RPL Department Robotics, Perception, and Learning Department

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Cheng Zhang Education Address: Rådmansgatan 8a LGH 1101 11425, Stockholm Sweden Email: chengz@kth.se URL: http://cheng-zhang.org/ PhD, KTH Royal Institute of Technology; Dec. 2011 - Sep.

1 Cheng Zhang Education Address: Rådmansgatan 8a LGH , Stockholm Sweden URL: PhD, KTH Royal Institute of Technology; Dec Sep RPL Department Robotics, Perception, and Learning Department School of Computer Science and Communication Research directions: Machine Learning, Computer Vision Supervisor: Prof. Hedvig Kjellström Co-supervisor: Lecturer. Carl Henrik Ek Master of Science, KTH Royal Institute of Technology; Aug Sep System, Control and Robotics Program; School of Electrical Engineering Bachelor of Science, Beijing Jiao Tong University (BJTU); Sep Jul Major: Mechanism Manufacturing and Mechanical Automatization; Minor: Logistics; School of Economics and Management Experience Researcher, Microsoft Research, Cambridge; Mar present Machine Intelligence and Perception Group Research Topic: Machine Learning and applications Postdoctoral Research Associate, Disney Research Pittsburgh; Jan Dec Machine Learning Group Advisor: Dr. Stephan Mandt Research Topic: Probabilistic Modelling and Approximate Inference Researcher, KTH Royal Institute of Technology; Sep Feb RPL Department Robotics, Perception, and Learning Department Advisor: Hedvig Kjellström Research Topic: Machine Learning in Health Care Researcher, Research Project under Mentor4Research; May Dec Research Project on Online Diagnose. Collaborative Project together with MD. PhD. Bo Christer Bertilson from Karolinska Institutet (KI). Research Intern, Microsoft Research Cambridge; Jun Sep Infer.Net team, Machine Learning and Perception Group Hosts: John Bronskill, Yordan Zaykov, Tomas Minka Research Topic: Generative Group Recommendation System Visiting Research Fellow, University of Sheﬃeld; Oct Nov Translational Neuroscience Department Hosts: Dr. James Hensman, Prof. Neil Lawrence, Prof. Magnus Rattray Research Topic: Inference of Transcript Expression Using RNA-seq Data

2 Research Engineer, KTH Royal Institute of Technology; Jul Nov RPL Department Robotics, Perception, and Learning Department Advisor: Prof. Hedvig Kjellström Research Topic: 3D Object Detection with Kinect Research Engineer, KTH Royal Institute of Technology; Jun Sep RPL Department Robotics, Perception, and Learning Department Advisor: Marianna Madry, Prof. Hedvig Kjellström, Prof. Danica Kragic Research Topic: Object Classification and Cue Integration Intern, Cummins (China) Investment Company Limited; Jul May Precision Command System (PCS) Team PCS is an enterprise information system Publication Advances in Variational Inference, C. Zhang, J. Butepage, H. Kjellstrom and S. Mandt, IEEE Transactions on Pattern Analysis and Machine Intelligence (in review) 2017 Causal Feature Selection for Individual Characteristics Prediction T. Ding, C. Zhang and M. Bos, Diversified Mini-Batch Sampling using Repulsive Point Processes C. Zhang, C. Oztireli and S. Mandt NIPS Workshop on Advances in Approximate Bayesian Inference, 2017 Causality Refined Diagnostic Prediction M. Klasson, K. Zhang, B. Bertilson, C. Zhang and H. Kjellström NIPS Workshop on Machine Learning for Health (ML4H), 2017 Perturbative Black Box Variational Inference C. Zhang*, R. Bamler*, M. Opper and S. Mandt* (* indicates equal contribution) Conference on Neural Information Processing Systems (NIPS) 2017 Determinantal Point Processes for Mini-batch Diversification C. Zhang, H. Kjellström and S. Mandt Uncertainty in Artificial Intelligence (UAI 2017). (accepted as plenary talk) Bridging Medical Data Inference to Achilles Tendon Rupture Rehabilitation A. Qu, C. Zhang, P. Ackermann and H. Kjellström NIPS Workshop on Machine Learning for Health, 2016 Balanced Population Stochastic Variational Inference C. Zhang, S. Mandt and H. Kjellström NIPS Workshop on Advances in Approximate Bayesian Inference, 2016 Structured Representation Using Latent Variable Models C. Zhang PhD Thesis, 2016 Diagnostic Prediction Using Discomfort Drawing with IBTM C. Zhang, H. Kjellström, C.H. Ek and B.C. Bertilson Machine Learning in Health Care (MLHC), 2016

3 Inter-Battery Topic Representation Learning C. Zhang, H. Kjellström and C.H. Ek European Conference on Computer Vision (ECCV), 2016 Diagnostic Prediction Using Discomfort Drawing with Multimodal Topic Model C. Zhang, H. Kjellström, and B.C. Bertilson UAI Workshop on Machine Leaning for Health, 2016 GroupBox: A Generative Model for Group Recommendation C. Zhang, M. Gartrell, T. P. Minka, Y. Zaykov and J. Guiver Microsoft Research Technical Report; MSR-TR How to Supervise Topic Models C. Zhang and H. Kjellström ECCV 2014 Workshop on Graphical Models in Computer Vision (oral) Supervised Hierarchical Dirichlet Processes with Variational Inference C. Zhang, C.H. Ek, X. Gratal, F. T. Pokorny and H. Kjellström IEEE ICCV 2013 Workshop on Inference for Probabilistic Graphical Models (oral) Contextual Modeling with Labeled Multi-LDA C. Zhang, D. Song and H. Kjellström IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013 Factorized Topic Models C. Zhang, C.H. Ek and H. Kjellström International Conference on Learning Representations (ICLR), 2013 Multi-Class Detection and Segmentation of Objects in Depth C. Zhang and H. Kjellström Grant & Awards Stiftelsen Promobilia PhD Research Grant; Principal Investigator (PI) Grant period: Mar Mar Received SEK ( around USD) grant for research on efficient and robust inference algorithms for computer vision with big data. Vinnova Grant Challenge-driven innovation - Step 1 ; Co-PI Grant period: Nov Aug Received SEK (around USD) grant from Vinnova for machine learning on pain diagnoses together with MD.PhD. Bo Christer Bertilson (KI). Stiftelsen Promobilia Research Project Grant; Principal Investigator (PI) Grant period: Aug Aug Received SEK (around USD) grant from Stiftelsen Promobilia for automatic object and scene understanding. NVIDIA Hardware Grant; Jan. 2015

4 Winner of KTH innovation competition; Oct Received SEK (around USD) award. Member of Winning Team of Best Hackathon project; Jul One Week Hackathon; Microsoft Research Cambridge Excellent Student in Study Scholarship, BJTU; Sep Excellent Student in Social Activities Scholarship, BJTU; Sep Talks Extracurricular Activity Microsoft Research, Cambridge; Sep University of Cambridge; Sep University of California, Santa Barbara (UCSB); May HiQ Stockholm; Dec IDA Machine Learning Seminars, Linköping University; Nov Disney Research Pittsburgh; Aug Swedish Defence Research Agency (FOI); Jan Stanford University; Dec The Royal Swedish Academy of Engineering Sciences (IVA); Nov KTH Innovation & founder.org; Dec Microsoft Research Cambridge; Sep The University of Sheffield; Sep Stockholm University; June Served as reviewer for: The Journal of Machine Learning Research (JMLR) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) EES Pattern Recognition International Conference on Machine Learning (ICML) International Conference on Learning Representations (ICLR) Conference on Neural Information Processing Systems (NIPS) European Conference on Computer Vision (ECCV) Conference on Computer Vision and Pattern Recognition (CVPR) International Conference on Computer Vision (ICCV) IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) IEEE International Conference on Robotics and Automation (ICRA) Teaching Assistant for: Image Analysis and Computer Vision, KTH; Applied Programming and Computer Science, KTH; 2014 Advanced Machine Learning, KTH; 2015 Decision Support System, KTH; 2016 Image Based Recognition and Classification, KTH; 2016 Machine Learning Reading group (co-organizer), KTH; PhD student supervision: Marcus Klasson (co-supervisior; main-supervisor: Prof. Hedvig Kjellström) Internship project supervision: David Wang (co-supervisior; main-supervisor: Stephan Mandt)

5 Tao Ding (co-supervisior; main-supervisor: Maarten Bos) Judith Butepage (co-supervisior; main-supervisor: Stephan Mandt) Marcus Klasson (co-supervisior; main-supervisor: Rafael Tena) Tianfan Fu (co-supervisior; main-supervisor: Stephan Mandt) Master and Bachelor thesis supervision: Tong Sheng (co-supervisior; main-supervisor: Prof. Hedvig Kjellström) Saad Eddin (main supervisor) Lan Wang (main supervisor) John Pertoft (co-supervisior; main-supervisor: Prof. Hedvig Kjellström) Kerry Zhang (co-supervisior; main-supervisor: Prof. Jussi Karlgren) An Qu (main supervisor) Charles Hamesse (main supervisor; examinar: Prof. Hedvig Kjellström) Ruibo Tu (main supervisor; examinar: Prof. Hedvig Kjellström) Language Skill IT Skill Interests Mandarin: Native speaker English: Fluent business English spoken/written Swedish: Basic communication Skilled in C++, Matlab, Bash script, Python and C# Painting: Have learned painting for 7 years. Draw as a hobby. Sport: Regular physical exercise. Have finished races, e.g. Stockholm half marathon, Pittsburgh half marathon.

Changyin Zhou. Ph.D, Computer Science, Columbia University Oct 2012

Changyin Zhou. Ph.D, Computer Science, Columbia University Oct 2012 Changyin Zhou Software Engineer at Google X Google Inc. 1600 Amphitheater Parkway, Mountain View, CA 94043 E-mail: changyin@google.com URL: http://www.changyin.org Office: (917) 209-9110 Mobile: (646)