About me
I am a second-year PhD student in the Department of Computer Science at Stanford University, advised by Prof. Matei Zaharia. I am affiliated with the Stanford InfoLab and supported by the National Science Foundation Graduate Research Fellowship.

My broad research interests include distributed systems and cloud computing -- in particular, I am interested in the Systems problems associated with learning and deploying machine learning models at scale. I currently work on Weld, a system that facilitates fast, parallel code generation. You can read more about Weld here.

I graduated from MIT in 2015 with a SB in Computer Science and Mathematics and a MEng in EECS.
Publications
DAWNBench: An End-to-End Deep Learning Benchmark and Competition
Cody Coleman, Deepak Narayanan, Daniel Kang, Tian Zhao, Jian Zhang, Luigi Nardi, Peter Bailis, Kunle Olukotun, Christopher Re, Matei Zaharia.
NIPS MLSys 2017.

DAWNBench: An End-to-End Deep Learning Benchmark and Competition
Cody Coleman, Deepak Narayanan, Daniel Kang, Tian Zhao, Jian Zhang, Luigi Nardi, Peter Bailis, Kunle Olukotun, Christopher Re, Matei Zaharia.
SOSP AISys 2017.

Weld: Rethinking the Interface Between Data-Intensive Libraries
Shoumik Palkar, James Thomas, Deepak Narayanan, Anil Shanbhag, Holger Pirk, Malte Schwarzkopf, Saman Amarasinghe, Samuel Madden, Matei Zaharia.
arXiv.

MacroBase: Prioritizing Attention in Fast Data
Peter Bailis, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri.
SIGMOD 2017.

Weld: A Common Runtime for High Performance Data Analytics
Shoumik Palkar, James J. Thomas, Anil Shanbhag, Deepak Narayanan, Holger Pirk, Malte Schwarzkopf, Saman Amarasinghe, Matei Zaharia.
CIDR 2017.
Teaching
I was a Teaching Assistant for Introduction to Algorithms (6.006) in Spring 2014, and for Design and Analysis of Algorithms (6.046) in Spring 2015.

Before that, I was a Lab Assistant for Elements of Software Construction (6.005) and Introduction to EECS I (6.01).
Contact me