Justin Gottschlich

Principal Scientist & Director/Founder of Machine Programming Research (Intel Labs)

Steering Committee Chair, ACM SIGPLAN Machine Programming Symposium (MAPS)

Chair of Industrial Board and Executive Director at PRECISE, University of Pennsylvania

Principal Investigator and Founder of the upcoming Intel Machine Programming Research Center

Adjunct Assistant Professor, University of Pennsylvania (my Penn website)

HIGHLIGHTS

Keynote @ MIT's DSAIL 2021 virtual retreat: "A Glimpse Into Machine Programming @ Intel Labs"

Machine programming talk @ UWisc: "Machine Programming: Challenges and Opportunities" (video)

Our general research direction has been highlighted by venues like Communications of the ACM, New York Times, SDTimes, Economic Times, Venturebeat, and Wharton, and many others.

Keynote @ PRECISE's Industry Day: "Machine Programming: The Future of Autonomy"

CURRENT STUDENTS

Roshni Iyer (advised by Yizhou Sun and Wei Wang @ UCLA)

Ramneet Kaur (co-advised with Insup Lee @ Penn)

Celine Lee (advised by me and Dan Roth @ Penn)

Bradley MacDonald (advised by me @ Penn)

Fangke Ye (advised by Vivek Sarkar @ Georgia Tech)

PanteA Zardoshti (advised by Mike Spear @ Lehigh)

RECENT COMMITTEES

PACT'21, FSE'21, ICML'21, USENIX ATC'21, ICLR'21, MLSys'21, OOPSLA'21, NeurIPS'20, MAPL'20 (SC chair), JPDC'20, aiDM '20, TheWebConf'20, MLSys'20, PACT'19 (SRC), SysML'19, MAPL'18 (general chair), MAPL'17 (PC chair)

Contact: justin.gottschlich@intel.com

BRIEF BIO

I founded and lead the Machine Programming Research group at Intel Labs. Machine programming (MP) is a new field of research that uses automation to reduce the temporal constraints of software development (e.g., the time it takes a developer to write, maintain, and test code) and quality (e.g., performance, correctness, security, maintainability, etc.). We generally consider MP as a fusion of machine learning and formal methods, which rely heavily on programming languages and systems. We provide a brief overview of MP in our “Three Pillars of Machine Programming” vision paper (see Armando Solar-Lezama's website for a deeper dive). In academia, I have appointments as the industrial advisory board chair and executive director for the PRECISE Center at the University of Pennsylvania (Penn). I am also an adjunct assistant professor at Penn in the Computer and Information Science Department.

I have a deep desire to build bridges with thought leaders across industry and academia to identify disruptive research and push it forward as a community. Recently I have been working with Amazon, Brown, Georgia Tech, Google AI, Hebrew University, IBM Research, Microsoft Research, MIT, Penn, Stanford, Texas A&M, UC-Berkeley, and UCLA, to name a few. I co-founded and am the principal investigator of the joint Intel/NSF CAPA research center which focuses on simplifying the software programmability challenge for heterogeneous hardware. I also helped create the ACM SIGPLAN Machine Learning and Programming Languages workshop and currently serve as its steering committee chair. I have the distinguished honor of serving on the advisory board of Solar-Lezama et al.’s 2020 NSF Expeditions “Understanding the World Through Code.”

I have 35+ peer reviewed publications, 40+ issued patents with over 100 patents pending. I've been lucky enough to give several dozen talks at wonderful places like Berkeley, BMW, IBM Research, MIT, Penn, Stanford, UCLA, University of Washington, VMWare, and Wharton. I've had the tremendous honor to give keynote addresses at places like University of Pennsylvania, the US Department of Energy, and MIT.

My (extremely dated) CV is here. Google scholar.

RECENT ACTIVITY

42nd Patent issued: "Neural network optimization mechanism" (10,929,749)

41st Patent issued: "Methods and apparatus for runtime multi-scheduling of software executing on a heterogeneous system" (10,908,884)

Upcoming keynote address @ MIT's DSAIL 2021 virtual retreat: "A Glimpse Into Machine Programming @ Intel Labs"

40th Patent issued: "Compute optimization for deep neural networks" (10,902,547)

Patent issued: "Coordination and increased utilization of graphics processors during inference" (10,891,707)

Accepted invitations to serve on the program committees of: ICLR'21, ICML'21, ATC'21, MLSys'21, OOPSLA'21, and FSE'21. With the exception of NeurIPS'21, I think that might be my limit of committee duty for 2021. :)

A video on our ControlFlag system

Patent issued: "Systems and methods for determining a configuration of a microarchitecture" (10,853,554)

Invited machine programming talk @ MIT & NeurIPS 2020, ML for Systems Workshop: "A Glimpse Into Machine Programming @ Intel Labs" (coming soon)

Paper accepted to 2020 NeurIPS Computer-Assisted Programming Workshop "Software Language Comprehension using a Program-Derived Semantics Graph"

Paper accepted to NeurIPS 2020 ML for Systems Workshop: "ControlFlag: A Self-supervised Idiosyncratic Pattern Detection System for Software Control Structures"

37th patent issued: "Methods and apparatus to detect anomalies of a monitored system" (10,802,942)

Invited MP talk @ UWisc: "Machine Programming: Challenges and Opportunities"

36th patent issued: "Programmable coarse grained and sparse matrix compute hardware with advanced scheduling" (10,769,748)

Keynote @ Department of Energy's Program Synthesis for Scientific Computing: "Machine Programming: Challenges and Opportunities"

Patent issued: "Neural Network Scheduling Mechanism" (10,719,760)

CACM article on machine programming: "Your Wish is My CMD" by Neil Savage

Paper accepted to MAPL 2020: "Learned Garbage Collection" (joint with MIT)

Paper accepted to CAV 2020: "An Abstraction-Based Framework for Neural Network Verification"

Patent issued: "Detecting Mobile Device Sensor Malfunctions" (10,591,313)

SDTimes & Economic Times highlighting our research.

Patent issued: "Extend GPU/CPU coherency to multi-GPU cores" (10,521,349)

FORMER STUDENTS

MS advisor: Akhilesh Gupta, University of Pennsylvania -> Apple

MS advisor: Sam Weintraub, University of Pennsylvania -> Outrider

PhD committee member: Mohammad Mejbah ul Alam -> Intel Labs

PhD committee member: Wenjia Ruan, Lehigh University -> Qualcomm

PhD co-advisor: Irina Calciu, Brown University -> VMWare Research

PhD committee member: Maaz Ahmad -> Adobe Research