Best fit
Data scientist or machine learning engineer roles focused on practical AI systems.
Vancouver, BC, Canada / Data Scientist | Machine Learning Engineer
I build practical AI systems for operations, recommendations, scientific data, and language-heavy workflows. My work spans mathematical optimization, time series forecasting, LLM/RAG products, privacy-preserving synthetic data, and applied research.
Current Focus
Data scientist or machine learning engineer roles focused on practical AI systems.
Optimization, forecasting, recommender systems, LLM/RAG products, and applied research.
Translate ambiguous operational problems into measurable models, pipelines, and decision support.
Optimization work translating supply chain rules, capacity limits, routing choices, and demand priorities into solver-ready formulations.
Active learning pipeline for satellite imagery selection with SpaceML and NASA IMPACT.
Research initiative ranking for AI-assisted Earth observation workflows.
Explainable AI, satellite data curation, mobile ML for agriculture, and machine-learning forecasting.
Selected Work
Optimization, forecasting, and enterprise ML workflows for forestry supply chain and manufacturing operations.
Recommendation systems, feature engineering, analytics pipelines, and cloud-native deployment.
Privacy-preserving synthetic tabular data generation and evaluation.
Self-supervised and active learning for petabyte-scale satellite imagery.
Explainable AI, medical image synthesis, and applied forecasting research.
Projects
Applied mathematics Current
A large-scale linear programming and operations research project for modeling shipping, capacity, routing, and demand-priority decisions in forestry operations.
Product ML Product
A matching and personalization workflow using LLM-derived features, RAG context, vector search, and behavioral analytics.
NLP research Research
Generated accessible biomedical research summaries for non-expert audiences using domain-specific LLMs, prompt tuning, RAG, and representation engineering.
LLM reasoning Research
Created structured natural-language explanations for AI2 Reasoning Challenge questions and used Tree of Thought prompting to guide step-by-step problem solving.
Earth observation Open source
Active learning system for identifying relevant satellite imagery from petabyte-scale unlabeled Earth observation datasets.
Mobile ML Published
Real-time iOS app for grape leaf disease diagnosis with on-device deep learning, remedy suggestions, and model optimization.
Publications
Explainable deep learning for SAR target classification, combining model performance with interpretable evidence for high-stakes imagery workflows.
Lessons from citizen-science tooling for surfacing useful imagery from petabyte-scale unlabeled Earth observation data.
Mobile explainable AI for grape leaf disease diagnosis, built for real-time on-device use and practical field support.
Explainable forecasting research focused on making model signals more transparent for financial prediction workflows.
Capabilities
Education
University of British Columbia / Vancouver, BC
GPA 93.4. Focused on advanced NLP, transformer models, machine learning and optimization, computational linguistics, and interactive data visualization.
Thapar Institute of Engineering and Technology / Patiala, Punjab, India
GPA 84.5. Covered data structures and algorithms, AI and machine learning, database systems, and software engineering.
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