Recent activity



Intel's Annual Gordon Moore Award Nomination: "Informed risk-taking across Intel Labs, PSG, SSG, and University Research that has furthered Intel's FPGA innovations"

      • Category: Excellence in Risk Taking.
      • Team: Aravind Dasu, Mahesh Iyer, Eriko Nurvitadhi, Michael Adler, Justin Gottschlich, Mondira Pant, Todd Younkin

Intel Tech Insights Leadership Award: "Machine Programming: A Radical Approach to Automating Software"

Patent issued: "Coordination and increased utilization of graphics processors during inference"

Recipient of High Five Patent Award (8th time, I think :)) -- co-inventor on five patent applications within a year.

Patent issued: "Extend GPU/CPU coherency to multi-GPU cores"

DATSA has been open sourced.

SysML whitepaper: "SysML: The New Frontier of Machine Learning Systems"

Invited talk, Stanford DAWN Retreat '19: "Machine Programming"

Patent issued: "Detecting root causes of use-after-free memory errors"

Patent issued: "Methods and systems to identify and reproduce concurrency violations in multi-threaded programs"

Invited talk to Dawn Song's research team at Berkeley: "Anomaly detection, machine programming, and other AI research at Intel"

Our "Precision and Recall for Time Series" NeurIPS paper has made a few different top paper reading lists. Here's one. Here's another.

Patent issued (milestone, 20th issued patent): "Programmable coarse grained and sparse matrix compute hardware with advanced scheduling."

Co-teaching with Insup Lee and James Weimer: CIS 700-002: Topics in Safe Autonomy, Spring 2019


Invited talk at UW's TVM Conference: "Machine Programming"

Invited talk at Intel's NeurIPS special luncheon: "Anomaly Detection: Today and Beyond"

NeurIPS spotlight talk: "Precision and Recall for Time Series"

NeurIPS 3-minute teaser video: "Precision and Recall for Time Series"

Intel Labs Division Recognition Award for creating and leading the Anomaly Detection IP Think Tank.

Invited talk at SPLASH-I: "The Future of AI: Machine Programmers and Their Necessary Self-Awareness"

Invited talk at Intel's Autonomous Driving Community of Practice Workshop: "Autonomous Vehicles and the Anomalous 1%"

GRASP / PRECISE Industry Symposium at University of Pennsylvania: "Deep Learning for Autonomous Driving" (video here)

MAPL presentation: "The Three Pillars of Machine Programming" (joint with MIT)

Program committee member, SysML 2019.

Invited talk at VMware Research: "Anomaly Detection for Practical Systems (and a Tiny Bit of Machine Programming)"

Special seminar at University of Pennsylvania: "The Future of Anomaly Detection" (slides forthcoming)

General Chair, Second ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL)


Intel's Principal Investigator for the joint Intel/NSF CAPA research center.

Program Chair and Founding Member, First ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL)

Deputy Technical Lead and Founding Member, NSF/Intel Partnership on Computer Assisted Programming for Heterogeneous Architectures


Talk at Intel's High Performance Developers Conference: "Using Machine Learning To Avoid the Unwanted"

Intel Research Velocity Challenge Winner: "Using Deep Neural Networks to Identify and Fix Performance and Correctness Anomalies in Data Centers"


General Chair and Steering Committee Member, TRANSACT 2015

Director of Engineering at Machine Zone


Program Chair, TRANSACT 2014


Application Track Chair, TRANSACT 2013