Joel Oren
Applied Researcher And ML Tech Lead
Tel Aviv
Summary
I am an experienced and dedicated applied researcher with broad interests in machine learning. I am passionate about applying my skills in projects that solve real problems, improve over state-of-the-art methods, and make an impact.
Overview
17
17
years of professional experience
27
27
years of post-secondary education
3
3
Languages
Work History
ML Tech Lead
Google-X (The Moonshot Factory)
11.2023 - Current
- Leading all machine learning and software engineering aspects of Project Neptune, X: the moonshot factory, Israel .
- Leading all algorithmic aspects: from ideation, through design, implementation, and analysis. Oversaw efforts that led to marked improvement in main KPI. Led scaling of computational workflows in cloud infrastructure.
- Lead a small team of software engineers for implementing algorithmic solution and backend infrastructure.
- Collaborating with academic advisors.
Senior applied researcher
General Motors
10.2021 - 11.2023
- Took part in various projects that apply object detection and segmentation techniques for detecting lanes on roads.
- Implemented transformer-based lane detection head.
- Designed and implemented various tools that are widely used by entire group.
Research Scientist
Bosch Center for Artificial Intelligence
08.2019 - 10.2021
- Main project: applying methods in deep reinforcement learning, planning, and Graph Neural Networks to optimization problems (e.g., scheduling and routing)
- Implemented agents that combine Deep RL methods (DQN and policy gradient methods), and planning methods (MCTS) for scheduling wafer fabrication processes
- The process was formulated as a traditional scheduling problem, and state representation learned via GNNs
- Results published as a conference paper in SoCS'21.
- Project involved both full-time and student group members in both Germany and Israel (Israel side led by me).
- Key areas of research: reinforcement learning and planning, combinatorial optimization, graph neural networks.
Research Scientist
Yahoo! Research
07.2017 - 08.2019
- Conducted applied research in machine learning projects pertaining to NLP, text classification in big data settings (processing terabytes of data daily)
- Took part in various projects pertaining to monetization of mail products, directly leading to marked increased customer conversions.
- Position included supervision of student interns, and publishing papers in academic conferences (see Publications section).
Research scientist
Wattpad.com
05.2015 - 06.2017
- Algorithm design, machine learning research and recommendation systems
- Applied machine learning techniques for recommending text-based items to users, leading to marked increased in recommendation success rates and user engagment.
- Large-scale computing frameworks in Spark and Hadoop
- Data-driven analytics of user behavior, text analysis, and social interactions
- Select projects: Large scale collaborative filtering recommendations; neural network techniques for classifying and scoring story covers; time series classification: analyzing sequential reading patterns for ranking and classifying stories (breakout detection).
Software Engineer
Superderivatives Inc.
10.2008 - 12.2008
Embedded systems software engineer
LucidLogix
08.2007 - 08.2008
Education
Ph.D. - Computer Science
University of Toronto
Toronto, ON, Canada 04.2001 - 05.2011
Master of Science - Computer Science
University of Toronto
04.2001 - 05.2011
Bachelor of Science - Computer Science
Ben Gurion University
Be'er Sheva, Israel 04.2001 - 05.2008
Skills
PyTorch
undefinedPublications
- Sampling Multiple Nodes in Large Networks: Beyond Random Walks, WSDM'22
- SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems, SoCS'21
- Predicting User Demography and Device from News Comments, SIGIR'21
- Generating Character Descriptions for Automatic Summarization of Fiction, AAAI'19
- Influence at Scale: Distributed Computation of Complex Contagion in Networks, KDD'2015
- The Pricing War Continues: On Competitive Multi-Item Pricing, AAAI'2015
- Efficient Voting via The Top-k Elicitation Scheme: A Probabilistic Approach, EC'2014
- Efficient Vote Elicitation under Candidate Uncertainty, IJCAI'2013
- Truthful Mechanisms for Competing Submodular Processes, WWW'2013
- Threshold Models for Competitive Influence in Social Networks, WINE'2010
Patents
- Determining and presenting user emotion - A Raviv, I Grabovitch-Zuyev, J Oren (2023)
- Automatic electronic message data analysis method and apparatus - A Raviv, J Oren, I Zuyev (2020)
- Systems and methods for efficient electronic message storage and retrieval - A Raviv, I Grabovitch-Zuyev, J Oren (2021)
- Method and system for mailbox-based coupon display - A Raviv, R Wolff, J Oren, N Avigdor-Elgrabli, M Viderman, IM McCARTHY (2024)
- Systems and methods for recommendation generation - A Raviv, I Grabovitch-Zuyev, J Oren (2023)
- Method for generating a state model describing a controllable system - FM Richter, J Oren (2023)
- Device and method for scheduling a set of jobs for a plurality of machines - A Taitler, C Daniel, D Di Castro, FM Richter, J Oren, M Lefarov, NM Dizbin, Z Feldman (2021)
Invited Talks
- Generating Character Descriptions for Automatic Summarization of Fiction, AAAI'2019
- Influence at Scale: Distributed Computation of Complex Contagion in Networks, KDD'2015
- Guest lecture: Social Data-Mining, Harvard University
- Poster presentation at AAAI'2015
- Efficient Voting via The Top-k Elicitation Scheme: A Probabilistic Approach, MSR UK
- A Game-theoretic Analysis of Catalog Optimization, AAAI'2014
- Robust winners and winner determination policies under candidate uncertainty, AAAI'2014
- Online Budgeted Social Choice, AAAI'2014
- Efficient Vote Elicitation under Candidate Uncertainty, IJCAI'2013
- Truthful Mechanisms for Competing Submodular Processes, WWW2013
- Online (Budgeted) Social Choice, COMSOC 2012
- The First Cambridge Computation and Economics Day (2012)
- Truthful Mechanisms for Competing Submodular Processes, Microsoft Research
- Threshold Models for Competitive Influence in Social Networks, WINE 2010
Awards
- The Ray Reiter Award 2015
- The Google-Lime Scholarship 2012
- The Ontario Graduate Scholarship - 2010-2011, 2011-2012, 2013-2014
- The Suzanne Zlotowski award for undergraduate students with exceptional admission merits - 2003
Timeline
ML Tech Lead
Google-X (The Moonshot Factory)
11.2023 - Current
Senior applied researcher
General Motors
10.2021 - 11.2023
Research Scientist
Bosch Center for Artificial Intelligence
08.2019 - 10.2021
Research Scientist
Yahoo! Research
07.2017 - 08.2019
Research scientist
Wattpad.com
05.2015 - 06.2017
Software Engineer
Superderivatives Inc.
10.2008 - 12.2008
Embedded systems software engineer
LucidLogix
08.2007 - 08.2008
Ph.D. - Computer Science
University of Toronto
04.2001 - 05.2011
Master of Science - Computer Science
University of Toronto
04.2001 - 05.2011
Bachelor of Science - Computer Science
Ben Gurion University
04.2001 - 05.2008
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