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Poster Session
Rishav Chourasia · Yichong Xu · Corinna Cortes · Chien-Yi Chang · Yoshihiro Nagano · So Yeon Min · Benedikt Boecking · Phi Vu Tran · Seyed Kamyar Seyed Ghasemipour · Qianggang Ding · Shouvik Mani · Vikram Voleti · Rasool Fakoor · Miao Xu · Kenneth Marino · Lisa Lee · Volker Tresp · Jean-Francois Kagy · Marvin Zhang · Barnabas Poczos · Dinesh Khandelwal · Adrien Bardes · Evan Shelhamer · Jiacheng Zhu · Ziming Li · Xiaoyan Li · Dmitrii Krasheninnikov · Ruohan Wang · Mayoore Jaiswal · Emad Barsoum · Suvansh Sanjeev · Theeraphol Wattanavekin · Qizhe Xie · Sifan Wu · Yuki Yoshida · David Kanaa · Sina Khoshfetrat Pakazad · Mehdi Maasoumy

Fri Dec 13 11:55 AM -- 12:30 PM (PST) @

Author Information

Rishav Chourasia (National University of Singapore)
Yichong Xu (Carnegie Mellon University)
Corinna Cortes (Google Research)
Chien-Yi Chang (Stanford University)
Yoshihiro Nagano (The University of Tokyo)
So Yeon Min (MIT)
Benedikt Boecking (Carnegie Mellon University)

I'm a PhD student in Robotics at Carnegie Mellon University, where I'm a member of the Auton Lab advised by Artur Dubrawski. I am interested in the technical and theoretical aspects of how we engage domain experts in building and training Machine Learning models. In my current research projects I develop methods for data exploration (semi-supervised clustering) and label acquisition (active learning, interactive learning). In the past, I have also worked on algorithms, tools, and data analysis to help fight sex trafficking using deep web and dark web data.

Phi Vu Tran (Flyreel)

Machine Learning Scientist

Seyed Kamyar Seyed Ghasemipour (University of Toronto, Vector Institute)
Qianggang Ding (Peng Cheng Laboratory)
Shouvik Mani (C3.ai)
Vikram Voleti (Mila, University of Montreal)

I am a PhD candidate at Mila, University of Montreal, and a Research Intern at Meta AI. I work on generative models of images, 3D and video. My recent work is on score-based denoising diffusion model for video prediction, generation and interpolation.

Rasool Fakoor (Amazon)
Miao Xu (RIKEN AIP)
Kenneth Marino (Carnegie Mellon University)
Lisa Lee (Carnegie Mellon University)
Volker Tresp (Siemens AG)
Jean-Francois Kagy (Google)
Marvin Zhang (UC Berkeley)
Barnabas Poczos (Carnegie Mellon University)
Dinesh Khandelwal (Indian Institute of Technology Delhi)

am a PhD student in the Department of Computer Science and Engineering at IIT Delhi. My supervisors are Dr. Parag Singla and Dr. Chetan Arora. My broad interests lie in the area of machine learning. Specifically, I have worked in the applications of Deep Learning and Graphical Models to Computer Vision problems. My current work focuses on how to incorporate test time evidence to improve predictions of Deep Networks. In past, I worked on designing efficient algorithms for MAP inference and scaling up the parameter learning in Graphical Models. During my master's at IISc Bangalore, I have worked with Prof. Chiranjib Bhattacharyya

Adrien Bardes (Ecole Normale Superieure Paris-Saclay)
Evan Shelhamer (Adobe)
Jiacheng Zhu (Carnegie Mellon University)
Ziming Li (University of Amsterdam)
Xiaoyan Li (University of Ottawa)
Dmitrii Krasheninnikov (University of Amsterdam)
Ruohan Wang (Imperial College London)
Mayoore Jaiswal (IBM)
Emad Barsoum (Microsoft)

Emad Barsoum is an Architect at Microsoft AI Platform team. He leads the deep learning framework effort in Microsoft and help driving Microsoft strategy in AI. Prior to that Emad was Principal SDE and Applied Researcher in the Advance Technology Group at Microsoft Research. He was one of the core developer and researcher behind the Emotion Recognition algorithm used in MS Cognitive Service for both still image and video. Before that, He was one of the main Architects for NUI API on Xbox One, and the tech lead for the depth reconstruction pipeline for Kinect v2. Furthermore, He developed fitness algorithm from skeleton poses and helped develop real-time image segmentation algorithm for Kinect v2, both shipped as part of Kinect SDK. His current research focuses are in computer vision and deep learning algorithms, especially in the area of emotion recognition, activity detection/recognition and unsupervised learning. He has given numerous internal and external talks on Deep Learning and Computer Vision.

Suvansh Sanjeev (UC Berkeley)
Theeraphol Wattanavekin (Google)
Qizhe Xie (CMU, Google Brain)
Sifan Wu (Tsinghua University)
Yuki Yoshida (The University of Tokyo)
David Kanaa (Ecole Polytechnique Montreal)
Sina Khoshfetrat Pakazad (C3.ai)
Mehdi Maasoumy (C3.ai)

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