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

Professor Shi-Chung Chang

Room No.

EE-550

Website

Introduction

Next generation network and spectrum sharing, dynamic access, technology and policy, geo-location database, optimal resource allocation, experiment and demonstration platform.

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 Thierry Blu

Room No.

EE-553

Website

Introduction

My original expertise is in wavelets, multiresolution, sparse signal representations and more generally approximation theory for signal processing problems. Over time, I have developed a keen interest in biomedical imaging applications (in particular fluorescence microscopy and MRI) and have focused on Image Processing problems like image registration, deconvolution/super-resolution and blind source separation.

Leader

Professor Ju-Hong Lee

Room No.

EE-553

Website

Introduction

(1) Research on One-dimensional (1-D) and Two dimensional (2-D) Digital Signal Processing: Theory and Design of 1-D and 2-D FIR and IIR digital filters and filter banks with continuous filter coefficients or discrete filter coefficients. For many communication and signal processing systems, quadrature mirror filter (QMF) banks have been widely used to achieve the goals of subband coding and short-time spectral analysis. In these applications, a QMF bank is employed to decompose a signal into subbands and the subband signals in the analysis system are decimated by an integer equal to the number of subbands. We have studied and developed theory and design of 1-D, 2-D Filters, Filter Banks, and Wavelet Filter Banks with linear phase or low group delay response for Applications in Audio, Image, and Video Signal Processing.

(2) Research on 1-D and 2-D adaptive array signal processing: Theory and Robust techniques for 1-D and 2-D adaptive array beamforming and bearing estimation in the presence of coherence signal sources, array sensor position errors, near field sources, and steering angle error, etc. One of the most important problems in a multiuser asynchronous environment is the inter-user interference, which can degrade the performance quite severely. This is the case also in a practical Code-Division Multiple Access (CDMA) system, because the varying delays of different users induce non-orthogonal codes. The base stations in mobile communication systems have long been using spatial diversity for combating fading due to the severe multipath. However, using an antenna array of several elements introduces extra degrees of freedom, which can be used to obtain higher selectivity. An adaptive receiving array can be steered in the direction of one user at a time, while simultaneously nulling interference from other users, much in the same way as the beamforming techniques. Recently, we also consider the research on OFDMA wireless communication systems. Theory and Techniques have been studied and developed for the adaptive processing of array signals in Smart Antennas with Applications in Wireless, Mobile Communications, and Anti-jamming Communications.

(3) Based on the achievements from (I) and (II), we have been conducting some more advanced researches including the explorations of theories and applications in the areas of multiple-input multiple-output (MIMO) wireless communication systems and MIMO radar systems for the next generation MIMO wireless communications.

Leader

Professor Mao-Chao Lin

Room No.

BL-503

Website

Introduction

The research of this lab. Is basically divided into two categories, i.e., the coding theory (classical error-correcting codes and modern error-correcting codes) and its applications to the communication systems and/or recording systems.

Leader

Adjunct Professor Kwang-Cheng Chen

Room No.

BL-504

Website

Introduction

1. Wireless Communication
2. Network Science
3. Data Analytics
4. Nature Computing and Networking

Leader

Professor Yi-Hsuan Yang

Room No.

BL-505

Website

Introduction

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

Leader

Professor See-May Phoong

Room No.

BL-506

Website

Introduction

Signal Processing for Communications, Synchronization and Parameter Estimation for Broadband Communications.

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 Char-Dir Chung

Room No.

BL-518

Website

Introduction

The research momentum of ACT Lab is focused on digital modulation theory, wireless communications and spread spectrum communications. The topics of current research interest include spectral precoding for multicarrier waveforms, MIMO systems, wireless sensor and relay networks, differential modulation systems, and OFDM system design, etc.

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

Professor Shih-Chun Lin

Room No.

BL-524

Website

Introduction

Using information-theoretic tools to study optimal schemes for networked systems, with applications in cyber-physical (AIoT) security and wireless multi-hop multi-user communications. Corresponding practical code design to approach the theoretical limit is also an interesting direction.

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

Associate Professor Borching Su

Room No.

MD-530

Website

Introduction

1. Signal processing for communication systems and radar systems.
2. Optimization of wireless transceivers, waveforms, and beamformers.

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

Associate Professor Hao-Chung Cheng

Room No.

MKI-513

Website

Introduction

Google and IBM have built their own small-scale quantum computers, which leads to a brand-new quantum era. It becomes a pressing matter to study how to harness the power of quantum computers to invent quantum information technology and thus to revolutionize Taiwan's Information and Communications Technology. Prof. Cheng proposes to apply his research expertise of quantum information processing techniques to investigate three major quantum information technologies - (i) quantum communication network, (ii) quantum circuits learning, (iii) quantum encryption, and (iv) quantum-enhanced artificial intelligence. Firstly, the study of quantum communication network involves designing multiple-terminal quantum information transmissions and receptions. This can be applied to simulate global operations in quantum computing. Secondly, quantum circuits learning aims to identify the unknown quantum circuits by using a series of quantum states as training samples. This will lead to applications of quantum circuits verification and testing. Thirdly, the study of quantum encryption can facilitate our national security. Fourthly, quantum-enhanced artificial intelligence harnesses the advantage of quantum resources to improve the efficiency and performance of machine learning and artificial intelligence tasks. Prof. Cheng proposes to employ this technology to integrate and enhance the development of artificial intelligence in the College of Electrical Engineering and Computer Science at the National Taiwan University (NTU) and the industries in Taiwan. The ultimate goal is to accomplish quantum information technology in the near-term future, and integrate the research and development between NTU, Ministry of Science and Technology (MoST), and the related industry-academia partnerships.

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.