three times with the ground truth progressively removed — can learning rediscover optimal play as a table, as a network, and finally as a bet-sizing rule whose signal is buried fifty-deep in per-hand noise?

  1. Monte Carlo Blackjack Simulatorthe instrumentA self-validating engine, checked against published blackjack mathematics — ~80M hands that every later claim is measured against.
  2. The Policy Audittabular controlTabular Monte-Carlo vs. the proven-optimal table: ~93% rediscovered, and the missing part traced to coverage, not method.
  3. From Table to NetworkDQN vs. tableA network repairs the table's coverage gaps — and pays for the smoothness exactly at the policy's sharp boundaries.
  4. Betting Against the NoiseKelly vs. RLThe capstone: the edge is real and measured — and provably too thin, rare, and noise-buried for end-to-end learning to hear.

Learning to Guess the Distance

A learned A* heuristic that looked like a wash — until the pooled average was split and two opposite effects appeared. One regime-tag feature turns it into 17% less search at a 0.2% cost; moved off its training distribution, it fails in two opposite ways. Two axes, never collapsed into one score.

Report (PDF)Code

Steam Review Intelligence

What does a Steam rating actually measure? 298k reviews, 50 games, 30 languages — four findings about when players review, whether they stay, how they write, and who they are, each forced to reproduce game-by-game before being believed. One 42-point "finding" died under that test; that's why the survivors can be trusted.

Report (PDF)Code