We are the Accelerate Data intensive Applications through Programming-Languages Techniques (ADAPT) lab. Our focus is on building novel program abstractions and optimizations targeting machine learning and data science workloads and to build evolvable compiler construction techniques using both machine learning and formal methods techniques. Informally, we do projects in both ML for compilers and compilers for ML and related areas. There are opportunities to join on-going projects at ADAPT lab. Please see PI's front page for how to reach out to find such opportunities.

Current Members

Charith Mendis

Principal Investigator

Damitha Lenadora

PhD student since 2021

Ahan Gupta

PhD student since 2022

Stefanos Baziotis

PhD student since 2021

Vimarsh Sathia

PhD student since 2022

Devansh Jain

PhD student since 2023

Jai Arora

PhD student since 2023

Chamika Sudusinghe

PhD student since 2023

Wanyu Zhao

PhD student since 2023

Yuhao Ge

MS student since 2023

Avaljot Singh

PhD Student student since 2022

co-advised with: Gagandeep Singh

Muyan Hu

PhD Student student since 2023

co-advised with: Vikram Adve

Yueming Yuan

Undergraduate student since 2022


Yufeng Wang

MSc, 2023

Thesis: A framework for programming and optimizing temporal graph neural networks

Now: Compiler Engineer at Tesla (Dojo system)

Tianfan Xu

BSc, 2023

Project: Verifying XLA tensor rewrite rules

Now: MS student at Harvard