Full Academic Cv: Grigori Fursin, Phd
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FULL ACADEMIC CV: GRIGORI FURSIN, PHD Current position VP of MLOps at OctoML.ai (USA) Languages English (British citizen); French (spoken, intermediate); Russian (native) Address Paris region, France Education PhD in computer science with the ORS award from the University of Edinburgh (2004) Website cKnowledge.io/@gfursin LinkedIn linkedin.com/in/grigorifursin Publications scholar.google.com/citations?user=IwcnpkwAAAAJ (H‐index: 25) Personal e‐mail [email protected] I am a computer scientist, engineer, educator and business executive with an interdisciplinary background in computer engineering, machine learning, physics and electronics. I am passionate about designing efficient systems in terms of speed, energy, accuracy and various costs, bringing deep tech to the real world, teaching, enabling reproducible research and sup‐ porting open science. MY ACADEMIC RESEARCH (TENURED RESEARCH SCIENTIST AT INRIA WITH PHD IN CS FROM THE UNIVERSITY OF EDINBURGH) • I was among the first researchers to combine machine learning, autotuning and knowledge sharing to automate and accelerate the development of efficient software and hardware by several orders of magnitudeGoogle ( scholar); • developed open‐source tools and started educational initiatives (ACM, Raspberry Pi foundation) to bring this research to the real world (see use cases); • prepared and tought M.S. course at Paris‐Saclay University on using ML to co‐design efficient software and hardare (self‐optimizing computing systems); • gave 100+ invited research talks; • honored to receive the ACM CGO test of time award, several best papers awards and INRIA award of scientific excel‐ lence. PROJECT MANAGEMENT, SYSTEM DESIGN AND CONSULTING (COLLABORATION WITH IBM, INTEL, ARM, GOOGLE, MOZILLA, GM) • led the development of the world’s first ML‐based compiler and the cTuning.org platform across 5 teams to automate and crowdsource optimization of computer systems (IBM and Fujitsu press‐releases; invitation to help establish Intel Exascale Lab and lead SW/HW co‐design group); • developed a compiler plugin framework that was added to the mainline GCC powering all Linux‐based computers and helped to convert production compilers into research toolsets for machine learning; • developed the Collective Knowledge framework to automate and accelerate design space exploration of AI/ML/SW/HW stacks while balancing speed, accuracy, energy and costs (170K+ downloads); CK helped to automate most of MLPerf inference benchmark submissions for edge devices as mentioned by Forbes, ZDNet and EETimes; • co‐founded an engineering company and led it to 1M+ in revenue with Fortune 50 customers using my CK technology; STARTUPS • founded and developed the cKnowledge.io platform with browser plugins to organize all research knowledge (AI, ML, Systems, quantum) in the form of portable CK workflows, common APIs and reusable artifacts. It helps users quickly find innovative technology, test it and adopt in production (acquired by OctoML.ai). COMMUNITY SERVICE (COLLABORATION WITH ACM, MLPERF AND THE RASPBERRY PI FOUNDATION) • introduced reproducibility initiatives and artifact checklists at MLSys, ASPLOS, CGO, PPoPP and other ML and systems conferences to validate results from published papers; • helped to reproduce 150+ research papers from ML and systems conferences; • developed an open‐source framework to automate MLPerf benchmark submissions; • co‐organized many reproducible competitions, tournaments and hackathons to co‐design efficient ML systems based on my CK technology; • helped to establish the ACM taskforce and SIG on reproducibility; • helped to prepare the ACM artifact review and badging policy. Full academic CV as Interactive HTML Contents 1 PROFESSIONAL EXPERIENCE (J) 3 2 INSTITUTION BUILDING (I) 6 3 EDUCATION (Z) 8 4 EDITOR (ED) 9 5 KEYNOTES (K) 9 6 SOCIAL ACTIVITIES AND COMMUNITY SERVICE (O) 9 7 STARTUPS (C) 10 8 EXAMINER 10 9 EXPERT SERVICE (E) 11 10 MAJOR RESEARCH ACHIEVEMENTS (M) 11 11 PUBLIC OR IN‐HOUSE REPOSITORIES OF KNOWLEDGE (R) 15 12 AWARDS, PRIZES AND FELLOWSHIPS (A) 17 13 MAJOR FUNDING (F) 18 14 MAJOR SOFTWARE AND DATASETS (S) 20 15 HARDWARE (H) 27 16 TALKS (T) 27 17 PARTICIPATING IN PROGRAM AND ORGANIZING COMMITTEES; REVIEWING 32 18 TEACHING AND ORGANIZING COURSES (L) 33 19 ADVISING/COLLABORATING (Q) 33 20 ORGANIZING/CHAIRING EVENTS (E) 36 21 PUBLICATIONS AND OTHER DISSEMINATION MATERIAL (P) 45 21.1 THESES ....................................................... 45 21.2 INTERNATIONAL JOURNALS ............................................. 45 21.3 INTERNATIONAL CONFERENCES ........................................... 47 21.4 INTERNATIONAL WORKSHOPS ............................................ 50 21.5 NATIONAL CONFERENCES AND WORKSHOPS ..................................... 53 21.6 POSTERS ...................................................... 54 21.7 TECHNICAL REPORTS, NEWSLETTERS, EXTENDED ABSTRACTS, INTRODUCTIONS ..................... 55 21.8 PRESS RELEASES ................................................... 57 2 1 PROFESSIONAL EXPERIENCE (J) # Year Job [J1] 2021‐04 ‐ VP of MLOps at OctoML.ai cur. company website: https://OctoML.ai [J2] 2019‐06 ‐ Founder of cKnowledge.io (acquired by OctoML.ai) building an open knowledge repository about how 2021‐03 to design, benchmark, optimize and use complex computational systems for AI, ML, quantum, IoTand other emerging workloads, accelerate their adoption, and reduce the technical debt The Collective Knowledge portal: https://cKnowledge.io MLPerf crowd‐benchmarking demo: https://cKnowledge.io/test [J3] 2016 ‐ Partner in the AI/ML/SW/HW co‐design project of General Motors (USA) using my CK framework with 2018 the universal autotuning workflow for automated co‐design of Pareto‐efficient software/hardware stacks for AI/ML workloads across diverse models, data set and platforms in terms of speed, accu‐ racy, energy, and costs. GM presentation about my Collective Knowledge technology at the Embedded Vision Summit: https: //www.youtube.com/watch?v=1ldgVZ64hEI [J4] 2015‐07 ‐ Co‐founder and CTO of dividiti (UK) pursuing my vision of self‐optimizing, efficient, reliable and afford‐ 2019‐03 able computing from IoT to supercomputers. We offered professional services based on my Collective Knowledge technology to help our Fortune50 clients and startups automate benchmarking, optimiza‐ tion and co‐design of emerging AI, ML and quantum workloads using my CK framework. The summary of my experience:: https://arxiv.org/abs/2006.07161 Our partners: https://cKnowledge.org/partners [J5] 2014‐11 ‐ Founder, CEO and CSO of the cTuning foundation (France) developing open‐source technology to auto‐ cur. mate AI, ML, computer systems and quantum R&D, and accelerate technology transfer from academia to industry to solve the world’s most challenging problems! • Funded by EU FP7 TETRACOM project [F3] • Sponsored by Microsoft (access to Microsoft Azure cloud) [F1] • Developed Collective Knowledge software and repository [S2, R2] • Received HiPEAC award [A3] • Publications [Pub31] [J6] 2014 ‐ Partner in the EU TETRACOM project of Arm (UK) developing the open‐source Collective Knowledge 2015 framework with a permissive license and validating it in practice with Arm thanks to a 6‐month grant form the EU TETRACOM initiative. I was honored to receive the European technology transfer award for this project. The Collective Knowledge project: https://cKnowledge.org CK framework: https://github.com/ctuning/ck 3 [J7] 2011‐09 ‐ Tenured research scientist (associate professor) at INRIA Saclay (France) directing R&D of the novel 2014‐10 Collective Mind concept for collaborative, systematic and reproducible benchmarking, optimization and co‐design of computer systems using public repository of knowledge, plugin‐based auto‐tuning, run‐time adaptation, big data, predictive analytics, machine learning, data mining, statistical analysis, feature selection, crowdsourcing and collective intelligence • Funded by INRIA 4 year fellowship [A4] • Initiated new publication model supported by HiPEAC where experimental results (tools, data, models) are continuously shared and validated by the community [E25, E27] • Associated software [S3, S10, S4, S5, S6] • Associated publications [Pub63, Pub33, Pub64, Pub65, Pub48, Pub66, Pub49, Pub6, Pub67, Pub50] • Associated events [E23, E25, E26, E28, E29, E30] • Associated public repository of knowledge [R3] [J8] 2010‐03 ‐ Co‐director and the head of the application optimization group in Intel Exascale Lab (France) preparing 2011‐08 the long‐term R&D vision based on my past research while leading the team of 8 researchers, engineers and students • More info about this activity [I2] [J9] 2008‐01 ‐ Visiting scientist in the Institute of Computing Technology of Chinese Academy Of Sciences preparing 2008‐01 collaboration on extending cTuning and MILEPOST technology • Funded by ICT (China) [F8] • Associated publications [Pub6, Pub13, Pub34, Pub36] [J10] 2007‐09 ‐ Tenured research scientist (assistant professor) at INRIA Saclay (France) leading R&D in EU MILEPOST 2010‐02 project on building practical machine learning based research compiler (MILEPOST GCC) and public plugin‐based auto‐tuning framework and repository of knowledge (cTuning.org) • Funded by EU MILEPOST project [F9] • Associated job [J12] • Associated public repository of knowledge [R5] [J11] 2007‐09 ‐ Adjunct professor at University of Paris‐Sud (France) preparing and teaching my novel approach on col‐ 2014‐10 laborative, systematic and reproducible benchmarking, optimization and co‐design of computer sys‐