About Me
Professional Experience
I ship AI systems to production, then study why they work. My approach: research rigor meets deployment reality. From RAG systems serving thousands of users to multi-agent AI for power grids, I build technology that scales responsibly for infrastructure that lasts.
Current Role
Graduate Research Assistant focused on multi-agent AI for power grid optimization.
Research Experience
Academic positions focused on AI systems research and development.
Graduate Research Assistant
Concordia University • VoltAge Fellowship • Sep 2025–PresentInvestigating coordination mechanisms for distributed AI agents in power grid management and climate modeling. Developing novel optimization algorithms for multi-agent decision-making under uncertainty. Collaborating with industry partners on real-world deployment of research prototypes.
Software Development Engineer
SpokenWeb (SSHRC/Concordia) • Jun 2024–PresentArchitected automated data pipelines for cultural heritage metadata processing using Ruby, Python, and Apache Solr. Improved processing efficiency by 61% through algorithm optimization and parallel processing. Modernized infrastructure with Docker containerization and CI/CD, reducing deployment time by 80%. Presented technical architecture at Blacklight Summit 2025.
Research Team Lead
Innovation Lab • Jan 2024–Dec 2025Led 4-person research team developing multilingual conversational AI system (6 languages) for cyber-violence prevention. Designed novel prompt-driven persona framework using Gemini LLMs with Redis-backed conversation state. Developed automated UI/UX evaluation methodology using GPT-4o, reducing testing cycles by 40%. System deployed to 2,000+ users.
Industry Experience
Production engineering roles with measurable business impact.
Applied ML Researcher
7Dish (Contract Research) • Jun 2023–Jan 2024Researched and developed production RAG architecture using LangChain and GPT-4 for nutrition question-answering. Investigated BERT-based embedding models for semantic search, improving retrieval accuracy by 21% on Databricks. Designed real-time ETL pipeline for knowledge base enrichment. Deployed system on Azure serving 5,000+ monthly active users with 30% engagement increase.
Data Science Intern
Visive Inc. • Aug 2022–Dec 2022Developed real-time image search engine using TensorFlow on AWS, reducing false positives by 16%. Built fraud detection pipelines using statistical modeling, achieving 92% accuracy in production. Engineered ETL pipelines processing 1M+ daily transactions with optimized database schemas.
Software Developer Intern
ProfCess • May 2021–Aug 2021Developed ML-driven recommendation system using scikit-learn, improving content relevance by 40%. Enhanced frontend performance and mobile UX across core user flows.
Technical Skills
Core competencies across research, engineering, and deployment.
AI/ML Research
PyTorch, TensorFlow, Hugging Face Transformers, Weights & Biases, MLflow, TensorBoard, Jupyter, Google Colab
LLM Systems
GPT-4, Claude, Gemini, Llama, Mistral with fine-tuning, prompt engineering, RLHF. LangChain, LlamaIndex, LangGraph, RAG architectures
Vector & Search
Pinecone, Weaviate, Apache Solr, Blacklight. Semantic search, embedding optimization, knowledge retrieval systems
Programming
Python (expert), JavaScript/TypeScript (proficient), Go, SQL, Ruby. FastAPI, Flask, Django, React, Node.js, Ruby on Rails
Infrastructure
AWS (EC2, Lambda, S3, SageMaker), Azure AI, Google Cloud. Docker, Kubernetes, CI/CD (GitHub Actions), Apache Airflow
Data Engineering
Apache Spark, PySpark, Databricks, ETL pipelines, PostgreSQL, MongoDB, Redis. Real-time data processing and pipeline optimization
Research Methods
Experimental Design, Statistical Analysis, A/B Testing, Model Evaluation & Benchmarking, Ablation Studies, Scientific Writing
Collaboration
Cross-functional team leadership, research mentorship, technical documentation, conference presentations, stakeholder communication
Achievements & Recognition
Fellowships, presentations, and notable outcomes.
VoltAge Doctoral Fellowship
Competitive research fellowship supporting PhD work on multi-agent AI systems for climate change mitigation through power grid optimization.
MITACS Accelerate Scholar
Research funding for Master's thesis on memory mechanisms for coherent LLM-based dialogue systems.
Blacklight Summit 2025
Presented technical architecture of SpokenWeb Search Engine at the premier conference for digital library search systems.
IEEE CAI 2026 Publication
SWin paper on sliding window summarization for coherent LLM-driven dialogue systems accepted at IEEE Conference on Artificial Intelligence.
EACL 2026 Publication
Accepted paper on causal bias mitigation in LLMs at European Chapter of the Association for Computational Linguistics.
Connect
Open to research collaborations and consulting opportunities.