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CSP Group
> Laboratories |
Leader |
Professor Hung-Yu Wei |
Room No. |
EE-355 |
Website |
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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 |
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Introduction |
1. Digital Signal Processing 2. Digital Image Processing 3. Multimedia Signal Processing |
Leader |
Professor Lin-Shan Lee |
Room No. |
EE-531 |
Website |
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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 |
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Introduction |
Advancement of Communication Theory, Information Theory, Signal Processing Technologies, and their applications. |
Leader |
Professor Homer H. Chen |
Room No. |
EE-533 |
Website |
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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 |
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Introduction |
For more information, please see the website. |
Leader |
Professor Hung-Yi Lee |
Room No. |
EE-552 |
Website |
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Introduction |
Deep Learning, Machine Learning, Spoken Language Understanding, Speech Recognition |
Leader |
Professor Thierry Blu |
Room No. |
EE-553 |
Website |
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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 Mao-Chao Lin |
Room No. |
BL-503 |
Website |
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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 |
Assistant Professor Chu-Hsiang Huang |
Room No. |
BL-504 |
Website |
|
Introduction |
• Next generation wireless communication system design • Communication system standardization • Artificial intelligence and machine learning • Statistical communication theory |
Leader |
Professor Yi-Hsuan Yang |
Room No. |
BL-505 |
Website |
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Introduction |
Musice information research; Artificial Intelligence; Machine learning; Musice generation |
Leader |
Professor See-May Phoong |
Room No. |
BL-506 |
Website |
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Introduction |
Signal Processing for Communications, Synchronization and Parameter Estimation for Broadband Communications. |
Leader |
Professor Ping-Cheng Yeh |
Room No. |
BL-515 |
Website |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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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. |