team

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

Stefanos Baziotis

PhD student since 2021

Avaljot Singh

PhD Student student since 2022

co-advised with: Gagandeep Singh

Devansh Jain

PhD student since 2023

Jai Arora

PhD student since 2023

Chamika Sudusinghe

PhD student since 2023

Muyan Hu

PhD Student student since 2023

co-advised with: Vikram Adve

Yuhao Ge

MS student since 2023

Hao Guo

MS student since 2023

Akash Pardeshi

MS student since 2024

Krut Patel

MS student since 2024

Zhihao Wang

Undergraduate student since 2024

Marco Frigo

Undergraduate student since 2024

Alex Broihier

Undergraduate student since 2024

Andy Luo

Undergraduate student since 2024

Kaushik Varadharajan

Undergraduate student since 2024

Nikhil Jayakumar

Undergraduate student since 2024

Alumni

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

Yueming Yuan

BSc, 2023

Project: code generation for sparse attention

Now: PhD student at UIUC

Wanyu Zhao

First year PhD rotation, 2024

Project: optimizations for temporal GNNs

Now: