Andrew I. Cooper is a Professor at the University of Liverpool, Director of the Materials Innovation Factory, and Honorary Professor at East China University of Science and Technology (ECUST). He pioneers research in advanced organic functional materials, including conjugated microporous polymers, porous organic cages, and porous liquids, and developed the first autonomous mobile robotic chemist. Fields of Interest: Materials chemistry, robotics, AI-driven synthesis, and computational design of functional materials. Scientific Impact: Over 200 SCI-indexed papers, 52,000+ citations, H-index 117. Key journals: Nature , Science , JACS , Angewandte Chemie . Awards: Royal Society of Chemistry Professorship, Outstanding AI Leader award, Fellow of the Royal Society and European Academy of Sciences. Leadership: Editor-in-Chief of Chemical Science , trained 47 Chinese postdoctoral fellows and PhD students, and leads international collaborations with Chinese universities. Research Trends: Articles focus on robotics, AI, computational materials design, photocatalysis, and dynamic porosity in molecular systems.
Xiuhao Deng is an Associate Research Fellow and PhD Supervisor at the Institute of Quantum Science and Engineering, Southern University of Science and Technology (SUSTech), with adjunct positions at Pengcheng Lab and Hefei Lab. He obtained his B.S. in Modern Physics from University of Science and Technology of China (USTC) in 2005, followed by an M.S. in Atomic and Molecular Physics from USTC (2009) and a Ph.D. in Physics from University of California, Merced (2015). Research Interests: Driven quantum systems Quantum control theory and open quantum systems Superconducting and spin qubits Quantum error correction Quantum simulation Quantum computing His work focuses on robust quantum gate engineering, scalable quantum control, and error mitigation in multi-qubit systems. Recent publications emphasize geometric correspondence methods, noise resilience, and hardware optimization. Academic Activities: Organized QIP 2020 (international quantum conference) Reviewer for Phys. Rev. X , Phys. Rev. Lett. , and other journals Transferred to Shenzhen International Quantum Academy in 2025 after tenure at SUSTech
Dr. Bai Ziqian is an Assistant Professor in the School of Automation and Intelligent Manufacturing at Southern University of Science and Technology (SUSTech) in Shenzhen, China. Recognized as a Pujiang Scholar and Shenzhen Pengcheng Peacock Talent, she has established herself as a leading researcher at the intersection of wearable technology, textile engineering, and human-computer interaction. Her work bridges technical innovation with practical design applications, focusing on user-centered solutions that enhance human experience through technology integration. Dr. Bai's educational background includes: PhD in Smart Wearable Product Design (2011-2015), Hong Kong Polytechnic University MA in Fashion and Textile Design (2005-2006), Hong Kong Polytechnic University BA in Fashion Design and Engineering (2001-2005), South China Agricultural University Her research spans wearable technology, tangible interactive interfaces, IoTs, ergonomics, functional garments, wearables for healthcare, material innovation, smart home applications, and user-centered design. Dr. Bai has pioneered work in smart wearable fabrics and sensing mechanisms based on flexible materials, with a particular focus on human-computer interaction theory and practice. She has established a research team that has mastered key technologies in smart fabrics, interactive textiles, physiological signal monitoring, and human-computer interaction systems. Her approach consistently emphasizes user-centered design principles, ensuring that technological innovations serve practical human needs while maintaining aesthetic appeal. Dr. Bai's publication record demonstrates a clear evolution from foundational work in photonic textiles toward increasingly sophisticated wearable healthcare and human-computer interaction systems. Her recent publications focus on advanced sensor technologies, energy harvesting for wearables, and sophisticated data analysis for human motion and physiological monitoring. The interdisciplinary nature of her work is evident in publications spanning materials science, biomedical engineering, textile technology, and design methodology, with papers appearing in high-impact journals including Advanced Functional Materials (IF: 19.5), ACS Sensors (IF: 8.9), and Computers in Industry (IF: 10). Dr. Bai has received numerous prestigious awards that highlight both the technical and artistic dimensions of her work: 2024 German Red Dot Design Award for Best Design 2013 Neo-Neon, permanent collection at China Silk Museum (State grade 1 museum) 2019 Finalist, ThermoBlanket, TechStyle for Social Good International Competition 2017 1st Prize Teaching Award, Donghua University 2017 China National Textile and Apparel Council Teaching Award Multiple Service Learning Awards from Hong Kong Polytechnic University She has successfully secured research funding from prestigious sources including the National Natural Science Foundation of China and Guangdong Province's General Project. Her projects include a collaborative effort with the Guangdong Provincial Department of Education and Li Ning Company on a 'flexible wearable lower limb functional electrical stimulation system.' Dr. Bai has extensive teaching experience across multiple institutions and has guided student teams to success in national competitions. She currently leads the Human-Computer Interaction Design Laboratory (HCID) at SUSTech, which focuses on advanced design, engineering, and technology research at the intersection of disciplines, training the next generation of interdisciplinary designers and engineers.
Dr. Xiong Yi is an Assistant Professor at the School of System Design and Intelligent Manufacturing (SDIM) at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He leads the Computational Design and Fabrication (CoDeFab) research group, focusing on the integration of computational design methods with advanced manufacturing technologies, particularly in the field of additive manufacturing. Dr. Xiong has established himself as a leading researcher in computational design for additive manufacturing, with a strong international research background spanning Europe and Asia. Dr. Xiong's educational journey includes: Doctor of Science (DSc) in Engineering Design and Production from Aalto University, Finland (2012-2016) Master of Science (MSc) in Machine Automation from Tampere University of Technology, Finland (2010-2012) Bachelor of Engineering (BEng) in Mechanical Engineering from Hubei University of Technology, China (2006-2010) Dr. Xiong's research primarily focuses on computational design and fabrication methodologies, with particular emphasis on design for additive manufacturing (DfAM), intelligent manufacturing systems, and smart materials. His work bridges the gap between theoretical design principles and practical manufacturing constraints, developing novel approaches for the production of complex engineered products. He has pioneered research in continuous fiber-reinforced composite additive manufacturing, developing innovative process planning and optimization techniques that enable the production of high-performance structural components. His research in electrothermally controlled origami and 4D printing of smart materials represents cutting-edge work at the intersection of materials science, mechanical engineering, and computational design. Dr. Xiong's recent publications reveal a strong focus on continuous fiber-reinforced composites, with significant contributions to 4D printing, metamaterials, and intelligent process planning. His work integrates computational design with manufacturing constraints, creating novel approaches for topology optimization, toolpath planning, and structural design that consider both performance requirements and manufacturability limitations. The research demonstrates increasing sophistication in materials science applications, particularly in programmable materials and multi-functional structures. Dr. Xiong has received multiple prestigious awards for his research contributions, including: Best Presentation Award at the 24th Chinese Conference on Mechanisms and Machine Science (IFToMM CCMMS2024) Best Presentation Award at the International Conference on Frontiers of Additive Manufacturing Research (RAAM 2024) Best Paper Award at the International Conference on Design for 3D Printing (ICD3DP 2023) PhD Scholarship from Aalto University (2016) Research Travel Grant from the International Association for Vehicle System Dynamics (IAVSD) (2013) National Scholarship from the Ministry of Education (2008) As a dedicated educator and mentor, Dr. Xiong serves as a PhD supervisor at SUSTech and has successfully guided students who have gone on to pursue advanced studies and careers at prestigious institutions including Hong Kong Polytechnic University, Beihang University, DJI Innovations, and Singapore's A*STAR research institute. His research is supported by multiple competitive grants, including key projects from the National Key R&D Program of China, the National Natural Science Foundation of China, and provincial and municipal funding agencies. Dr. Xiong also serves on the editorial board of the Journal of Engineering Design and as a guest editor for Composites Communications, contributing to the advancement of his field through scholarly service. Dr. Xiong leads the CoDeFab research group, which maintains a strong collaborative culture focused on 'design leading manufacturing, manufacturing driving design, and digital-intelligent integration.' The group has developed several advanced manufacturing platforms, including multi-axis continuous fiber-reinforced composite additive manufacturing systems, smart composite additive manufacturing platforms, and multifunctional soft matter open manufacturing platforms. With a focus on practical applications and innovation, the CoDeFab group actively collaborates with industry partners and has established a joint laboratory to bridge academic research with industrial implementation.
Liu Leo Liu is an Associate Professor and tenure-track faculty member in the Department of Chemistry at Southern University of Science and Technology (SUSTech), Shenzhen, China, leading research on multi-active ambiphilic main group centers. He serves on editorial boards for Chem (2020-2023), European Journal of Inorganic Chemistry (since 2022), Chinese Chemical Letters (since 2022), Inorganic Chemistry Frontiers (since 2024), and Acta Chimica Sinica (since 2024). His educational background includes: B.Sc. in Chemistry, Xiamen University (2007-2011) Ph.D. in Organic Chemistry, Xiamen University (2011-2016) with joint study at UC San Diego (2013-2015) Post-doctoral Fellow, University of Toronto (2016-2019) under Prof. Douglas W. Stephan Post-doctoral Scholar, Lawrence Berkeley National Laboratory & UC Berkeley (2019-2020) under Profs. F. Dean Toste, Kenneth N. Raymond, and Robert G. Bergman Dr. Liu's research pioneers the synthesis of novel ambiphilic compounds across d- and p-block elements, integrating synthetic chemistry, computational modeling, and spectroscopy. His group develops multi-active centers that challenge textbook knowledge while enabling practical applications in catalysis and materials science. Key focus areas include low-valent carbon species, isolable carbenes, and main group element chemistry with inverted electronic configurations. His publication record demonstrates consistent innovation in ambiphilic main group chemistry, with recent breakthroughs in crystalline stannyne, σ0π2 carbenes, and carbyne anions featured in Science, Nature Chemistry, and JACS. These works reveal fundamental principles of bonding and reactivity while expanding synthetic possibilities for unconventional molecular architectures. Significant scientific recognition includes: Chinese Chemical Society Young Chemist Award (2022) Huang Yao-Zeng Metal Organic Chemistry Young Award (2023-2024) Distinguished Lectureship Award from Chemical Society of Japan (2024) Chinese Chemical Society-RSC Young Chemist Award (2024) World's Top 2% Scientists (2024) As a doctoral supervisor, Dr. Liu mentors graduate researchers and received SUSTech's Outstanding Graduate Supervisor Award (2025). His research is supported by National Natural Science Foundation grants including Original Exploration Program, Excellent Youth Fund (Overseas), General Program, and Youth Fund C Project. The LLL group maintains active collaborations with international institutions and contributes to major chemistry conferences through invited lectures on ambiphilic main group chemistry. The LLL group operates as a dynamic interdisciplinary team within SUSTech's chemistry department, combining experimental synthesis with computational analysis to explore frontier areas of main group element chemistry. Their work bridges fundamental discovery and potential applications in catalysis, materials science, and chemical synthesis.
Lupei Du is an Associate Professor at the Department of Medicinal Chemistry, School of Pharmacy, Shandong University, China. He earned his B.S. and Ph.D. in Pharmaceutical Chemistry from China Pharmaceutical University (1999 and 2006) and completed postdoctoral research in Chemistry at Georgia State University (2006–2009). Research focuses on potassium channel blockers for antiarrhythmic agents Specializes in pharmacophore modeling, molecular docking, and fluorescent probe development Contributed to computational drug discovery and structure-activity relationship studies His publications highlight trends in cardiovascular drug design (targeting I Kr , I Ks , and Kv1.5 channels) and fluorescent probe engineering for hydrogen peroxide and carbohydrate detection. Awards include the Nanjing Outstanding Thesis Award (2005) and multiple fellowships. Lupei Du collaborates extensively through co-authorships and is a member of the China Pharmaceutical Association.
Cao Haishan is an Associate Professor at Tsinghua University, affiliated with the Department of Energy and Power Engineering in the School of Mechanical Engineering. His research focuses on cryogenic cooling systems, high heat flux thermal management, and the physics of amorphous ice formation and phase transitions. He leads a research group supported by the National Natural Science Foundation of China and industry partners including Huawei, Midea, and Lenovo. Ph.D., Mechanical Engineering, University of Twente, 2013 M.Sc., Chemical Engineering, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 2009 B.Sc., Chemical Engineering, Zhejiang University, 2006 Dr. Cao's research spans three major areas: cryogenic cooling (including micro cryocoolers and sorption systems), high heat flux electronic cooling (especially with non-condensable gases), and the formation and transformation of amorphous water ice. His work combines theoretical modeling, computational simulation, and experimental validation, often at micro and nano scales. He applies principles from thermodynamics, fluid dynamics, and materials science to solve engineering challenges in refrigeration and thermal control. The recent publications reflect a strong trend toward interdisciplinary research, integrating machine learning for heat transfer prediction, computational screening of MOFs for cryogenic switches, and fundamental studies of ice nucleation on various substrates. The articles span journals in physics, engineering, materials, and applied thermal sciences, indicating broad impact across multiple domains. Notable scientific awards include: Gustav and Ingrid Klipping Award (2016) Cryogenics Best Paper Award (2017) Annual Teaching Excellence Award, Tsinghua University (2023) Excellent Supervisor Award, Tsinghua University (2024) Multiple First Prize Advisor awards in national student contests on energy saving Dr. Cao has been principal investigator on several grants, including projects funded by the National Natural Science Foundation of China on amorphous ice lifetime and micro-cryocooling for semiconductor chips. He has also led industry-university collaborations with Huawei, Midea, and Lenovo. He advises graduate students and leads a research team focused on next-generation cooling technologies. He serves on editorial boards for Journal of Refrigeration , Vacuum and Cryogenics , and Energies , and has chaired sessions at major international conferences such as ICEC-ICMC and ACTS. His research group operates within the Institute of Thermophysics at Tsinghua University, leveraging facilities in the Lee Shau Kee Science and Technology Building. The team collaborates with national laboratories and international institutions, particularly maintaining ties with the University of Twente. Current efforts are directed toward ultra-low vibration cooling, efficient separation of non-condensable gases, and extending the stability of amorphous ice for cryobiological applications.
Shi Li is a Professor in the Theory Group at the Department of Computer Science and Technology, School of Computer Science, Nanjing University. He previously held faculty positions at the University at Buffalo (2015–2023) as Assistant and Associate Professor, and was a Research Assistant Professor at Toyota Technological Institute at Chicago (2013–2015). He earned his Ph.D. from Princeton University in 2014 under Moses Charikar and completed his B.S. in Computer Science and Technology at Tsinghua University, where he was part of Andrew Chi-Chih Yao’s Special Pilot Class. His research lies at the intersection of theoretical computer science and combinatorial optimization, with a focus on the design and analysis of algorithms for problems in clustering, scheduling, network design, facility location, and online algorithms. He also explores learning-augmented algorithms and differential privacy in algorithmic contexts. His work combines deep theoretical insights with practical algorithmic frameworks, often leveraging linear programming relaxations, iterative rounding, and randomized techniques. The recent publications highlight a consistent trend in approximation algorithms, particularly in clustering (e.g., correlation clustering, fair k-set selection), scheduling (e.g., unrelated machine scheduling, load balancing), and robust optimization. His work frequently appears in top-tier theoretical venues such as STOC, FOCS, SODA, and ICALP, with increasing emphasis on fairness, privacy, and efficiency in algorithm design. Best Paper Award of Track A, ICALP 2011 Co-winner of Best Paper Award, FOCS 2012 Invited to Special Issue of SICOMP (FOCS 2017 paper) Best Paper Award, COCOON 2018 Invited to Special Issue of SICOMP (STOC 2019 paper) Best Paper Award of Track A, ICALP 2024 Outstanding Paper Award, SPAA 2024 Shi Li has advised several PhD and master’s students, including Yuda Feng, Han Dai, Zihao Liang, and Jia Ye, and has mentored postdoctoral researcher Ruilong Zhang. He has served on numerous program committees (e.g., STOC, SODA, ICALP) and is an Editorial Board Member of ACM Transactions on Algorithms . He teaches core algorithm courses such as Design and Analysis of Algorithms and Advanced Algorithms , and actively collaborates with researchers worldwide. His lab focuses on theoretical foundations of efficient and fair algorithm design, with applications in large-scale data analysis and distributed systems.
Jin Yunshui is an Associate Professor at the Media Experiment and Practice Teaching Center within Tongji University's School of Art and Media. He holds a PhD in Digital Design and Technology from the University of the Arts London (2022) and has extensive experience in digital animation, interactive media, and immersive technologies. Education PhD in Digital Design and Technology (2017-2022), University of the Arts London, UK MFA in Media Art and Design (2011-2012), Bauhaus University Weimar, Germany Master of Arts (2010-2013) and Bachelor of Animation (2006-2010), Tongji University Research Interests Jin's work spans virtual reality (VR) , augmented reality (AR) , serious games , cultural heritage digitization , 3D visualization , and natural user interfaces . He focuses on applying immersive technologies to education, mental health, and historical preservation. Research Trends His recent publications highlight comparative studies of VR/AR systems, immersive education applications, and ethical design of interactive media. Key themes include digital storytelling , user engagement metrics , and technological frameworks for generative art . Scientific Awards 金曦奖-创新印象艺术奖 (2022) The Rookies奖沉浸式媒体组冠军 (2019) 全国计算机设计大赛一等奖 (2009) 同济大学优秀教师 (2018) Grants & Projects Jin leads major initiatives like the Shanghai Educational Research Project on Mental Health Intervention (2024), Ministry of Education's National Golden Course in Shadow Puppetry (2023), and international collaborations with Brunel University on creative industries (2023). Labs & Teams He heads the Non-planar Imaging Laboratory at Tongji and contributes to the Forever Project with Holocaust survivor holography (2017).
Ma Xufeng is an Assistant Professor in the Animation Department at the School of Art and Media, Tongji University , Shanghai. She earned her PhD in Image Arts from Chung-Ang University, South Korea , and completed a postdoctoral fellowship at the School of Journalism and Communication, Tsinghua University . Her research bridges intelligent imaging, animation games, AIGC, new media art, and the metaverse , focusing on intelligent image production and dissemination, AI-driven art therapy, and serious games . Education: PhD in Image Arts, Chung-Ang University, South Korea (2018.09–2021.02) Master of Image Arts, Chung-Ang University, South Korea (2016.09–2018.06) Bachelor of Art Design (Animation), Zhongnan University of Economics and Law, China (2011.09–2015.07) Research Interests: Dr. Ma’s scholarship sits at the intersection of artificial intelligence, digital media, and therapeutic applications . She explores how AI-generated content (AIGC) can revolutionize animation, game design, and immersive storytelling . A second strand investigates serious games and VR systems for autism rehabilitation and emotional therapy , leveraging game psychology to craft interventions that blend aesthetics, technology, and mental health . Publications & Research Trends: Her most recent work (2021-2024) charts a trajectory from VR-based rehabilitation games to AI painting for art therapy , demonstrating a shift from interactive technology prototypes toward critical and aesthetic theories of AI art . Collectively, her publications map the evolution of intelligent media ecosystems and their societal impact. Scientific Awards & Grants: Principal Investigator, Korean BK21+ CFT Convergence Research Project – VR immersive game for autistic children (2020) Principal Investigator, Korean BK21+ CFT Convergence Research Project – Fitness-bicycle functional game (2019) Special Selection Award, Seoul International Animation & Cartoon Festival (2020) Nomination, Golden Kuker–Sofia International Animation Festival (2020) Teaching & Labs: At Tongji University, Dr. Ma contributes to undergraduate and postgraduate curricula in animation, new media art, and game design . She is affiliated with the Omnimedia Research Institute and the Media Experiment and Practice Teaching Center , where she guides students in AI-driven content creation and VR/AR prototyping .
Wang Chun is a tenured Associate Professor in the Department of Management Science and Engineering at the School of Economics and Management, Tsinghua University. He currently serves as Deputy Director of the department and has held academic positions at Tsinghua since 2017. His work bridges stochastic control, reinforcement learning, and machine learning applications in operations management and financial technology. Education: Bachelor's Degree from Tsinghua University (2005) Master's Degree from the University of Wisconsin-Madison (2008) Doctorate in Operations Research from Columbia University (2014) Research Interests: His research focuses on stochastic control and decision-making under uncertainty, particularly in inventory management, revenue management, financial engineering, and sports analysis. He also investigates reinforcement learning algorithms for dynamic optimization and applies machine learning to business data analytics and financial technology. Published Work Trends: Wang’s publications span operations research, financial mathematics, and computational management science. Recent studies address seasonal optimization patterns, robust inventory models, and game-theoretic approaches to sports analytics. His work integrates theoretical advancements in dynamic programming with practical applications in financial engineering and market microstructure. Career History: 2023–Present: Associate Professor, Tsinghua University 2020–2023: Associate Professor, Tsinghua University 2017–2020: Assistant Professor, Tsinghua University Researcher at KCG (New York), leading studies on quantitative investment and asset optimization
Pengcheng An is an Assistant Professor at the School of Innovation and Creative Design at Southern University of Science and Technology (SUSTech) in Shenzhen, China. His research sits at the intersection of Design and Human-Computer Interaction (HCI), focusing on the design and implications of intelligent interactive systems in everyday contexts such as smart classrooms, offices, and other learning environments. Education: Ph.D. in Industrial Design, Eindhoven University of Technology, Netherlands Postdoctoral Research, Eindhoven University of Technology Postdoctoral Research Fellow and Sessional Lecturer, School of Computer Science, University of Waterloo, Canada An's research interests center on creating interactive systems that enhance learning, education, and support for children, families, and underprivileged groups. His work explores how emerging technologies like IoT, intelligent systems, and multimodal interfaces can be seamlessly integrated into real-world settings to improve user experiences without disrupting natural workflows. He particularly focuses on peripheral and unobtrusive interaction techniques that support busy practitioners like teachers and healthcare workers. His publication record demonstrates consistent contributions to top-tier HCI venues, with a focus on educational technology applications, assistive systems, and novel interaction techniques. The research trajectory shows increasing sophistication in understanding real-world deployment challenges and developing solutions that respect existing workflows while providing meaningful augmentation. Scientific Awards: Best Paper Honorable Mention Award (ACM CHI) Reviewers' Choice Award (INTERACT) Red Dot Design Award: Best of the Best (twice) iF Design Talent Award An serves as an active member of the HCI community, having been Associate Chair for the "Learning, Education, and Family" track at ACM CHI since 2021. He has secured research funding including a National Social Science Fund Youth Project exploring AI technology in art therapy for special children. His service extends to reviewing for major conferences (CHI, DIS, TEI, IDC) and journals (Behavior & Information Technology, Experimental Results). His laboratory work focuses on real-world deployments of interactive systems, particularly in educational settings, where he collaborates with teachers and students to develop and evaluate technologies that support learning without disrupting classroom dynamics.
Junmin Jiang serves as Associate Professor in the Department of Electronic and Electrical Engineering at Southern University of Science and Technology's College of Engineering since 2022, following promotion from Assistant Professor. He directs a research group focused on cutting-edge analog/power IC design with strong industry partnerships including Texas Instruments, Qualcomm, and Analog Devices. His educational background includes: Ph.D. in Electronic and Computer Engineering (2017), The Hong Kong University of Science and Technology Visiting Scholar (2015-2016), State Key Laboratory of AMSV, University of Macau B.Eng. in Electronic Information Engineering (2011), Zhejiang University Dr. Jiang's research centers on power management IC design with three interconnected thrusts: Power ICs for Specific Applications (e.g., audio/LiDAR drivers), Power ICs for AI systems, and AI-enhanced power IC design. His work achieves breakthroughs in switched-capacitor converters, delivering ultra-high efficiency (>97%), fast transient response ( His 15 most recent publications demonstrate consistent leadership in top venues (ISSCC/JSSC), showing accelerating impact in hybrid converter topologies, parasitic loss reduction, and AI-integrated power management. The trend reveals increasing industrial relevance with 8 U.S. patents and real-world implementations in audio/LiDAR systems. Scientific recognition includes: IEEE SSCS Pre-Doctoral Achievement Award (2017) National Overseas High-level Talent (Youth Project, 2022) SUSTech Outstanding Teaching Award (2024) Shenzhen Industrial Innovation Talent Award (2023) As an advisor, he mentors 8+ students including ISSCC awardees and competition winners. His group actively recruits undergraduates for chip design projects, with students winning top honors in National Electronic Design and Mathematical Modeling competitions. Current teaching includes graduate Nonlinear Circuits and undergraduate Microcomputer Principles. The Jiang Research Group maintains strong industry ties for student placements and collaborates with international institutions in the U.S., EU, and Macau. Lab capabilities focus on full-cycle IC design from simulation to tapeout, with recent 100V-output converters achieving 86.2% efficiency for acoustic applications.
Li Yi is a Tenured Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech) , with expertise in nanoplasmonics, nano-optics, and biochips. His career spans institutions including KU Leuven, Imperial College London, and Ludwig-Maximilians-Universität München. Education: Ph.D. (2015, KU Leuven & IMEC), M.S. (2010) and B.S. (2007) in Biomedical Engineering from Zhejiang University. Career: Associate Professor (2021–present) and Assistant Professor (2019–2020) at SUSTech; LMU Research Fellow (2018–2019); Research Associate (2015–2018) at Imperial College London. Research Interests focus on single-molecule biochips, DNA data storage, and nanopore sequencing. His work bridges nanotechnology with biomedical applications, including: Integrated circuit-compatible optical/electrical devices Computational lithography and nanoscale imaging Neural network training for biosensing Publications include >60 peer-reviewed articles with 25 H-index. His recent work emphasizes DNA-based data encryption, nanopore engineering, and portable biosensing systems. Key journals: Nature Communications, Nano Letters, ACS Nano. Scientific Awards : LMU Research Fellowship (Marie Curie COFUND) imec Excellent Scientific Award Shenzhen 'Peacock Plan' Category B Talent Outstanding Poster Award at Surface Plasmon Photonics 2017 Participation in Lindau Nobel Laureates Meeting (2019) Grants include Ministry of Science and Technology Key R&D Youth Program, NSFC General Program, and Guangdong Provincial Key Program. His lab develops: Fluidic nanopores for single-molecule sensing Optical antennas for enhanced detection Training programs in biochip design and nano-optics
Li Zhe is an Associate Professor and Doctoral Supervisor at the Department of Biomedical Engineering , Southern University of Science and Technology, since May 2024. He previously served as Assistant Professor at the same department from 2023 to 2024. His educational background includes a PhD in Analytical Chemistry from Purdue University (2019) under Prof. Chengde Mao, and a B.S. in Materials Chemistry from Peking University (2014). Research Focus: Protein design, DNA nanotechnology, bionanomaterials, and self-assembly Awards: 2023 National Natural Science Fund for Excellent Young Scientists (Overseas) 2019 Chinese Government Award for Outstanding Self-financed Students Abroad 2019 M.G. Mellon Award in Analytical Chemistry Publications: His 20+ works in high-impact journals like Science and Nature Materials emphasize computational protein design, DNA crystal engineering, and molecular actuation systems.
