Tsinghua Electronic Information Alumni Forum (Shenzhen)

Invited Speakers

    Yi Pan

  • Chair Professor and Dean
  • Fellow of AIMBE, RSPH, IET, and JSPS,and Foreign Member of AESU.
  • Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
  • Title: AI in Medical and Biological Engineering
  • Abstract: Artificial Intelligence (AI) is the science of mimicking human intelligences and behaviors. Machine Learning (ML), a subset of AI, trains a machine how to use algorithms or statistics to find hidden insights and learn automatically from data. Deep learning (DL) is one of machine learning methods where we use deep neural networks with advanced algorithms such as auto-encoding or convolution to recognize patterns in data. AI has become very successful recently due to the availability of huge data and powerful supercomputers. Many applications such as speech and face recognition, image classification, natural language processing, bioinformatics, health informatics such as disease prediction and detection suddenly took great leaps due to the advance of AI. Although various AI architectures and novel algorithms have been invented for many bio and health applications, better explainability, increasing prediction accuracy and speeding up the training process are still challenging tasks among others. In this talk, I will outline recent developments in AI research for bioinformatics and health informatics. The topics discussed include proposing more effective architectures, intelligently freezing layers, gradient amplification, effectively handling high dimensional data, designing encoding schemes, mathematical proofs, optimization of hyper-parameters, effective use of prior knowledge, embedding logic and reasoning during training, result explanation and hardware support. These challenges create a huge number of opportunities for people in both computer science and health care. In this talk, some of our solutions and preliminary results in these areas will be presented and future research directions will also be identified.
  • Bio: Dr. Yi Pan is currently a Chair Professor and the Dean of Faculty of Computer Science and Control Engineering at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China and a Regents’ Professor Emeritus at Georgia State University, USA. He served as Chair of Computer Science Department at Georgia State University from 2005 to 2020. He has also served as an Interim Associate Dean and Chair of Biology Department during 2013-2017. Dr. Pan joined Georgia State University in 2000, was promoted to full professor in 2004, named a Distinguished University Professor in 2013 and designated a Regents' Professor (the highest recognition given to a faculty member by the University System of Georgia) in 2015.

    Dr. Pan received his B.Eng. and M.Eng. degrees in computer engineering from Tsinghua University, China, in 1982 and 1984, respectively, and his Ph.D. degree in computer science from the University of Pittsburgh, USA, in 1991. His profile has been featured as a distinguished alumnus in both Tsinghua Alumni Newsletter and University of Pittsburgh CS Alumni Newsletter. Dr. Pan's current research interests mainly include bioinformatics and health informatics using big data analytics, cloud computing, and machine learning technologies. Dr. Pan has published more than 450 papers including over 250 journal papers with more than 100 papers published in IEEE/ACM Transactions/Journals. In addition, he has edited/authored 43 books. His work has been cited more than 16000 times based on Google Scholar and his current h-index is 82. Dr. Pan has served as an editor-in-chief or editorial board member for 20 journals including 7 IEEE Transactions. Currently, he is serving as an Associate Editor-in-Chief of IEEE/ACM Transactions on Computational Biology and Bioinformatics. He is the recipient of many awards including one IEEE Transactions Best Paper Award, five IEEE and other international conference or journal Best Paper Awards, 4 IBM Faculty Awards, 2 JSPS Senior Invitation Fellowships, IEEE BIBE Outstanding Achievement Award, IEEE Outstanding Leadership Award, NSF Research Opportunity Award, and AFOSR Summer Faculty Research Fellowship. He has organized numerous international conferences and delivered keynote speeches at over 60 international conferences around the world.
  • Personal Page

    Gang Li

  • Professor
  • Tsinghua University
  • Title: Radar Sensing for Assisted Living
  • Abstract: In this presentation we will introduce the applications of radar sensing techniques in assisted living. Some examples of radar localization and tracking of human objects, radar classification of human activities, radar recognition of hand gestures, and radar detection of breathing disorder will be presented. The trends of radar sensing in assisted living will also be discussed.
  • Bio: Gang Li received the B.S. and Ph.D. degrees in electronic engineering from Tsinghua University, Beijing, China, in 2002 and 2007, respectively. Since July 2007, he has been with the Faculty of Tsinghua University, where he is currently a Professor with the Department of Electronic Engineering. From 2012 to 2014, he visited Ohio State University, Columbus, OH, USA, and Syracuse University, Syracuse, NY, USA. He has authored or coauthored more than 170 journal and conference papers. His research interests include radar signal processing, distributed signal processing, remote sensing, and information fusion. He is the author of Advanced Sparsity-Driven Models and Methods for Radar Applications (London, UK: SciTech Publishing, 2020). He is an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING and was the Guest Editor for the IET RADAR SONAR AND NAVIGATION and DIGITAL SIGNAL PROCESSING. He is a recipient of the National Science Fund for Distinguished Young Scholars of China and the Royal Society Newton Advanced Fellowship of United Kingdom. He is the Fellow of the IET.
  • Personal Page

    Jing Zhou

  • CTO
  • CoreAIOT Technology Co.,Ltd
  • Title: High accuracy indoor positioning technology and its application
  • Abstract: Beidou and other satellite positioning technologies are becoming more and more mature. By 2035, China will build a more ubiquitous integrated positioning system based on Beidou. Due to the limitation of indoor application of satellite positioning technology, high accuracy indoor positioning technology is still a big challenge to build this ubiquitous positioning system. Focusing on high-precision positioning technology, this presentation focuses on BLE AOA and ranging technology and its application for massive Bluetooth-based devices.
  • Bio: Zhou Jing, 33, is a bachelor and master of electronic engineering from Tsinghua University. Former product and Internet of things expert of TP-LINK, responsible for MiFi / security camera related product planning. Familiar with Bluetooth / WiFi / 4G / 5G / UWB and other wireless communication protocols, proficient in software defined radio design. Currently, he is CTO of CoreAIoT, responsible for product planning and R & D.
  • Personal Page

    Fei Qiao

  • Associate Professor
  • Tsinghua University
  • Title: Processing Paradigm of “Sensing with Computing” in Analog Domain and its Continuous Perception IC
  • Abstract: Intelligent Internet of Things technology is an inevitable product of the rapid development of artificial intelligence technology and Internet of Things technology. The design and implementation of integrated Internet of Things nodes with continuous intelligent perception capabilities is the promising way for various terminal devices to achieve intelligence, and it is also the solution to the current Internet of Things, which are the key technologies for reducing system power consumption, real-time performance, security and privacy. This article reviews the emerging "Senputing Architecture, Sensing with Computing" including system architecture and the new paradigm of integrated circuit design for intelligent continuous perception. First, the intelligent visual perception integrated system is the breakthrough point. The goal is to integrate artificial intelligence under the new processing architecture. The processing task is closely integrated with the visual sensor to realize an ultra-low-power intelligent visual acquisition and analysis chip that can work continuously, and expand to a variety of perception modes such as auditory perception and tactile perception. This presentation will introduce the multi-dimensional scalable exploration method of emerging "Senputing Architecture" for intelligent continuous sensing, the design method of high-energy-efficiency "Sensing + computing in Memory" mixed-signal integrated circuit chip, and the software and hardware codesign ideas to solve various non-ideal factors of mixed-signal architecture and circuits, to improve the performance and reliability of low-power smart chips.
  • Bio: Fei Qiao is currently the group leader of iVip Lab (integrated Vision, intelligent perception), Dept. of EE, Tsinghua University. His research interests are low power CMOS circuits design for multimedia sensor network, and integrated intelligent perception chips, including visual, auditory and tactile smart sensing. Fei’s group has published conference and journal papers, including ISSCC, DAC, ICCAD, ISLPED, IROS, ICRA, and TCAS-I, TCAS-II, TVLSI, TC, TCAD. Additionally, the iVip group have been granted for about 30 patents.
  • Personal Page

    Yu Wang

  • Chairman/CEO/Co-Founder
  • Seetrum Technology
  • Title: Spectral sensing everywhere
  • Abstract: Seetrum’s chip-scale hyperspectral sensor integrates metasurface technology and wide-spectrum dispersion characteristics and includes a novel algorithm framework. Compared with commercialized spectrometers, we have miniaturized the bulky and expensive spectrometer to only 1% of its size and cost, with an outstanding spectral resolution of 0.8 nm. Compared with leading researches worldwide, our achievement features smaller spectral pixel, higher spectral resolution, and wider spectral range. However, the most important advantage is that our technology is perfectly compatible with the CMOS process, making massive and cheap production available. Our technology was reviewed by the international top journal “Science” this year and listed as the latest research achievement in this field. Seetrum would lead the expensive hyperspectral sensing to our daily life and make spectral sensing everywhere. Seetrum is committed to providing advanced spectral chips, AI algorithms, and intelligent sensing solutions, empowering the industries and supporting our customers' efficient development. We are a high-tech company that originated from Tsinghua University. We have innovated a snapshot CMOS hyperspectral imaging chip with high resolution, low cost, and massive production ability, which will expand sensing applications in smartphone, medical device, machine vision, AR, autopilot, smart city, etc. We are making spectral sensing everywhere.
  • Bio: Yu Wang co-founded Beijing Seetrum Technology Co., Ltd., which focuses on CMOS spectral chips, in 2020. He has many years of experience in R & D, technology and management in the nano optics industry. Wang Yu graduated from the Department of Electronic Engineering of Tsinghua University in 2017 with a doctorate. During the semester, he published 5 SCI papers and 4 EI papers as the first author, and won Tsinghua Special Scholarship. From 2017 to 2020, Wang Yu worked in Everbright Securities Asset Management Co., Ltd. as a researcher/assistant investment manager in the electronics industry.
  • Personal Page

    Yunhang Liu

  • Algorithm Director & General manager of subsidiary
  • Pudu Technology
  • Title: AI & Learning Theory in Service Robotics
  • Abstract: This talk will discuss the global development of service robot and highlight Podutech’s work in developing robot products based on learning theory.
  • Bio: Liu yunhang received his master's degree from Artificial Intelligence college, Beijing University of Posts and Telecommunication. He is now working at Pudutech company, served as the algorithm director and general manager of subsidiary. His research interests are robot mobile technology and product development.
  • Personal Page