Curriculum Vitae

Personal Information

AutoDW: Automatic Data Wrangling Leveraging Large Language Models L. Liu, S. Hasegawa, SK. Sampat, M. Xenochristou, WP. Chen, T. Kato, T. Kakibuchi, T. Asai In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2024
Regression-Stratified Sampling for Optimized Algorithm Selection in Time-Constrained Tabular AutoML M. Bahrami, S. Hasegawa, L. Liu, WP. Chen In ICML Workshop on Structured Probabilistic Inference {\&} Generative Modeling, 2024
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
J. Bae, M. R. Zhang, M. Ruan, E. Wang, S. Hasegawa, J. Ba, R. Grosse
In International Conference on Learning Representations (ICLR), 2023
Improving Predicate Representation in Scene Graph Generation by Self-Supervised Learning
S. Hasegawa, M. Hiromoto, A. Nakagawa, Y. Umeda
In IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023

Facilitating the Identification of the Nannofossil Species in Cretaceous of Abu Dhabi Using Artificial Intelligence
H. Tamamura, M. Yamanaka, S. Chiyonobu, G. Yamada, S. Hasegawa, Y. Totake, T. Nanjo
In Abu Dhabi International Petroleum Exhibition & Conference, 2020
Analysis of light absorption characteristics in very-thin single-crystalline silicon solar cells with photonic crystals
S. Hasegawa, K. Ishizaki, Y. Tanaka, and S. Noda
In 78th Japan Society of Applied Physics (JSAP) Autumn Meeting, 2017
Numerical analysis of μc-Si solar cells with photonic crystals formed on top surface -Introduction of asymmetric structure-
S. Hasegawa, K. Ishizaki, Y. Tanaka, A. Motohira, Y. Kawamoto, M. De Zoysa, S. Fujita, and S. Noda
In 63th Japan Society of Applied Physics (JSAP) Spring Meeting, 2016

Apr 2016 ~ Mar 2018: MEng in Electronics at Kyoto University
- Thesis: Fabrication and Evaluation of Thin Single-Crystalline Silicon Solar Cells with Photonic Crystals
- Supervisor: Susumu Noda
Apr 2012 ~ Mar 2016: BEng in Electrical and Electronic Engineering at Kyoto University

Oct 2022 ~ : machine learning researcher at Fujitsu Research of America
- My research is focused on automation of data analysis
Aug 2021 ~ Sep 2022: machine learning researcher at Fujitsu Research
- My research was focused on scene graph generation, self-supervised learning, and generative models
Sep 2019 - Jan 2020: research assistant at SYMBOL
- My work was focused on developing deep learning-based solutions to extract essential information from 3D data (point cloud, mesh, multi-view)
Apr 2018 ~ Jul 2021: software engineer at Fujitsu
- My work was focused on providing deep learning-based solutions with the customers and developing software products using speech processing and computer vision technologies

Project name	Descrption
adeleine	Deep learning-based implementations of line art colorization with hints and without hints. Userhintv2 model in the repository is used in Giga Manga.
senju	Several deep-learning based implementations pertaining to anime. The repository also includes GUI application consisting of Go server and Python modules connected via gRPC.
accela and cyberia	Music digging tools. accela is implemented in TypeScript, and cyberia is done in Python.
AwesomeAnimeResearch	A massive collection of machine learning papers and projects related to anime

Computer Science
- Machine Learning, Deep learning
- Signal Processing: Computer vision, Speech processing
- Low-level Programming: Emulators of NES, GB, CGB
- Programming Language: Python, Go, C
Software Development
- Team development
- OS: Linux(Ubuntu, CentOS), MacOS, Windows
- Tools: Docker, Docker-compose, Git, Gitlab, Github, MySQL, PostgreSQL, MongoDB, Nodejs, gRPC, Nginx, RabbitMQ
Language
- Japanese: native
- English: advanced (TOEFL: 96, IELTS: 7.0, GRE: V153/Q170/AW3.5)