Zarreen Reza

I am a Senior Applied AI Research Scientist with over five years of experience across diverse industries. My background combines deep research and practical ML expertise, spanning various domains.

I earned my M.Sc. in Computer Science focusing on AI from the University of Windsor. Since then, I have held roles as a Data Scientist at Thales for over two years, an AI Research Scientist at Volta Charging Inc. (an EV charging infrastructure company in San Francisco) for more than a year, and currently, I serve as a Senior Applied AI Research Scientist at Jacobb.ai, a non-profit applied AI research center in Montreal, Quebec.

My current research work focuses on the privacy, fairness, robustness, interpretability, and scalability of LLMs. I have extensive research and industry experience in deep learning, LLMs, and privacy-preserving ML, applying these techniques to human-centered applications such as education, healthcare, and more. Additionally, I am highly interested in doing research on the reasoning capabilities of LLMs.

 

Research

(*equal contribution, †alphabetical / random authorship)

Paper Image

Low-rank finetuning for LLMs: A fairness perspective

S. Das, M. Romanelli, C. Tran, Z. Reza, B. Kailkhura, F. Fioretto
Preprint, 2024.

Paper Image

Automated identification of sea pens using OpenCV and machine learning

Z. Reza† and 9 others.
Data Study Group, The Alan Turing Institute, 2023.
Published as the final report of the Data Study Group at The Alan Turing Institute in London, UK, following a week-long intensive hackathon.

Paper Image

PySyft: A Library for Easy Federated Learning

A. Ziller†, A. Trask†, A. Lopardo†, B. Szymkow†, B. Wagner†, E. Bluemke†, J. M. Nounahon†, J. Passerat-Palmbach†, K. Prakash†, N. Rose†, T. Ryffel†, Z. Reza†, G. Kaissis†
Springer International Publishing, 2021.
Published as a book chapter in Federated Learning Systems: Towards Next-Generation AI.

Paper Image

Real-time Automated Weld Quality Analysis From Ultrasonic B-scan Using Deep Learning

Reza, Zarreen Naowal
Master’s dissertation, 2019. Nominated for Governor General’s Gold Medal.
Supervised by Dr. Roman Maev and Dr. Dan Wu.

Paper Image

Detecting jute plant disease using image processing and machine learning

Zarreen N. Reza, Faiza Nuzhat, Nuzhat Ashraf Mahsa, Md. Haider Ali.
ICEEICT, 2016.
Orally presented in the 3rd International Conference on Electrical Engineering and Information Communication Technology (ICEEICT).

Paper Image

Authenticity Analysis of Opinion and Claims made online

Zarreen N. Reza, Ruturaj R. Raval, Kaival Patel.
3rd Winner, Thales Student Innovation Championship in AI, 2018.
Ranked 3rd out of 52 student teams from universities across Canada by developing an end-to-end AI solution for fighting misinformation in online news.

Paper Image

Visual Relationship Detection using Deep Learning for Vision and NLP

Zarreen N. Reza†, Ashraf Neisari†, Ruturaj R. Raval†, Zeeshan Mansoor†.
Course final project, University of Windsor, 2018.

Paper Image

Finding Relevant Biomarkers for Prostate Cancer using Feature Selection and Dimensionality Reduction

Zarreen N. Reza, Susha Suresh.
Course final project, University of Windsor, 2018.

Paper Image

A Comprehensive Study of Unsupervised Feature Learning using Autoencoders

Zarreen N. Reza.
Course final project, University of Windsor, 2019.

Paper Image

Cancer Progression Prediction from Breast Cancer Gene Expression Data using Machine Learning

Zarreen N. Reza, Rajasi Upadhyay, Sumit Khairnar.
Course final project, University of Windsor, 2018.

Experience

Senior Applied AI Research Scientist, 2023 — Present

JACOBB – Applied Artificial Intelligence Center
Montreal, Canada

Co-Founder and Lead AI Scientist, 2021 — Present

resolutio.ai
Ottawa, Canada

Privacy-Preserving AI Researcher, open-source contributor, 2020 — Present

OpenMined
Remote, USA

AI Research Scientist, 2021 — 2023

Volta Charging, later acquired by Shell
Montreal, Canada

Data Scientist, 2019 — 2021

Thales Canada (Guavus)
Montreal, Canada

Research Assistant, 2017 — 2019

Institute of Diagnostic Imaging and Research (IDIR)
Windsor, Canada

Teaching

Talks

Services

  1. Leadership Fellow, Women Who Code, Aug. 2021 – Sep. 2022.

    • Led the Data Science Track consisting of 4500+ members in organizing free events, and workshops to help women excel in STEM roles.
    • Led a team of 50+ volunteers in program designing, event planning, and building technical content for 150+ events including webinars, workshops, hands-on coding tutorials, career growth, etc.
    • Honed public speaking skills through speaking at 40+ events including annual summits and conferences.
  2. Organizer

  3. Judge and Reviewer

  4. Mentorship

Mentorship

  • JACOBB: Led 8-member AI team, planning and coordinating research work as sprints, ensuring timely milestone delivery.
  • JACOBB: Mentored five junior AI researchers, focusing on code quality and standardization.
  • OpenMined: Mentored 25 participants of the OpenMined Beta Tech Bootcamp on Privacy-Preserving ML.
  • Guavus: Mentored two data scientist interns and collaborated with researchers, engineers, and the customer success team on AI model integration.
  • IDIR: Trained three undergrad CS students in Python Programming and Machine Learning to succeed in their Co-op term.

Awards and Achievements

Certificates