Advanced Intelligent System for Recognition in Real-world, ContentsGeneration and Knowledge Discovery

Overview

The Harada, Kurose, and Mukuta Laboratory aims to build advanced intelligent systems capable of understanding the real world, generating content, and discovering knowledge by extracting meaningful information from physical environments and connecting it with vast data and computing resources in cyberspace.
With a team of around 60 members, including faculty and students, our lab conducts research across a broad range of computer science fields, integrating mathematical foundations and robotics.

Our core research areas and keywords include:
◆ Mathematical Foundations:
Information theory, machine learning, deep learning, data mining, pattern recognition, probability and statistics, time-series analysis, causal inference, learning theory, and feature extraction theory.

◆ Perception, Understanding, and Reasoning:
Big data, computer vision, image recognition and retrieval, 3D information processing, action recognition, multimodal recognition, emotion understanding, natural language processing, speech and music processing, and medical information analysis.

◆ Content Generation:
Natural language description and summarization of images/videos, image generation from text, conversational dialogue systems, and automatic article creation based on interesting real-world phenomena.