# jemdoc: analytics{UA-3179349-3} ~~~ {}{img_left}{sewoong_venice.jpg}{Photo of Sewoong Oh}{250}{}{} === Sewoong Oh #*Sewoong Oh*\n Associate Professor \n Allen School of Computer Science & Engineering\n University of Washington\n sewoong@cs.washington.edu\n Bill & Melinda Gates Center, room 207\n University of Washington\n Seattle, WA 98195\n ~~~ #I am looking for a graduate student with a strong mathematical background and a strong interest in machine learning. Email me at swoh@illinois.edu if you are interested. #~~~ === News - Excited to be a part of the new NSF AI Institute on Foundations of Machine Learning (led by Adam Klivans and Alex Dimakis starting September 1st 2020) with a great team of colleagues at UW, UT Austin, MSR, and Wichita State University. [https://news.cs.washington.edu/2020/08/26/new-nsf-ai-institute-for-foundations-of-machine-learning-aims-to-address-major-research-challenges-in-artificial-intelligence-and-broaden-participation-in-the-field/ UW news article] - Together with [https://sites.google.com/view/hyejikim Hyeji Kim] and [http://infotheory.ee.washington.edu/ Sreeram Kannan], I had the pleasure of giving a tutorial on ``Information Theory and Deep Learning: an Emerging Interface'' at ISIT June 2018 at Vail, Colorado. Here are the [slide_ISITTutorial2018.pdf Slides]. Here is a [http://youtu.be/t7azfdvGCcc link] to a video recording. - Find out more about [http://swoh.web.engr.illinois.edu/pacgan.html PacGAN], our new principled apporach to mitigate mode collapse in training Generative Adversarial Networks. [slide_pacgan_princeton.pdf slides] and [talk_pacgan_princeton.mp4 video] recording of a talk I gave at Princeton is now available. === About Sewoong Oh is an Associate Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Previous to joining University of Washington in 2019, he was an Assistant Professor in the department of Industrial and Enterprise Systems Engineering at University of Illinois at Urbana-Champaign since 2012. He received his PhD from the department of Electrical Engineering at Stanford University in 2011, under the supervision of Andrea Montanari. Following his PhD, he worked as a postdoctoral researcher at Laboratory for Information and Decision Systems (LIDS) at MIT, under the supervision of Devavrat Shah. Sewoong's research interest is in theoretical machine learning in topics including #Generative Adversarial Networks, blockchains, rumor source obfuscation, matrix and tensor completion, #ranking, crowdsourcing, information quantity estimation, robust statistics, meta-learning, generative adversarial networks, social computing, and differential privacy. He was co-awarded the ACM SIGMETRICS best paper award in 2015, NSF CAREER award in 2016, ACM SIGMETRICS rising star award in 2017, and GOOGLE Faculty Research Award in 2017 and 2020. Here is a more detailed *[./SewoongOhCV.pdf CV]* and *[./papers.html Publications]*. === [./teaching.html Teaching] === Group - Current\n Ashok Makkuva Vardhan\n Kiran Thekumparampil\n Xiyang Liu \n Raghav Somani \n Jonathan Hayase - Alumni \n Weihao Gao (PhD 2019, co-advised with Pramod Viswanath, now at ByteDance)\n Jungseul Ok (PostDoc 2019, now at PosTech)\n Harshay Shah (BS 2019, now at MSR India)\n Hyeji Kim (PostDoc 2018, co-advised with Pramood Viswanath, now at UT Austin)\n Ashish Khetan (PhD 2018, now at Amazon)\n Giulia Fanti (Visiting student 2014-2016, now at CMU)\n Peter Kairouz (PhD 2016, co-advised with Pramod Viswanath, now at Google)