An ML researcher and developer with over 4 years of industry experience in designing and implementing scalable machine learning solutions in Financial & Tech Industries, with a particular enthusiasm for reinforcement learning and verifiable inference. I'm based in Toronto, Canada and You can contact me at [email protected].

Currently, I’m advancing AI product development,Scaling our innovative Verification Pipeline and distributed Inference at Inference Labs, I hold an MSc in CS from McMaster University with my thesis on advancing stochastic optimization leveraging hierarchical reinforcement learning.

• Distributed Proving Framework - Contributed as a core researcher to DSperse - opensource framework for distribued, verifiable inference.
• Quantization and Posttraining - Contributed to an opensource ZK toolkit for quantization and post-training methods.
• Verifiable AI Agent - Developed the first verifiable Doom agent, reducing overhead from 1000x to 8x.
• Modular Proving Framework - Designed a scalable proof-of-inference framework leveraging agentic testing and probabilistic proofs, with no computational overhead, using a JIT design pattern and caching system.
• DPO-Based Ranking - Implemented ranking profiles using Reinforcement Learning benchmarking DPO, Group Relative Policy Optimization (GRPO) and Reinforcement Learned Teache (RLT).

• Customer Clustering at Scale - Developed scalable, ensemble tree-based algorithm leveraging Spark to process 4M+ customer transactions, driving MAU growth to 8.5M within one year.
• Chain Fraud Detection Dashboard - Built a real-time pipeline and analytics dashboard for blockchain transaction monitoring.
• Marketing Data Pipeline -Led cross-team collaboration to design an end-to-end marketing data modeling ETL pipeline with ERD system design, migrating the legacy data warehouse from Django.

• Autonomous Inventory System - Developed scalable inventory reordering system for 15 hypermarkets with 8,000+ SKUs.
• Automated Shopping Experience - Contributed to a $100M funded project for a fully automated shopping experience (Low-Cost Amazon Go), implementing indoor location tracking in collaboration with Rocket Internet.
• Operational Analytics - Established real-time operational KPIs with automated reporting systems, ensuring data accuracy and driving strategic decisions.

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