I'm Tatsuki Koga, a 3rd-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 - Present (Expected Graduation 2025): 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
- Koga, T., Meehan, C. & Chaudhuri, K.
"Privacy Amplification by Subsampling in Time Domain".
25th International Conference on Artificial Intelligence and Statistics (AISTATS), Virtual, Mar. 2022
- 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
- Apple Inc., ML Engineer Intern, Summer 2022
- • Worked at Private Federated Learning (PFL) team and worked on building language models (LM) in PFL.
- Conducted research on domain adaptation technique for LM in PFL to deal with the setting where we have smaller population size for specific use-cases.
- 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
- Conducted 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
- Conducted 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 Intern, 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 Intern, Summer 2017