Abdul Wasay

I am a Research Scientist in the Machine Programming Group at Intel Labs.

My research is at the intersection of systems and machine learning. I identify co-design opportunities between the two fields to develop techniques that accelerate data science and deep learning pipelines by removing computation and data movement bottlenecks. Additionally, I am interested in mapping out deep neural network models' design space to enable better design.

Before joining Intel, I got my Ph.D. from Harvard and my bachelor's degree from Lahore University of Management Sciences (LUMS). I also spent a summer at EPFL and another at HP Research.

Please see my resume for more details.

I also maintain a bibliography on research at the intersection of deep learning, data management systems, and responsibility.

Selected Publications

Computation-Cautious Machine Learning Systems.
Abdul Wasay.
Ph.D. Thesis. 2021.

μ-TWO: 3× Faster Multi-Model Training with Orchestration and Memory Optimization
Sanket Purandare, Abdul Wasay , Stratos Idreos, and Animesh Jain.
Conference on Machine Learning and Systems MLSys, 2023.

Machine Programming: Turning Data into Programmer Productivity.
Abdul Wasay, Nesime Tatbul, and Justin Gottschlich.
Conference on Very Large Databases VLDB, 2022.

More or Less: When and How to Build Convolutional Neural Network Ensembles. [demo] [poster]
Abdul Wasay and Stratos Idreos.
International Conference on Learning Representations ICLR, 2021.

Deep Learning: Systems and Responsibility. [video] [bibliography]
Abdul Wasay, Subarna Chatterjee, and Stratos Idreos.
ACM International Conference on Management of Data SIGMOD, 2021.

MotherNets: Rapid Deep Ensemble Learning. [demo] [poster]
Abdul Wasay, Brian Hentschel, Yuze Liao, Sanyuan Chen, and Stratos Idreos.
Conference on Machine Learning and Systems MLSys, 2020.

Learning Data Structure Alchemy.
Stratos Idreos, Kostas Zoumpatianos, Subarna Chatterjee, Wilson Qin, Abdul Wasay, Brian Hentschel, Mike Kester, Niv Dayan, Demi Guo, Minseo Kang, and Yiyou Sun
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 2019.

The Periodic Table of Data Structures. [website]
Stratos Idreos, Konstantinos Zoumpatianos, Manos Athanassoulis, Niv Dayan, Brian Hentschel, Michael S. Kester, Demi Guo, Lukas Maas, Wilson Qin, Abdul Wasay, and Yiyou Sun.
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 2018.

Data Canopy: Accelerating Exploratory Statistical Analysis. [website] [poster] [video]
Abdul Wasay, Xinding Wei, Niv Dayan, and Stratos Idreos.
ACM International Conference on Management of Data SIGMOD, 2017.

Queriosity: Automated Data Exploration. [website] [poster]
Abdul Wasay, Manos Athanassoulis, and Stratos Idreos.
IEEE International Congress on BigData, 2015.

Rethinking Buffer Management in Data Center Networks.
Aisha Mushtaq, Asad Khalid Ismail, Abdul Wasay, Bilal Mahmood, Ihsan Ayyub Qazi, and Zartash Afzal Uzmi.
ACM International Conference on Data Communications SIGCOMM, 2014.


I thoroughly enjoy teaching. I have designed and taught courses both at Harvard University and Ashesi University, where I was a visiting faculty through the Archer-Cornfield Teaching Fellowship.

Harvard University
Course Instructor at CSCI S-165: Data Systems and Machine Learning | Summer 2019

Ashesi University
Course Instructor at CS402: The Scientist and the Machine, CS313: Intermediate Programming, and CS460: Data Systems and Machine Learning | Fall 2019 and Spring 2020

Harvard University
Teaching Fellow at CS165: Data Systems, CS265: Big Data Systems, and ac297r: Capstone Projects | 2015 through 2019


aw.awasay [at] gmail.com | abdul.wasay [at] intel.com