Apoorva Sinha — Engineer, AI/ML, Quantum Computing

Apoorva
Sinha

Computer scientist, trained first in physics and silicon. From analog chips at Texas Instruments to quantum error correction at Georgia Tech — engineering systems that work at every level of the stack.

AI / ML Quantum Computing Distributed Systems Embedded & Analog

A note from Apoorva

I began in circuits — the kind of engineering where every decision is measured in millivolts and nanoseconds. Eight years later I am writing belief-propagation decoders for quantum codes and distributed key-value stores in C++.

The common thread isn't the tool. It's the instinct to go all the way down — to understand a system at the level that lets you fix it. I'm looking for a team that builds hard, useful things, and treats rigor as a feature.

A life, in years

2013

Enters IIT Kharagpur

Admitted to the five-year Dual Degree program in Electrical Engineering & Control Systems. Studies Electromagnetics by day, reads cosmology at night.

2016

First taste of silicon

Summer intern at Texas Instruments, Bangalore. Writes a jitter-measurement suite for high-speed data links — C++, Python, MATLAB, all talking to lab instruments over GPIB.

2017

A detour into String Theory

MITACS Fellow at the University of Winnipeg. Simulates the thermodynamic evolution of string distributions via numerical Boltzmann transport equations. Discovers he likes writing the solver more than deriving the equations.

2018

Dual Degree, IIT Kharagpur

Graduates with a B.Tech + M.Tech, CGPA 8.75 / 10. Joins Texas Instruments as an analog engineer the same summer.

2018 — 2021

Analog engineer, Texas Instruments

Ships twelve device families — isolated LVDS, CAN, RS-485 and USB chips. Designs the RF blocks for USB 2.0 isolation. Cuts HW/RTL–software co-development cycles by 6×. Learns to trust measurements over intuition.

2023

A deliberate pivot

Leaves industry to begin an MS in Computer Science at Georgia Tech — not to escape hardware, but to scale his engineering to the problems software can reach.

2024

Back to the frontier — this time, quantum

Joins Georgia Tech's quantum computing lab. Designs defect-tolerance strategies for IBM's Gross code [[144, 12, 12]]. Teaches Intro to Quantum Computing to 120+ graduate students.

2025

4.0 GPA · Looking for the next hard problem

Graduating May 2025. Open to software and ML engineering roles where the work is load-bearing.

Selected work

Quantum · Research

Defect-tolerant QLDPC codes

Repairs broken X/Z syndrome checks on IBM's Gross code [[144, 12, 12]] via a super-check construction. Tolerates up to two simultaneous qubit or check failures. Modified BP-OSD decoder in Python & C.

Distributed Systems

GT Store

A distributed key-value store with consistent hashing, gRPC, configurable replication and predecessor-takeover failure recovery. Strong write, eventual read consistency under node churn.

Machine Learning

Bus bunching, solved in real time

Reinforcement-learning agent trained on NYC & Atlanta transit traces. 92 % precision early-warning system via ensemble models, integrated with a live Express.js dashboard.

Physics-informed ML

Battery management via PINN

Hybrid physics–data RNN for State-of-Charge estimation on NASA 18650 cells. Worst-case 1.1 % SOC error, 7.8 % drift over 20 h, 70 % faster calibration via frozen-MLP staging.