Leader

Professor Hung-Yu Wei

Room No.

EE-355

Website

Introduction

As wireless communication technology shows enormous potential to affect the way people communicate, we dedicate ourselves to studying and developing communication technology to make communication more convenient and accessible. The Wireless Mobile Network Lab is led by Professor Hung-Yu Wei, involving 6 PhD, 12 MS researchers and 1 administrative assistant, collaboratively pursuing the cutting-edge communication technologies. Our research areas mainly focus on wireless communication, mobile networking, edge/fog computing, and game theoretic models for networking services. We are specialize in
1. 5G/5G+ wireless
2. Multimedia streaming and VoIP over wireless networks
3. IoT (industrial IoT, V2X, smart grid)
4. Edge/Fog computing
5. 5G Security
6. Machine learning for wireless and IoT systems
7. Game theory models for communications and networking
8. 3GPP and IEEE Standards

Leader

Associate Professor Chun-Lin Liu

Room No.

EE-530

Website

Introduction

1. Digital Signal Processing
2. Digital Image Processing
3. Multimedia Signal Processing

Leader

Professor Lin-Shan Lee

Room No.

EE-531

Website

Introduction

1. Core technologies for speech recognition:
New features for speech signals, new models and new frameworks for speech recognition, handling noise and channel effect, improved acoustic modeling and adaptation, improved language modeling and adaptation, spontaneous speech processing, Mandarin-English bilingual speech processing, prosody and tone modeling, etc.

2. Intelligent applications of speech recognition vender network environment:
Speech understanding, spoken dialog modeling and systems, semantic analysis, voice-based information retrieval, speech information summarization and distillation, spoken document understanding and organization, spoken key term extraction, speech synthesis, distributed speech processing technologies, etc.

Leader

Professor Hsuan-Jung Su

Room No.

EE-532

Website

Introduction

Advancement of Communication Theory, Information Theory, Signal Processing Technologies, and their applications.

Leader

Professor Homer H. Chen

Room No.

EE-533

Website

Introduction

The mission of our lab is to develop cutting-edge technology for real-world problems and to give students world-class training in research. Our research projects are related to computational photography and display, big data, music recommendation, and content delivery. The foundation of our technology development includes machine learning, vision science, image processing, audio processing, data science, affective computing, and communication networks.

Leader

Associate Professor Chun-Ting Chou

Room No.

EE-550

Website

Introduction

For more information, please see the website.

Leader

Professor Hung-Yi Lee

Room No.

EE-552

Website

Introduction

Deep Learning, Machine Learning, Spoken Language Understanding, Speech Recognition

Leader

Professor Zsehong Tsai

Room No.

EE-554

Website

Introduction

Architecture Enhancement and Performance Improvement of the Next Generation Broadband Communication Network.

Leader

Professor Yi-Hsuan Yang

Room No.

BL-505

Website

Introduction

Musice information research; Artificial Intelligence; Machine learning; Musice generation

Leader

Professor Tsung-Nan Lin

Room No.

BL-507

Website

Introduction

1. Wireless Communications
2. Wireless Networks
3. Cooperative Communications
4. Indoor Localization

Leader

Professor Shyh-Kang Jeng

Room No.

BL-510

Website

Introduction

Apply results of cognitive science areas like cognitive neuroscience and cognitive psychology to robotics. The goal is to develop an elder-accompany robot and to model human neural systems related dementia.

Leader

Professor Ping-Cheng Yeh

Room No.

BL-515

Website

Introduction

1. PHY of Wireless Communications
2. Cooperative Communications
3. Wireless Multimedia Transmissions
4. PHY Security of Wireless Communications

Leader

Professor Hung-Yun Hsieh

Room No.

BL-521

Website

Introduction

The TONIC Research Group encompasses students with research interests on mobile networking and wireless communications. Ongoing research endeavors include machine-to-machine (M2M) communications, cognitive radio (CR) networks, and next-generation mobile communications technologies.

Leader

Associate Professor Pei-Yuan Wu

Room No.

BL-530

Website

Introduction

Privacy preserving machine learning, Scene text recognition, Deep learning and adversarial examples, Deep learning for image dehazing, Unsupervised?disentangled representations learning, Sample complexity in deep learning.

Leader

Professor Polly Huang

Room No.

BL-621

Website

Introduction

The Network and System Laboratory pursues research towards building robust and scalable communication systems. We dedicate our effort to the design, modeling, simulation, and performance issues of such networked systems. The members of nslab have worked on a wide range of research topics, including multicast routing, network QoS, Internet traffic dynamics, network simulations, Internet topology analysis, and wearable computing. Much of our recent effort concentrates on the following problem domains:

1. Internet Characterization: modeling and simulation of the Internet.
2. Sensor Network: communication of sensor-enriched miniature devices for easy mobile lifestyle.
3. Peer-to-peer Multimedia Network: delivering quality multimedia data over the Internet.

Leader

Professor Jian-Jiun Ding

Room No.

MD-531

Website

Introduction

Digital signal processing, digital image processing, time-frequency analysis, wavelet transform, music signal processing

Leader

Professor Yu-Chiang Frank Wang

Room No.

MKI-514

Website

Introduction

The research focuses of our labs span the areas of computer vision, machine learning, deep learning and artificial intelligence. Our recent research topics include transfer learning, vision and language, 3D vision, meta and self-supervised learning for visual analysis. In addition to publishing works at top-tier conferences and journals in the above fields, we also work closely with industrial partners for making impacts to real-world computer vision problems. Our industrial collaborator in recent years include Google, Qualcomm, ASUS Computer, Inventec, TSMC, Novatek, Chunghwa Telecomm and so on.

Leader

Professor I-Hsiang Wang

Room No.

MKI-515

Website

Introduction

Our group is focused on fundamental research on networked information and data, including communications, computation, data analysis, and machine learning. Areas of our major interest are information theory, learning theory, and high dimensional statistics.
In particular, we are interested in the following subjects:
1. Networked information processing
2. Crowdsourced machine learning
3. Privacy and security in distributed learning
4. Delay-limited and memory-constrained distributed learning

Leader

Professor Che Lin

Room No.

MKI-516

Website

Introduction

iDSSP Lab is the abbreviation of Interdisciplinary Data Science & Signal Process Laboratory. Our research is about interdisciplinary data science and signal processing, which could be mainly classified into Bioinformatic Data Analysis and Financial Technology Data Analysis. Our research is based on AI applications and deep learning to develop interdisciplinary applications.

Leader

Assistant Professor Shao-Hua Sun

Room No.

MKI-518

Website

Introduction

Our research focuses on developing interpretable and generalizable robot learning algorithms and frameworks that enable robots to acquire long-horizon and complex skills with hierarchical structures, such as furniture assembly and cooking.