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Jing Zhang is currently a Professor at School of Automation Science and Engineering, Xi’an Jiaotong University. He obtained bachelor's and doctoral degrees from the Department of Mathematics and the Department of Automation at Tsinghua University in 2001 and 2006, respectively. He worked as a Postdoc at Tsinghua University from 2006 to 2008, and then worked at Department of Automation, Tsinghua University from 2008 to 2022. In 2022, he joined Xi’an Jiaotong University and worked as a Second-Class Professor. Professor Zhang mainly engaged in research on quantum and micro nano system control, optical microresonator sensors, etc. He has published more than 80 papers in authoritative journals in the fields of physics and control, e.g., IEEE Transactions on Automatic Control, Nature, Nature Photonics, Physics Reports, Physical Review Letters, Nature Communications. His work on chaotic propagation and stochastic resonance in optomechanical systems was selected as the cover hot paper of the June 2016 issue by Nature Photonics and was awarded as the "2016 Important Achievements in Chinese Optics". As the first author, his work has be awarded by the International Federation of Automatic Control (IFAC) as Young Author Award, which is one of the most important international awards in the field of Automation. He received support from the National Natural Science Foundation of China's Outstanding Youth Fund in 2016, and then selected as a Young Changjiang Scholar in 2017. In 2021, he was selected as a Changjiang Distinguished Professor.

Speech Title: Optical sensor based on chip-integrated optical microresonator

Abstract: In recent years, with the development of cutting-edge technology, sensing techniques have approached the classical noise limit. Optical sensing technique based on optical microresonators, leveraging resonance enhancement and noise suppression technologies, holds the potential to break this limit while combining precision and size advantages. Additionally, optical microresonator sensors can achieve on-chip integration through semiconductor silicon-based fabrication techniques. The report introduces the development and applications of chip-integrated optical microresonator sensors. 1) First, we introduce the fundamental principles, competitive advantages, and our progresses of optical microresonator sensors. 2) Next, we elaborate on three application scenarios of optical microresonator sensors in underwater target detection and autonomous navigation: i) The application of optical microresonator sensors in autonomous navigation, specifically for gyroscopes and accelerometers; ii) The application of optical microcavity sensors in underwater acoustic detection, namely hydrophones. We detail their detection principles, results from pool calibration, lake trials, and sea tests, with calibration results surpassing traditional piezoelectric hydrophones by 1-2 orders of magnitude; iii) The application of optical microresonator sensors in underwater target magnetic detection, with a detection accuracy of 0.19pT/Hz^1/2, and verification experiments using simulated radar scanning are provided. 3) A prospect was made for the application of optical microresonator sensors in quantum sensing.

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Prof Jin Xie received B.Eng. degree from Tsinghua University in 2000, and M.Eng. degree from Zhejiang University in 2003, and the Ph.D. degree from Nanyang Technological University, Singapore in 2008. From 2007 to 2011, he worked in Institute of Microelectronics, Singapore, where he was a scientist in the Sensors and Actuators Microsystems Program. From June 2011 to July 2012, he worked as a post-doc researcher in the Department of Mechanical Engineering, University of California, Berkeley, CA, USA. He was a research member of Berkeley Sensor & Actuator Center (BSAC). In October 2012, he joined School of Mechanical Engineering, Zhejiang University as a full professor. His research interests include MEMS sensors and actuators, wearable devices and flexible sensors. He has published more than 120 journal papers and 80 conference papers, and has been granted 15 Chinese invention patents. He was TPC member of IEEE NEMS 2015, 2018, 2020, 2022 and Transducers 2021. He is an IEEE member, and is an editorial board member of the journal of AI Sensors (MPDI) and the journal of Smart Wearable Technology.

Speech Title: Human-Machine Interaction Based on Piezoelectric Micromachined Ultrasonic Transducers

Abstract: Wearable ultrasonic devices can non-invasively monitor muscle activities for prosthetic hand control and human-machine interaction (HMI). However, most existing ultrasonic probes for deep muscle tissue monitoring are designed with bulky structures, limiting their wearability for long-term continuous monitoring. This talk includes three topics: (1) First, a sensing and controlling strategy is introduced for upper extremity prosthetics through finger motion decoding based on wearable piezoelectric micromachined ultrasound transducer (PMUT). (2) Secondly, a strategy is proposed for simultaneous gesture recognition and upper limb angle measurements using multiple A-mode ultrasonic patches, enabling real-time control of a four-degree-of-freedom (4-DOF) virtual robotic arm. (3) Finally, we present a soft electronic skin (E-skin) for 3D hand reconstruction inspired by human biology, which integrates a multi-sensor fusion of stretchable carbon nanotubes (CNTs) strain sensors and PMUT.

Weixin Liu is a Postdoctoral Research Fellow in the Department of Electrical and Computer Engineering at the National University of Singapore. His research spans nano-opto-electro-mechanical (NOEM) systems, silicon photonics, mid-infrared waveguide sensing, and microwave photonics. He received the B.Eng. in Mechatronics Engineering from Zhejiang University in 2019 and the Ph.D. in Electrical and Computer Engineering from NUS in 2024. Dr. Liu’s first-author publications include Science, Nano Letters, Advanced Optical Materials, and Nanophotonics.

Speech Title: Nano-opto-electro-mechanical gratings for on-chip light switching and spectral shaping

Abstract: Programmable spectral shaping, i.e., dynamic and arbitrary control over spectra, promises to reshape photonic systems with unprecedented spectral efficiency and network agility. However, most existing photonic components offer rigid, weakly tunable spectral functions, constraining compact and high-speed on-chip implementations. This talk presents a pixelated nano-opto-electro-mechanical (NOEM) grating that leverages electromechanically induced symmetry breaking to achieve pixel-level, precise control of the grating coupling strength, enabling an ultracompact on-chip spectral shaper. The device combines a high degree of spectral programmability with fast, reconfigurable operation on a single chip, opening new routes toward elastic bandwidth allocation in optical networks and frequency-domain parallel optical signal processing. It also points to opportunities in optical computing, microwave photonics, and quantum photonics.

Prof. Xiaochen DONG obtained PhD degrees from Zhejiang University in 2007. In 2012, he joined Institute of Advanced Materials, NanjingTech University as a Full Professor. And in 2022, he was promoted to vice president of Jiangsu Normal University. He has published more than 300 papers, with citation by >40,000 times (H-index~109), edited and published 3 books in English and Chinese. The current research involves biophotonics and bioelectronics, flexible electronics. His scientific achievements have been honored by many prestigious scientific awards in China, including "Ten thousand plan" - National high level talents special support plan (2017), Distinguished Young Scholar of China (2015), National Science Foundation (2015), and so on.

Speech Title: Conductive Hydrogels for Flexible Electronics

Abstract: Hydrogels are 3D crosslinked polymer networks imbibed with a significant amount of water. Because of their natural affiliation with biological tissues, environmental friendless and ionic conductivity, they have recently drawn significant attention as active materials for a range of flexible electronic applications, especially flexible and stretchable sensors. By extending the structural design strategy based on composite materials, which we previously developed, we have demonstrated hydrogel-based multifunctional wearable sensors that can detect various human motions, body temperature, as well as strains and pressures. Two-dimensional carbides and nitrides, also known as MXenes, are a rapidly expanding new family of 2D nanomaterials that have found wide applications in energy storage, electronics, etc. They possess metallic conductivity, superior hydrophilicity and abundant chemical modification opportunities. Therefore, when used as conductive nanofillers in hydrogels, new properties and functions emerge due to complex interactions between MXenes and other constituents within the hydrogel system, leading to dramatically enhanced applications and even brand new ones, as we demonstrated through MXene-hydrogel-based flexible sensors.

Zhiwu Han, professor and doctoral supervisor, is currently the director of Key Laboratory of Bionic Engineering (Ministry of Education) of Jilin University. His research encompasses the study in mechanical bionics, bionic perception theory and technology, bionic functional surface and advanced biomimetic composites. His work aims to apply mechanical bionic principles to hypersensitive sensors, lightweight high-strength materials, and micro-nano manufacturing. He serves as a fellow of the International Society of Bionic Engineering, the associate editor of Journal of Bionics Engineering, and vice chairman of the editorial board of Chinese Journal of Mechanical Engineering. To date, Prof. Han has authored more than 100 peer-reviewed papers in notable journals, including Nature, Science Advances, Advanced Materials, Progress in Materials Science, and Materials Today. His pioneering work in mechanical bionics has won more than 5 significant awards at the national or provincial level, such as Second Prize of the State Technological Innovation Award, First Prize of the Ministry of Education Technology Invention Award, First Prize of the Jilin Province Technology Invention Award, First Prize of the Mechanical Industry Science and Technology Award, etc.

Speech Title: Bionic high-performance perception theory and technology

Abstract: Sensors, which serve as crucial instruments for gathering external information, have drawn substantial attention in domains such as electronic skin, human-computer interaction, and precision instrumentation. Among these, mechanical sensors represent a major area of research focus. However, the performance of existing mechanical sensors in terms of weak vibration detection, target signal identification, and vibration source localization is difficult to meet the practical requirements. Therefore, it is important to find innovative methods to design high-performance mechanical sensors. Over billions of years of evolution, the fusion of organisms and nature has become perfect. This report takes the scorpion as its biological prototype. Through systematic bionic studies, a range of intrinsic mechanisms underlying the scorpion's remarkable perceptual functions have been revealed. These principles enable scorpions to detect faint stimuli, accurately discriminate signals, and quickly locate vibration sources even in complex settings, which is conducive to avoiding enemies and hunting for food in harsh conditions to maintain survival. Drawing inspiration from such ingenious biological strategies, corresponding designs and fabrication methods for biomimetic sensors have been developed and widely applied in fields such as automotive industry manufacturing, micro-vibration monitoring of bridges, and fault monitoring of precision equipment.

Dr. Jian-Hao Chen is currently a Professor at the School of Physics, Peking University. He received his PhD in Physics from the University of Maryland in 2009. After graduation, he worked as a post-doctoral researcher at the University of Maryland and the University of California, Berkeley. He joined ICQM, Peking University as a tenure-track Associate Professor in 2013, and then promoted to tenured Associate Professor in 2019, and to tenured Full Professor in 2024. His research interests focus on quantum transport and device physics of low-dimensional materials, including topological and correlated materials, magnetic materials and high mobility materials as well as their heterostructures. He has published more than 60 papers with more than 12,000 citations (Google Scholar). He has also been listed as the most cited Chinese Researchers for the year of four consecutive years from 2021 to 2024 by Elsevier. He is currently the Physics Editor of National Science Review and Associate Editor of npj 2d Materials and Applications.

Speech Title: Spin transport with magnon-flat bands and spin-spin correlations

Abstract: van der Waals magnets have been a fertile playground for low-dimensional spin excitation and spin-based device applications; spin-spin correlations in complex spin structures provide exotic correlated states that might facilitate spin excitation and transport. We will discuss our recent process in a long distance, quasi-1D magnon transport in a 2D spin lattice, aid by the formation of a flat magnon band; short introduction of an electrically operated digital magnon NOT gate[1] and an electrically operated magnon anisotropic read-only memory [2] will also be provided; lastly, we will discuss an ultra-long distance spin transport phenomena based on spin-spin correlation instead of conventional exchange interactions (Figure 1)[3]. These results unveil the potential of van der Waals anti-ferromagnets and complex magnetic materials for studying highly tunable spin physics and for application in magnon-base circuitry in future information technology. [1] Guangyi Chen et al., Nature Communications 12:6279 (2021) [2] Shaomian Qi et al., Nature Communications 14: 2526 (2023) [3] Di Chen et al., Nature Communications (2025) Online publication: https://www.nature.com/articles/s41467-025-68203-4

Xingsheng Wang obtained his Ph.D. from the University of Glasgow, UK, in 2010, later he worked in Synopsys as senior engineer and he joined Huazhong University of Science and Technology (HUST) as a full professor in 2018. Prof. Wang focuses on the research of Design–Technology Co-Optimization (DTCO) EDA and novel computing-in-memory chip technologies. He has published over a hundred papers in leading IEEE journals and conferences such as IEEE EDL, TED, ISCAS, DAC, ICCAD, and IRPS. He holds more than ten major research projects, including key projects from NSFC and National Key R&D Program, also joint research projects with YMTC, and Huawei. He serves as TPC sub-committee chairs or members of IEEE ISEDA and ICTA, DAC and ETDM. He is a senior member of IEEE, CCF, and CAAI. He received the 2022 Huawei OlympusMons Pioneer Award.

Speech Title: Memristor-based Computing-in-Memory Chip Co-Design for Edge AI

Abstract: Analog matrix multiplication based on memristor crossbar arrays can significantly increase computational throughput and energy efficiency. However, its physical implementation faces several fundamental challenges, including unclear device dynamics, reliability issues in multilevel operation, and IR-drop of the array. To address these issues, we fabricated CMOS-compatible memristor array chips based on 180 nm and 55 nm processes and developed a 3D multi-physics device simulator and crossbar array simulators. This enabled us to clarify the conductive filament formation and rupture mechanism in memristors, as well as the random telegraph signal (RTS) mechanism affecting read current reliability. We also developed superlattice-like memristors to achieve stable multilevel characteristics. For the critical issue of crossbar IR-drop, which severely impacts computational accuracy and throughput, we implemented a fast and accurate modeling method with O(n) complexity. Through co-optimization of layout and circuit design, along with a proposed real-time deployment correction approach, we substantially increased the scale of a single multiply-accumulate core to several megabits. These advances systematically overcome the bottleneck of array scaling, significantly improving both computational performance and energy efficiency of memristor computing-in-memory chips.

Zhenyu Wu received his B.S. degree in Physics from Shandong University (SDU), Jinan, China, in 2004. He received M.Sc. and Ph.D. degree both from Ulm University, Ulm, Germany, in 2006 and 2011, respectively. He worked as R&D engineer and project manager for MEMS technology at the Automotive Electronics Division, Robert Bosch GmbH, Reutlingen, Germany, from 2011 to 2018. He joined the Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences (CAS) since 2018 as a professor, where he is currently director of the Laboratory of Transducer Technology. He is vice director at Shanghai Industrial μTechnology Research Institute (SITRI) and joint Professor at Shanghai University. He has published more than 50 papers, 30 international patents, and co-authored 4 books. His research interest includes advanced micro/nano fabrication technology, MEMS microsystems and new sensors based on quantum effects

Speech Title: A NOVEL MANUFACTURING TECHNOLOGY FOR PIEZOELECTRIC MEMS MPW INTEGRATING BIMORPH AlScN PROCESS AND ACHIEVEMENTS

Abstract: This paper reports a novel piezoelectric MEMS multi-product wafer (MPW) manufacturing technique that integrates bimorph AlScN processing for the first time. It achieves a significant increase in actuation force without changing the materials used in the piezoelectric MEMS chips. By characterizing the resonant frequency and maximum displacement of cantilevered process control monitor (PCM) fabricated in MPW, it is demonstrated that the bimorph AlScN process effectively enhances the actuation performance of cantilever beams. Furthermore, compared to unimorph structures, the resonant frequency exhibits no significant change. We validated these results across different devices using the MPW platform, demonstrating that the 1+1μm bimorph AlScN structure and the 1.5μm unimorph AlScN structure increased the deflection angles of the two quasi-static piezoelectric micromirrors by 29% and 65%, respectively. For sensors, this bimorph structure does not enhance performance because the charges generated by the upper and lower piezoelectric films on the intermediate electrode cancel each other out.

Baoyong Chi received the B.S. degree in microelectronics from Peking University, Beijing, China, in 1998, and the Ph.D. degree from Tsinghua University, Beijing, in 2003. From 2006 to 2007, he was a Visiting Assistant Professor with Stanford University, Stanford, CA, USA. He is currently a Full Professor at the School of Integrated Circuits, Tsinghua University, where he also serves as Chair of the Academic Degrees Sub-Committee. His primary research focuses on radio-frequency (RF)/millimeter-wave integrated circuits and RF microsystems for communication and radar. He has been recognized with several prestigious honors, including the National Science Fund for Distinguished Young Scholars from the NSFC and the High-Level Talents from the Ministry of Education. He has published over 200 academic papers. Prof. Chi has served as TPC Chair of IEEE A-SSCC, Guest Editor for IEEE Journal of Solid-State Circuits (JSSC) and IEEE Transactions on Circuits and Systems II (TCAS-II), and Editorial Board Member of SCIENCE CHINA Information Sciences. As principal investigator, he has led major projects from the NSFC, National High-Tech R&D Program (863 Program), National Science and Technology Major Project, and National Key R&D Program. His awards include the Tsinghua University Academic Newcomer Award, the China Institute of Electronics Outstanding Scientist Award, the Second Prize of Beijing Municipal Science and Technology Progress Award, and the Grand Prize of Tianjin Natural Science Award.

Speech Title: Accuracy-Boosted Temperature Compensated Crystal Oscillator

Abstract: Accurate megahertz clocks, typically generated by crystal oscillators (XOs), play a critical role in wireless communication systems. High frequency accuracy could be achieved by the active compensation in the temperature compensated crystal oscillator (TCXO). However, the spectral purity is usually degraded by the noise and distortion from the active compensation. This talk reports a megahertz TCXO featuring a time-domain accuracy boosting scheme to enhance the signal-to-noise and distortion ratio (SNDR) at the oscillator core’s tuning port. The key design considerations and circuit details are discussed. The TXCO is implemented in a 0.18-µm CMOS process, and achieves ±0.6 ppm/±1.4 ppm frequency accuracy over -55◦C to 85◦C/115◦C, corresponding to a 38:6×/13:2× improvement over uncompensated cases while maintaining competitive noise performance compared with existing solutions.

Professor Jinling Yang currently serves as a Professor and Doctoral Supervisor at the Institute of Semiconductors, Chinese Academy of Sciences (CAS), and is also a professor at the University of Chinese Academy of Sciences. She received her Ph.D. in Condensed Matter Physics from the Institute of Physics, CAS, in 1997. She subsequently conducted research at Tohoku University (Japan), the University of Freiburg (Germany), and the IBM Zurich Research Lab/University of Basel (Switzerland). In 2004, she was selected for the CAS "Hundred Talents Program" and returned to China to continue her work. Her research focuses on Micro-Electro-Mechanical Systems, particularly the development and application of resonators, oscillators, scanning probes, and so on. Professor Yang has published 2 scientific books and over 100 peer-reviewed papers, which have been cited more than 2,000 times in prestigious journals including Nature and its sister journals. She was invited to contribute chapters to the Encyclopedia of Nanotechnology and the Handbook of MEMS. She has authorized 1 PCT patent, 3 European patents, and over 60 Chinese invention patents. Her distinguished contributions have been recognized with awards including the Innovation Talent Award from the Chinese Overseas Community and the 2022 Hubei Provincial Second Prize for Scientific and Technological Progress. The scanning probe technology developed by her team was featured as a research highlight in Nature Methods.

Speech Title: Deep learning based inverse design for non-parameterized MEMS structural design

Abstract: In light of the growing demand for miniaturized, high-performance sensors in the Internet of Things, the optimal design of Micro-Electro-Mechanical System resonators has become a critical challenge. Conventional design methods heavily rely on finite element analysis and engineers' prior knowledge, resulting in prolonged design cycles, high computational costs, and difficulties in achieving co-optimization of multi-objective performances. This presentation introduces a revolutionary design paradigm developed to address these challenges—an inverse design framework for MEMS resonators based on deep learning and genetic algorithms. This framework can automatically generate high-performance 3D structures directly from target physical properties like frequency, quality factor, and motional impedance, without predefining the model topology. Beyond enabling rapid (within 10 minutes) and accurate (average deviation (3%) device design, this method also demonstrates exceptional versatility, supporting multiple vibration modes and a broad frequency range. Our research validates the algorithm's effectiveness via simulations and experiments, laying a solid foundation for its application in accelerating the innovative design of various MEMS devices.

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