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Florian Shkurti Florian Shkurti http://www.cs.toronto.edu/~florian [email protected] +1-905-828-3809 StGeorgeCampus: UTMCampus: 6King’sCollegeRoad 3359MississaugaRoad D.L.PrattBuilding,Office283E DeerfieldHall,Office3066 Toronto,ON,M5S3H5 Mississauga,ON,L5L1C6 CURRENT POSITIONS Assistant Professor (tenure-track) Dec 2018- Department of Computer Science, University of Toronto Mathematical & Computational Sciences, University of Toronto Mississauga University of Toronto Institute for Aerospace Studies (Cross-Appointment) Director, Robot Vision & Learning (RVL) Lab Scientific Advisory Board Sept 2018- Propagator Ventures Faculty Member May 2019- University of Toronto Robotics Institute Faculty Affiliate Sept 2019- Vector Institute EDUCATION Ph.D. ComputerScience&Robotics,McGillUniversity 2012-2018 Thesis: Algorithms and Systems for Robot Videography with Human Specifications Supervisor: Gregory Dudek, GPA 4.0/4.0 Committee: Joelle Pineau, Doina Precup, Michael Langer M.Sc. ComputerScience&Robotics,McGillUniversity 2009-2011 Thesis: 3D Simultaneous Localization and Mapping (SLAM) using Visual and Inertial Measurements, GPA 4.0/4.0 Supervisors: Gregory Dudek & Ioannis Rekleitis H. B.Sc. ComputerScience&Mathematics,UniversityofToronto 2005-2009 AWARDS AmazonResearchAward,Robotics,International 2021 ConnaughtNewResearcherAward,Institutional 2021 OutstandingReviewer,CVPR,International 2021 BestPaperAward,RSS,Self-SupervisedRobotLearningWorkshop,International 2020 AlexanderGrahamBellCGSDoctoral(CGS-D)Award,NSERC,National 2014-2016 1 GraduateStudentExcellenceAward,McGill,Institutional 2013-2016 AAAIRoboticsFellowship,International 2015 FQRNTDoctoralAward,McGill,Provincial 2013-2014 LorneTrottierScienceAcceleratorFellowship,McGill,Institutional 2014 GREATAward,McGill,Institutional 2015,2017 WalterSumnerFoundationAward,McGill,National 2011-2013 Provost’sGraduateFellowship,McGill,Institutional 2009 Dean’sHonorList,UofT,Institutional 2006-2009 WoodsworthCollegeStudentAssociationAward,UofT,Institutional 2008 TrenwithAwardinComputerScience,UofT,Institutional 2007 CoxeterScholarshipinMathematics,UofT,Institutional 2007 ExceptionalHighSchoolStudentAward,Eurobank,Athens,Greece,National 2005 PROFESSIONAL EXPERIENCE 2010-18 Robotics Researcher, Mobile Robotics Lab, McGill University. Designed, implemented, and analyzed algorithms for control and motion planning under uncertainty. Extensive experience with robust estimation algorithms and probabilistic modeling. Extensive experience with vision-based 3D reconstruction, coupled with inertial measurements. Designed and deployed robotics systems in challenging outdoor environments (underwater, air, deserts). Experience with machine learning techniques for representation learning, reinforcement learning, variational inference, sampling, inverse reinforcement learning etc. Supervised by Prof. Gregory Dudek. 2016-17 Robotics Consultant, Independent Robotics Inc. Montreal, QC. Provided integration and debugging services for software and hardware systems. 2015-16 Co-Inventor of a hardware and software 3D mapping system. Montreal, QC. Integrated machine-vision cameras with an IMU and a mobile GPU. Created a stereo vision and IMU SLAM system. Won $20,000 in startup funding. 2015 Software Engineering Consultant, Lemay-Yates Associates Inc, Montreal, QC. Supervised by Robert Yates and Johanne Lemay. Provided systems review services for simulators of electromagnetic spectrum auctions. 2009 Undergraduate Software Engineer, University of Toronto, ON. NSERC USRA, advised by Prof. Gregory Wilson. Implemented parts of Basie, a project management portal for classroom use that includes wiki pages, mailing lists, code reviews, and source code browsers. 2008 Software Engineering Intern, Google Inc. Mountain View, CA. Ads Quality Team, supervised by Simon Favreau-Lessard and Michelle Levesque. Developed software infrastructure for statistical experiments. 2007 Undergraduate Software Engineer, University of Toronto, ON. Google Summer of Code award. Advised by Prof. Karen Reid and Jason Montojo (IBM). 2006 Undergraduate Research Assistant. A.U.G. Signals, Toronto, ON. NSERC Industrial USRA, supervised by Dr. George Lampropoulos. Designed 2 signal-processing filters for the classification of spectral signatures of different types of terrains and plants. RESEARCH STATEMENT My research spans mobile robotics, machine learning, planning and control. My goal is to develop machine learning and perception methods that enable robots to reason and operate efficiently and safely, particularly in outdoor environments and alongside humans. To this end, I am working on planning and control methods that improve with experience, and on safe behaviors learned from high-fidelity physics and rendering simulators. When human supervision and human-robot interaction are necessary, I want to enable people to effectively specify the desired task and behavior of their robots through as few interactive demonstrations as possible, without requiring them to write code. I work on the following topics: Autonomous visual Visual exploration navigation and visual search Inverse RL and AI alignment Imitation learning Task and from videos motion Video Autonomous robots for Field planning summarization environmental monitoring robotics Machine learning for Shared planning and control autonomy Learning to search Active sensing Collaborative human- and information robot environmental Likelihood-free gathering monitoring Continual inference learning Safe RL and exploration Verification Robust control Safety guarantees Differentiable during learning sensor simulation Adversarial and deployment simulation scenarios Risk Rare event estimation generation One of the applications of my research has been to enable environmental monitoring by robots that autonomously operate in the field and collect useful data for environmental scientists. Human-robot 3 collaboration, learning from a few demonstrations, and robust navigation in 3D are critical in these outdoor domains. Another application has been in automatically generating simulation environments for self-driving cars, which in many cases today is done semi-manually and in ways that do not facilitate optimization in high dimensions. PUBLICATIONS Submitted Conference Papers (Under Review) ICRA ’22 Learning to Search from Experience in Task and Motion Planning. Mohamed Khodeir*, Ben Agro*, Florian Shkurti. 8 pages. ICRA ’22 Accounting for Unpredictability in Autonomous Driving Behaviour. Sepehr Samavi, Florian Shkurti, Angela Schoellig. 8 pages. ICRA ’22 Gradient-based Synthesis of Adversarial Environments and Scenarios for Au- tonomous Driving. Yasasa Abeysirigoonawardena*, Sally Chen*, Siyun Li, Ruiqi Wang, Florian Shkurti. 8 pages. ICRA ’22 Augmenting Offline Experience for Imitation Learning via Equivariant Repre- sentations. Dhruv Sharma, Alihusein Kuwajerwala, Florian Shkurti. 8 pages. NeurIPS ’21 SLIC: Self-Supervised Learning with Iterative Clustering for Human Action Videos. Salar Hosseini Khorasgani, Yuxuan Chen, Florian Shkurti. 21 pages. Peer-Reviewed Conference Papers CoRL ’21 Taskography: Evaluating Robot Task Planning over Large 3D Scene Graphs. [C.31] Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti. 13 pages. CoRL ’21 Seeing Glass: Joint Point-Cloud and Depth Completion for Transparent Objects. [C.30] Haoping Xu, Yi Ru Wang, Sagi Eppel, Alan Aspuru-Guzik, Florian Shkurti, Animesh Garg. 19 pages. Oral presentation, top 6.5% of accepted papers ICCV ’21 Physically Plausible Human Motion Estimation for Learning Motion Synthesis [C.29] from Video. Kevin Xie, Tingwu Wang, Umar Iqbal, Yunrong Guo, Sanja Fidler, Florian Shkurti. International Conference on Computer Vision. 17 pages. IROS ’21 Latent Attention Augmentation for Robust Autonomous Driving Policies. Chris [C.28] Agia, Ran Cheng, David Meger, Florian Shkurti, Gregory Dudek. IEEE Interna- tional Conference on Robots and Intelligent Systems. 8 pages. 4 ICLR ’21 Conservative Safety Critics for Exploration. Homanga Bharadhwaj, Aviral [C.27] Kumar, Nick Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg. Inter- national Conference on Learning Representations. 25 pages. ICLR ’21 gradSim: Differentiable Physics and Rendering Engines for Parameter Esti- [C.26] mation from Video. Krishna Jatavallabhula, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine, Jerome Parent- Levesque, Kevin Xie, Kenny Erleben, Liam Paull, Florian Shkurti, Sanja Fidler, Derek Nowrouzezahrai. International Conference on Learning Representa- tions. Top 15% of accepted papers. 25 pages. ICLR ’21 Latent Skill Planning for Exploration and Transfer. Kevin Xie*, Homanga [C.25] Bharadhwaj*, Danijar Hafner, Animesh Garg, Florian Shkurti. International Conference on Learning Representations. 13 pages. ICRA ’21 Continual Model-Based Reinforcement Learning with Hypernetworks. Yizhou [C.24] Huang, Kevin Xie, Homanga Bharadhwaj, Florian Shkurti. IEEE International Conference on Robotics and Automation. 13 pages. ICRA ’21 LEAF: Latent Exploration Along the Frontier. Homanga Bharadhwaj, Ani- [C.23] mesh Garg, Florian Shkurti. IEEE International Conference on Robotics and Automation. 20 pages. ICRA ’21 Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations [C.22] using Generative Models. Yuchen Wu, Melissa Mozifian, Florian Shkurti. IEEE International Conference on Robotics and Automation. 7 pages. CVPR ’21 LOHO: Latent Optimization of Hairstyles
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