I'm Tatsuki Koga, a first-year Ph.D. student in Computer Science at University of California San Diego, advised by Prof. Kamalika Chaudhuri.
My research interests are machine learning with privacy guarantees, under a class imbalance, and for medical applications.
I have obtained my B.S. in Information Science at the University of Tokyo in March 2020.
Talk & Slides
- 2020.9 - : Ph.D. in Computer Science, University of California San Diego
- 2016.4 - 2020.3: B.S. in Information Science, The University of Tokyo
- 2018.4 - 2020.3: School of Science, Dept. of Information Science
- 2016.4 - 2018.3: College of Arts and Sciences
- 2013.4 - 2016.3: Tokyo Gakugei University Senior High School
- RIKEN Medical Science Innovation Hub Program (MIH), AI based Healthcare and Medical Data Analysis Standardization Unit, Research Part-time Worker II, Fall 2017 - Summer 2020
- Conducting research on generating medical data (clinical data, images) fed into machine learning methods with GANs in order to resolve the imbalance of the classes in datasets.
- RIKEN Advanced Intelligence Project (AIP), AI Security and Privacy Team, Student Trainee, Spring 2018 - Summer 2020
- Conducting research on differentially private deep neural network, especially generative models for medical data and its tradeoff between model’s utility and privacy.
- Yahoo Japan Corporation, Software Engineer, Summer 2017
- Developed library to collect various user information for Android applications, implemented in Java.
- Received the Best Performance Award.
- PKSHA Technology Inc., Software Engineer, Summer 2017
- Developed a chatbot dialogue system (natural language processing) to be embedded in a robot.
- Koga, T., Meehan, C. & Chaudhuri, K.
"Privacy Amplification by Subsampling in Time Domain".
TPDP 2021 - Theory and Practice of Differential Privacy at 38th International Conference on Machine Learning (ICML), Virtual, Jul. 2021.
- Koga, T., Rie, E., Hirose, K. & Seita, J.
“Human and GAN collaboration to create haute couture dress”.
NeurIPS Workshop on Machine Learning for Creativity and Design 3.0 at 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, Dec. 2019. Contributed Talk.
- Koga, T., Nonaka, N., Sakuma, J. & Seita, J.
“General-to-Detailed GAN for Infrequent Class Medical Images”.
ML4H: Machine Learning for Health Workshop at 32nd Conference on Neural Information Processing Systems, Montreal, Canada, Dec. 2018.
- TOKYO Fashion Week 2019 A/W Collection by EMarie, February 2019
- Dean's Award from School of Science, the University of Tokyo, March 2020
- top ~5%; only 2 recipients from Department of Information Science (16 in total from School of Science).
- health++ (Stanford Health Hackathon) Best Use of Intel API 3rd Place Award, November 2018