Islamabad, Pakistan
Two IEEE publications on cooperative multi-agent RL for wireless systems. Mitacs Globalink researcher at McMaster University (2025), advised by Dr. Istvan David, on integrating human advisory signals into PPO via subjective logic. Open to research-focused Masters opportunities, available to start any upcoming term.
01 / Research
I am looking for research-focused Masters opportunities in machine learning, available to start any upcoming term. My focus is reinforcement learning under realistic constraints: partial observability, multi-agent coordination, and learning from limited or noisy human feedback.
Cooperative and competitive policy learning under partial observability. Two IEEE publications on decentralized MARL for CR-NOMA wireless systems.
Integrating advisory signals from humans into on-policy training. Mitacs Globalink work with Dr. Istvan David at McMaster on subjective-logic belief modeling layered onto PPO.
Sample-efficient continuous-action policies for transmit power control, spectrum access, and energy harvesting under stochastic fading. Benchmarks on DDPG, TD3, PPO.
Bridging classical RL with language-model post-training. Industry exposure to retrieval, tool use, and multi-agent orchestration informs research questions on alignment and reward modeling.
02 / Background
I graduated from NUST in 2025 with a B.E. in software engineering and a 3.61 / 4.00 CGPA. My research track started in my third year at the Information Processing and Transmission Lab under Prof. Dr. Syed Ali Hassan, where I co-authored two IEEE papers on multi-agent DRL for wireless systems.
In summer 2025 I was a fully funded Mitacs Globalink research intern at McMaster University with Dr. Istvan David at the SSM Lab. I worked on guided policy optimization: integrating human advisory signals into PPO via subjective logic belief modeling on Gymnasium PacMan, with measurable convergence gains over baseline PPO.
Alongside research, I work as an AI engineer at Adept Tech Solutions on voice and email agents. This pays the bills and keeps me close to production LLM systems, which is informing my interest in RLHF and reward modeling research.
03 / Peer reviewed
Saleha Ahmed, Muhammad Uzair, Syed Asad Ullah, et al.
IEEE Internet of Things Journal · 2025
A cooperative multi agent DRL framework for CR-NOMA IoT, where distributed agents jointly learn spectrum access and power control policies under partial observability.
Saleha Ahmed, Muhammad Uzair, Syed Asad Ullah, et al.
IEEE International Conference on Communications (ICC) · 2025
DRL driven transmit power control for energy harvesting uplink nodes, evaluated against MRC, SC, and EGC diversity combining schemes under Rayleigh fading.
04 / Selected work
A REINFORCE policy-gradient agent on ALE Pacman with human advisory signals fused into the policy via subjective-logic belief modeling. Achieves measurable convergence speedup over baseline PPO.
Implementation backing two IEEE publications on cooperative MARL for wireless powered networks. From-scratch MADDPG, MATD3, MASAC, and MAPPO over a CR-NOMA environment with energy harvesting and three diversity-combining receiver variants (SC, MRC, EGC).
Proximal Policy Optimization on the MuJoCo inverted pendulum with a hand-shaped reward and Optuna-driven hyperparameter search. Groundwork for my Mitacs research on guided policy optimization.
Comparative study of single-device vs multi-GPU training for a learning-to-rank DNN on the ANTIQUE QA dataset, built on TensorFlow Ranking. Same ranking quality across both strategies, with a discussion of when MirroredStrategy actually buys you speed.
End-to-end IoT and ML pipeline built around a custom dataset gathered from ESP32 sensors deployed across campus. 75% AQI regression accuracy on held-out days.
Domain-specific LLM assistant for banking queries on LLaMA 3.2 3B Instruct with LoRA fine-tuning, FAISS retrieval, and live document ingestion. Testing how far a small open-weights model can go on a narrow domain when retrieval is well tuned.
05 / Timeline
Jun 2025 to Aug 2025
Hamilton, ON, Canada
Advised by Dr. Istvan David · SSM Lab
Jun 2024 to Sep 2025
Islamabad, PK
Advised by Prof. Dr. Syed Ali Hassan
Nov 2025 to Present
Islamabad, PK
06 / Academic
Nov 2021 to Jun 2025
Islamabad, PK
Relevant coursework
07 / Get in touch
available
Open to research-focused Masters opportunities in machine learning, available to start any upcoming term (Winter, Spring, or Fall 2026 / 2027). My research focus is reinforcement learning, multi-agent systems, and learning from human feedback.
If you are a professor or graduate admissions reviewer, email is the fastest way to reach me and I respond within a day. My CV is linked below.