- I have uploaded an arxiv draft on a game-theoretic analysis of adversarial examples and robust classifiers. I'll be presenting this work at the NIPS workshop on Machine Deception.
- ACML 2017 was a successful convention with many interesting invited talks and papers. The next conference will take place in Beijing, 2018.
- I'm teaching CSE5522 (AI2) in SP'18, WedFri 9:35-10:55AM. Please check here for a brief description of the course.
- I'm on the program committee of AISTATS'18.
- The paper titled Minimax Filter: Learning to Preserve Privacy from Inference Attacks was accepted to the Journal of Machine Learning Research.
- I'm on the program committee of AAAI'18.
- I'm teaching Machine Learning and Statistical Pattern Recognition (CSE5523) for Autumn 2017.
- I'm on the program committee of NIPS'17.
- I'm teaching Machine Learning and Statistical Pattern Recognition (CSE5523) for Spring 2017.
- We (with Misha and Per as co-PIs) have won the OSU Translational Data Analytics Seed Grant 2017.
- I'm serving as workshop chair of ACML'17 with Krikamol Muandet.
- Our papers titled Enhancing Utility and Privacy with Noisy Minimax Filters and Crowd-ML: a Library for Privacy-preserving Machine Learning on Smart Devices will be presented at the ICASSP'17.
- Our paper titled "Fluid Dynamic Models for Bhattacharyya-based Discriminant Analysis" is accepted for IEEE TPAMI.
- We (with Misha as co-PI) have received a funding from OFRN-C4ISR titled "Human-centered Big Data", representing OSU in the multi-university team of researchers.
- I'm on the program committee of PMPML'16.
- Gordon's paper titled "A large-scale study in predictability of daily activities and places" is accepted for Mobicase'16.
- I'm on the program committee of AISTATS'17.
- I'm on the program committee of AAAI'17.
- I'm teaching CSE5522 (AI2) for AU16. The course website is on Carmen.
- We published the open source code on GitHub for differentially private crowd-based machine learning. The codes are loosely based on the ICDCS'15 paper.
- I published the open source code on GitHub for Geodesic Registration on Anatomical Manifolds which appeared in MedIA'10.
- News from earlier...
All aspects of Machine Learning. Specific topics include the following:
- Privacy-Preserving Machine Learning
- Adversarial Learning and Minimax Optimization
- Distributed Machine Learning and IoT
- Nonlinear Dimensionality Reduction and Manifold Learning
- Medical Image Analysis and Computational Anatomy
- Automated Facial Expression Analysis
You can find the list of publications from Google scholar.
- Ph.D. in Electrical Engineering, University of Pennsylvania, 2008
- M.S. in Biomedical Engineering, Seoul National University, 2001
- B.S. in Electrical Engineering, Seoul National University, 1997
- Google Internet of Things (IoT) Technology Research Pilot Award, 2016
- Single PI. Access to developer resource
- Finalist, MICCAI Young Scientist Publication Impact Award, 2013
- Best Paper Award, MedIA-MICCAI, 2010
- "GRAM: A Framework for Geodesic Registration on Anatomical Manifolds"
- 1st place (out of 804 submissions), 1st author
- Translational Data Analytics Seed Grant, 2017
- "Quantifying the structure of human experience with data streams from smartphones for early detection of Alzheimer’s disease"
- PI (with Co-PIs Belkin and Sederberg (psych)), $30,000
- Ohio Federal Research Network, C4ISR, 2016
- "Human-Centered Big Data"
- PI (with Co-PI Belkin), $168K for 2 years
- Multi-university team (WSU as the main university), $1.2M
- NSF EAGER, 2015
- "The Exploration of Geometric and Non-Geometric Structure in Data"
- Co-PI (with PI Belkin), $150K for 1 year
- Google Faculty Research Award, 2015
- "Privacy-Preserving Machine Learning for Smart Devices"
- Single PI, $45K gift, award rate = 16.5%
- Defence Research and Development Canada (DRDC), 2014
- "Assessment of Personality Traits from Users' Presence in Social Media"
- Single PI/contractor
- Departmental Research Fellowship, 2002 – 2008
- University Merit Scholarship, 1998 – 2001
Teaching and advising
- CSE 3521/5521: Survey of Artificial Intelligence I: Basic Techniques. The course homepage is hosted on Carmen.
- CSE 5522: Survey of Artificial Intelligence II: Advanced Techniques. The course homepage is hosted on Carmen.
- CSE 5523: Machine Learning and Statistical Pattern Recognition. The course homepage is hosted on Carmen.
- If you are a student interested in machine learning or AI-related projects, please send me your CV.
Please check the courses page for details.
- Workshop co-chair of ACML'17 with Krikamol Muandet
Program Committee and Invited Reviewer:
Neural Information Processing System (NIPS), International Conference on Machine Learning (ICML), Artificial Intelligence and Statistics Conference (AISTATS), Association for the Advancement of Artificial Intelligence (AAAI), Journal of Machine Learning Research (JMLR), IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Neural Networks (TNN), IEEE Transactions on Image Processing (TIP), IEEE Transactions for Information Forensics and Security (TIFS), Neural Networks (NN), Pattern Recognition (PR), International Journal of Pattern Recognition (IJPR), Medical Image Computing and Computer Assisted Intervention (MICCAI), Medical Image Analysis (MedIA).