Research
Research Experience.
Currently developing os12.com - a passion project research company focusing on AI native layer.
My work focuses on building and improving reinforcement learning systems, efficient computing models, and real-world applications of AI. I am passionate about reinforcement learning, efficient algorithms, and scalable automation, working across AI, robotics, and full-stack development.
Selected research and technical contributions are listed below.
Recursive Transformer Modules (RTMs)
Adi Singh, OS12 Research
Technical Draft. A unifying architecture for adaptive depth, parameter sharing, and auditable reasoning. RTMs invert the fixed-depth paradigm by recursively applying a shared reasoning block to a persistent latent workspace.
Async + Parallel LLM Coding Agents
Adi Singh, OS12 Research
Technical Draft. A framework for asynchronous and parallel execution in LLM coding agents. Investigates parallel speculative generation and dynamic scheduling to reduce latency while preserving solution quality.
Benchmarking Classic and Modern RL Algorithms: REINFORCE, DQN, and Tabular Q-Learning on CartPole-v1
Adi Singh, Jan Christian Meyer
PhD Research Collaboration, Department of Computer Science, In Progress (2025)
AI-Based Matchmaking (CatMatch): A Novel Convolutional Neural Network Approach to Preference Learning
Adi Singh, Cogito NTNU
AI Tinder training algorithm using CNN, Proceedings of the Student Project at Cogito (2023)
Cost-Efficient Treatment Methods for Hydrocephalus: Data Analysis and Optimization
Adi Singh
MIT Biogen Community Lab, Journal of Medical Research & Innovation (2022)
Education.
Master's/PhD Level:
Computer Vision and Deep Learning, Methods in Artificial Intelligence, Advanced Parallel Computing, Network Programming & Security
Bachelor's Level:
Engineering Statistics, Linear Algebra, Procedural & Object-Oriented Programming, Control Theory (1+2)
Awards & Recognition.
Meta Generative AI Hackathon — 4th Place, 2025
Jane Street Estimathon — 1st Place, 2024
Start Code Hackathon — 2nd Place, 2024
TripleTex Hackathon — Finalist, 2024
Building 15,000+ Follower ML Channel — 2024
EECS Representative — 2024-Present
Advanced Math Scholar — Virginia Richmond
High School Representative — 2021