Scholar
Zarreen Naowal Reza
Google Scholar ID: YTYweEwAAAAJ
Senior AI Research Scientist
Citations & Impact
Citations
411
H-index
5
i10-index
3
Publications
10
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published multiple papers including:
- ‘Small Models, Big Support: A Local LLM Framework for Teacher-Centric Content Creation and Assessment using RAG and CAG’
- ‘Low-rank finetuning for LLMs: A fairness perspective’
- ‘PySyft: A Library for Easy Federated Learning’ (book chapter in ‘Federated Learning Systems: Towards Next-Generation AI’, Springer, 2021)
- ‘Detecting jute plant disease using image processing and machine learning’ (oral presentation at ICEEICT 2016)
- Master’s dissertation contributed to U.S. Patent US20230228716A1 ([0140]–[0143]).
- 3rd place in Thales Student Innovation Championship in AI (2018) among 52 Canadian university teams for an end-to-end AI solution against online misinformation.
- Completed course projects on visual relationship detection (vision+NLP) and biomarker selection for prostate cancer.
Research Experience
- Currently Senior Applied AI Research Scientist at Jacobb.ai, a non-profit applied AI research center in Montreal.
- Former AI Research Scientist at Volta Charging Inc. (San Francisco) for over a year.
- Former Data Scientist at Thales for over two years.
- Participated in The Alan Turing Institute’s Data Study Group (2023), developing an automated sea pen identification system using OpenCV and ML.
- Contributed to third-party audit research on AI transparency of recommender systems at LinkedIn and Dailymotion (October 2024).
- Involved in Secure Enclaves for AI Evaluation project with Anthropic, UK AI Safety Institute, and OpenMined (November 2024).
Background
- Senior Applied AI Research Scientist with over five years of experience across diverse industries.
- Current research focuses on privacy, fairness, safety and robustness, interpretability, and scalability of LLMs and Agentic AI.
- Extensive research and industry experience in deep learning, LLMs, and privacy-preserving ML.
- Applies AI techniques to human-centered applications such as education and healthcare.
- Highly interested in the reasoning capabilities of LLMs.
Co-authors