Abdul Samad Zaheer Khan

MS Computer Engineering, New York University · New York, NY
ak9943@nyu.edu · github.com/abdulllkhan · linkedin.com/in/abdulsamadzkhan · Full portfolio

Research interests: quantum machine learning and hybrid quantum–classical algorithms; multi-agent AI systems; applied machine learning in medical imaging and finance.

Education

New York University — MS, Computer Engineering
2023 – 2025

GPA 3.80 / 4.00. Coursework: Quantum Computing, Machine Learning, Deep Learning, Computer System Architecture, Network Security, Mathematics, Physics, Finance.

The National Institute of Engineering, Mysuru — BE, Computer Science
2017 – 2021

GPA 9.00 / 10.00 (3.78 / 4.00). Coursework: Advanced Mathematics & Statistics, Advanced Algorithms, Parallel Programming, Formal Language & Automata Theory, Computer Networks.

Research Experience

Research Intern, Center for Quantum Information Physics, NYU
JAN – MAY 2025

Papers & Technical Writing

Coin-Flip Pricing in a Tournament-Winner Market: A Paired-Contract Trade on the 2026 IPL Champion
2026

Independent writing. Bayesian analysis of a mispriced tournament-winner market: coin-flip pricing (0.75 combined) against a 93.3% base rate for a top-two seed, exploited via a paired position returning ~27.7%.

Read the paper (PDF)

TicTacPro: Exactly Solving a Combinatorial Piece-Placement Game and Stress-Testing Deep Q-Learning Against It
2026

Independent writing. An exhaustive alpha-beta solver proves TicTacPro is a first-player win from all 27 openings — refuting the opposite conclusion reached by time-limited minimax self-play — and a Dueling Double DQN (792K parameters) trained with a curriculum of rule-based opponents reaches 100% against random and bullseye opponents, with pipeline pitfalls reported as negative results.

Read the paper (PDF)

Selected Projects

TicTacPro RL — a Dueling Double DQN trained with a curriculum of rule-based opponents, paired with an exact alpha-beta solve of the game. PyTorch, DQN, Alpha-Beta.

Multi-Step Tool Attacks — a Kaggle red-teaming entry against tool-using LLM agents (gpt-oss, gemma). Python, llama.cpp, LLM red-teaming.

Hybrid Quantum–Classical Neural Network — six-year lung-cancer risk estimation from a single low-dose CT scan. Qiskit, PyTorch.

Stock Direction Prediction — fine-tuned FinBERT and LLMs feeding a Random Forest to forecast GameStop’s price direction. FinBERT, Llama, Random Forest.

QubitQuery — retrieval-augmented assistant over lecture notes, built to make office hours more productive. LangChain, FAISS, OpenAI.

chromeControl — MCP-compliant Chrome sidebar that answers questions about the current page. TypeScript, React, MCP.

Squaris — procedurally generated polycube packing puzzles over a single generation kernel (2D tiling, 3D lattice, Tetris-style). React, TypeScript, Three.js.

Industry Experience

Founding Engineer, Starboard
OCT 2025 – PRESENT

Applied research in multi-agent systems: agents with tool use that autonomously process shipment tracking and reconcile data across logistics platforms; fine-tuned open-source LLMs for document parsing.

Software Development Intern, Tiny Archives
SEPT – DEC 2024

Backend archival systems for organizations and individuals, with a focus on scalability (Python, Django, PostgreSQL).

Software Development Engineer I, Finflux
NOV 2022 – JULY 2023

Built ELMS, an exposure and limit-management engine covering 35M+ customers.

Hackathons & Competitions

Activities

Represented NYU in contract bridge (North American Bridge Championships, Philadelphia, 2025) and in poker at the Intercollegiate Poker Association annual tournament, 2025. Member, SASE and IEEE.