About
Hello, I’m Aadarsha
I’m a Master’s student in Computer Science at Washington University in St. Louis with hands-on experience in machine learning, data engineering, and full-stack development. My thesis research focuses on using domain-adversarial learning to detect preclinical Alzheimer’s disease through driving behavior analysis.
I currently serve as a Graduate Teaching Assistant for CSE 5114 (Data Manipulation and Management at Scale), guiding students through data pipelines, distributed systems, and real-world capstone projects. I also work as a Graduate Assistant with WashU’s Taylor Family Center for Student Success, leading data initiatives and supporting first-generation and limited-income student programs.
What I’m Working On
Research: Building a Domain Adversarial Neural Network (DANN) to create vehicle-agnostic cognitive signatures from naturalistic driving data for early Alzheimer’s detection.
Teaching: Guiding students in implementing data pipelines and real-time processing systems, conducting technical oral exams, and mentoring capstone project groups in CSE 5114.
Student Success: Driving data assessment and communication strategies at the Taylor Family Center for Student Success, supporting first-generation and limited-income student programs.
Leadership: Serving as Vice President of the Graduate-Professional Council Chamber and on three university advisory boards (Student Affairs, Career Engagement, and Bauer Leaders Academy).
Featured Projects
Multimodal Alzheimer’s Prediction — Combined CNNs for MRI analysis with clinical data models for early detection, documented in NeurIPS format.
Datacenter Cooling Optimization — Applied deep reinforcement learning (DDQN, PPO, SAC) to achieve 35.8% energy efficiency improvement.
Interactive Storybook — Full-stack application with Vue.js, Node.js, and MongoDB featuring AI-powered story generation via OpenAI API.
Check out more on my Projects page.
Background
I’m currently completing my M.S. in Computer Science at WashU (expected May 2026), with coursework in AI for Health, Deep Learning, Computer Vision, and Computational Biology. I hold a B.A. in Computer Science & Data Analytics from Ohio Wesleyan University, where I was recognized with the Golden Bishop Award and Mortar Board membership.
Previously, I interned as an AI Engineer at Crittero, Inc. and as a Data Analyst at Lab714, where I built full-stack applications and delivered data-driven insights.
Let’s Connect
I’m always interested in collaborating on projects at the intersection of technology and impact. Feel free to reach out or explore my CV for more details.