Machine learning professional with solid history of developing and refining predictive models to solve complex problems. Adept at collaborating with cross-functional teams to achieve impactful results, while remaining adaptable to evolving project needs. Renowned for analytical skills and proactive approach to problem-solving.
Overview
5
5
years of professional experience
Work History
Machine Learning Engineer
Monsters Aliens Robots Zombies (MARZ)
09.2022 - 02.2024
Developed Vanity AI, Vanity AI is a production-ready solution that empowers VFX teams and Hollywood to deliver large volumes of high-end 2D aging, de-aging, cosmetic, wig, and prosthetic fixes.(https://monstersaliensrobotszombies.com/vanityai)
Vanity AI is up to 300 times faster than traditional VFX pipelines, 80% more cost effective, and has no capacity constraints.
Developed a full end-to-end tested data preparation pipeline using Apache Airflow.
Deployed GitHub workflows for maintaining and updating docker images.
Launched Vanity AI API on AWS and local servers
Deployed Redis server and workers between different services.
Research Assistant
Simon Fraser University
01.2020 - 01.2022
Leading research on drug resistance prediction using AI for key bacterial diseases
Using GenAI developed models for predicting drug resistance in Mycobacterium Tuberculosis and E Coli using machine learning and deep learning algorithm.
Highlighted Projects: 5000 Youtube channels Analysis - Data Analysis Web app - Adult Demographic Analysis - Netflix TV shows and movies dataset Analysis - Ecommerce Purchase Analysis
Research Assistant
Sharif University of Technology
10.2018 - 01.2020
Developed deep learning methodologies for the identification of cancer subtypes, focusing on pancreatic and liver cancers
Integrated multi-omics data using deep learning techniques to enhance diagnostic accuracy and treatment specificity