Skip to content
View Ameya-bit's full-sized avatar

Highlights

  • Pro

Organizations

@saark-web

Block or report Ameya-bit

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Ameya-bit/README.md

Ameya Panchal

Undergrad at Penn State — CS, Physics, AI, Schreyer Honors '28.
Working on mechanistic interpretability: reverse-engineering what language models compute, and why.

Writeups live at ameya-bit.github.io.



Currently


Building Anthropic's Jacobian lens from scratch — the method from Verbalizable Representations Form a Global Workspace in Language Models (Gurnee et al., 2026) — in raw PyTorch + HuggingFace, validated against finite differences and the logit-lens identity before any reference code is diffed. Reference implementations exist; the point is owning the mechanism, because the code becomes the probe for what comes next.

jacobian-lens-from-scratch · in progress, built in the open




Interpretability


Every Method Has a Blind Spot: Reading GPT-2's IOI Circuit Three Ways
Jul 2026

Direct logit attribution finds the name-mover heads, activation patching finds what feeds them, path patching finds the wire between — and each method is blind to exactly what the next one reveals. A replication of Wang et al. framed as a comparison of what the three techniques can and can't see, with DLA, activation patching, and path patching hand-implemented before reaching for library helpers.

Code



An Induction Head in Disguise: Chasing Grammar in a Character-Level Transformer
Jul 2026

Trained a 6-block character-level transformer, isolated a copying head (B5H0) via OV-circuit eigenvalues and copying scores, and killed two of my own hypotheses — quotation and parenthesis grammar — with targeted QK attention-pattern controls. The result: the OV circuit encodes bracket completion while the QK circuit stays blind to bracket structure. A half-built mechanism the model never learned to route.

Code




Physics research


Monte Carlo Radiative Transfer — Neutron-Star Pulse Profiles
Penn State Multi-Campus REU · advised by Prof. Asif ud-Doula · Oct 2025 – present

A two-stage pipeline — a Monte Carlo scattering atmosphere feeding a general-relativistic pulse-profile model with Schwarzschild light-bending and Doppler effects — built to quantify the systematic error introduced by the isotropic-emission assumption in neutron-star mass–radius measurements. Validated against Chandrasekhar's exact H-function (reduced χ² = 0.70) and published reference waveforms (0.11% peak error). First-author paper in preparation.

Code · Project writeup




Also


CanvAI — semantic retrieval over Canvas LMS content; HuggingFace embeddings indexed in FAISS. PSU Hackathon, 2025.


Web vulnerabilities study — seven common vulnerability classes, with defensive implementations across Rust, Python, PowerShell, and PL/pgSQL.


Application Specialist (part-time) — Penn State Office of the Physical Plant, with the Nittany AI Advance.




Stack


Python · PyTorch · HuggingFace Transformers · TransformerLens · NumPy · scikit-learn · Git

Secondary: Java · JavaScript / React · SQL · Flask




Website · LinkedIn · X · Email

Pinned Loading

  1. QuotesByNiche QuotesByNiche Public

    Not quite quotes by Nietzsche, but a language transformer tries their best

    Jupyter Notebook 1

  2. IOI IOI Public

    Learning Direct Logit Attribution, Activation Patching, Path Patching

    Jupyter Notebook

  3. ML-Bootcamp ML-Bootcamp Public

    Jupyter Notebook

  4. vulnerabilties_study vulnerabilties_study Public

    Rust

  5. mc-radiative-transfer mc-radiative-transfer Public

    Python

  6. OBress/CanvAI OBress/CanvAI Public

    PSU Hackathon Fall 2025

    Python