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102 labs · 35 student voices
Faculties at Waseda University ›
Momoko Hayamizu
0 student voices
The Hayamizu Lab uses the language of discrete mathematics to study problems that arise in biology. Centered on the theory of phylogenetic trees and phylogenetic networks, which represent the evolution of living things, the lab works at the intersection of discrete mathematics, statistics, and biology. This work is expected to help explain phenomena that are also medically important, such as cell differentiation and viral mutation.
Akihiko Hirata, Professor
0 student voices
The Hirata Lab studies amorphous materials, such as glass, in which atoms are arranged without regularity. The lab combines diffraction crystallography experiments, computer simulations using molecular dynamics and Monte Carlo methods, and analysis using topology. Through nanoscale measurement such as electron beam imaging and mathematical analysis, the lab aims to reveal the order hidden in amorphous structures. Amorphous materials are also expected to be useful as electrode materials and solid electrolytes for next-generation batteries.
Jun Muramatsu
0 student voices
The Muramatsu Lab studies the theory of sending information efficiently and securely. In the field known as information theory, the lab works on codes that approach the theoretical limit of communication performance (the Shannon limit) and on methods for securely sharing keys using random numbers. The lab also works on the theory of coding that makes use of the properties of sparse matrices.
Yan Liu, Associate Professor
0 student voices
Based on mathematical statistics, the Liu Lab works on elucidating time-dependent phenomena and developing new methods. Time series analysis is a field that statistically studies uncertain data that changes over time. It is applied in a wide range of fields, including the natural sciences, engineering, economics, financial engineering, and biomedical engineering. The lab aims to predict and make inferences about uncertain targets more accurately.
Hiroshi Ishikawa, Professor
0 student voices
The Ishikawa Lab studies computer vision and pattern analysis. It develops algorithms that allow computers to recognize and understand scenes from images. Using methods such as probabilistic models and graph-based optimization, the lab approaches the mechanisms of recognition mathematically. The lab also works on applications to medical image processing.
Masato Uchida, Professor
0 student voices
The Uchida Lab studies the theory and applications of machine learning. Moving back and forth between theory and applications, the lab aims to clarify the principles and properties of machine learning mathematically. It also conducts empirical research using real-world data.
Naoyasu Ubayashi, Professor
0 student voices
The Ubayashi Lab studies software engineering. Using AI and machine learning, as well as "collective intelligence" that gathers the knowledge of many people, the lab aims to build high-quality software. It works on research on automatically finding and fixing bugs in programs, and on formal methods, which verify software specifications mathematically. Beyond publishing its results as papers, the lab releases practical development support tools as open-source software.
Hironori Kasahara, Professor
0 student voices
The Kasahara Lab studies parallelizing compilers and multicore processors. The lab develops an automatic parallelizing compiler called the "OSCAR compiler" and works on technology that automatically distributes a program across multiple cores so that it runs fast. The lab also conducts research on low power consumption and green computing, including compiler technology that automatically reduces power consumption. The lab also has applications in familiar devices in view, such as medical image processing and driver-assistance systems.
Keiji Kimura, Professor
0 student voices
The Kimura Lab studies multicore processors and automatic parallelizing compilers. The lab pursues ways to run "multicore" processors, which place multiple CPU "cores" on a single chip, with high performance and low power consumption. Jointly with the Kasahara Lab, the lab studies the "OSCAR compiler," which automatically distributes a program across cores, and the multicore processors suited to it. The lab also works on speeding up and reducing the power consumption of a variety of applications on multicores, such as scientific and technical computing and image recognition.
Edgar Simo-Serra, Professor
0 student voices
Simo-Serra Lab researches technologies in machine learning, computer vision, and computer graphics. The lab was established in October 2018 and has accepted students since April 2019. Each year, the lab accepts new students through lab assignment from the Department of Computer Science and Engineering and the Department of Communications and Computer Engineering.
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