Jesse Islam

Visitors so far: Loading…

Experience

Sep. 2018 – Sept. 2025

Pioneered a deep‑learning framework for time‑varying effects, dynamically capturing hazard shifts to boost survival prediction accuracy. Github | Publication | Docker
Pioneered a data‑agnostic, VAE + GAN counterfactual framework, unlocking 10 insights per feature.
Reduced stakeholder interpretation time by ∼70 % by streamlining 10 metrics into a 5‑tier causal framework.
Cut in silico analysis runtime ∼10× and increased throughput ∼100× with an optimized, efficient pipeline.
Co‑developed casebase in R for survival analysis in a team of 3 using version control. CRAN | Publication
Created a custom data pre‑processing pipeline to meet stakeholder requirements. Bitbucket
Prevented $50,000+ in wasted experimental resources by developing a de‑confounded analysis pipeline integrating multi‑modal, high‑dimensional data across tissues using a hierarchical multi‑hypothesis testing framework with random intercepts, uncovering cross‑tissue insulin response patterns.

Jan. 2022 – Aug. 2022

Facilitated conversations guiding ∼50 students through the myPath Individual Development Program (IDP) in groups of 5–10, aligning their life goals with their values.

Sep. 2021 – Dec. 2021

Improved student comprehension by tailoring R programming best‑practice lectures to diverse student profiles.

Sep. 2017 – Dec. 2019

Computer Science Teaching Assistant Award (Dec. 2019)
Empowered hundreds of undergraduates by distilling complex circuit‑design, machine‑code, and assembly concepts into clear, accessible explanations that bridged gaps left by standard lectures.

Goal-oriented in silico perturbation: a data‑agnostic framework using GANs and variational inference for counterfactual analyses.
Islam, J. et al. (Expected 2025)
In silico validation of gene expression perturbations affecting progression‑free incidence in TCGA.
Islam, J. et al. (Expected 2025)
Case‑Base Neural Network: Survival analysis with time‑varying, higher‑order interactions.
Islam, J. et al. | Github (2024)
casebase: An Alternative Framework for Survival Analysis and Comparison of Event Rates.
Bhatnagar, S. R., Turgeon, M., Islam, J. et al. | CRAN (2022)

Proof of concept for deep learning time‑to‑event prediction framework
District 3 / IVADO AI Genomics Competition, 1st Place & Innovation Award (May 2020)
Pivotstage
Real‑time AI subject tracking tool leveraging deep‑learning object detection for social media with a GUI.
Github
Retrieval‑Augmented Generation for arXiv
AI‑powered Python toolkit leveraging transformer LLMs for summarizing and clustering arXiv abstracts.
Github
Cloud resume challenge
Demonstrates skill with cloud applications, database APIs, Terraform for IaC and Cloud Build for CI/CD.
Terraform | Backend | Frontend

Ph.D. Quantitative Life Sciences, McGill (Montreal, QC)
Sep. 2018 – Dec. 2025
B.Sc. Joint Major in Computer Science and Biology, McGill (Montreal, QC)
Sep. 2014 – May 2018