Prof. Hayden Kwok Hay SO is an Associate Professor at the University of Hong Kong (HKU), affiliated with the Department of Electrical and Electronic Engineering. He currently serves as Acting Director of the School of Innovation and previously co-directed the Computer Engineering Program. His research focuses on reconfigurable computing systems, FPGA-based architectures, and their applications in AIoT, medical imaging, and high-performance computing. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (1998–2007). Prof. So has been recognized with awards such as the IEEE-HKN Teaching Award (2021), Croucher Innovation Award (2013), and multiple teaching excellence awards. He leads the Computer Architecture & System Research Lab (CASR) and co-founded the Joint Lab on Future Cities (JLFC). His work spans FPGA overlay architectures, graph processing systems, and hardware-software co-design for efficient computing. Key research contributions include advancements in FPGA-based reconfigurable systems, sparse dataflow architectures, and medical imaging accelerators. He has secured grants for projects like 'Advanced machine vision guided aquatic surface vehicles' and 'Efficient and Productive Parallel Data Processing in Hybrid FPGA-CPU Clusters.' Prof. So has advised numerous students and researchers, contributing to over 150 peer-reviewed publications. His current projects explore AI hardware acceleration, neuromorphic computing, and FPGA-driven solutions for big data challenges.
Edoardo Charbon is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Engineering, where he leads the Advanced Quantum Architecture Lab (AQUA). He also serves on the School Council STI and is Co-Director of STI-SSIQ Administration. Previously, he was a full professor and chair at Delft University of Technology from 2008 to 2016. Charbon received his Elektrotechnik Diploma from ETH Zurich, M.S. from UC San Diego, and Ph.D. from UC Berkeley, all in electrical engineering. His career spans industry experience at Cadence Design Systems and Canesta Inc. before joining EPFL in 2002. His research focuses on ultra high-speed and 3D optical sensors, with applications in LiDAR, FLIM (Fluorescence Lifetime Imaging Microscopy), PET (Positron Emission Tomography), FCS (Fluorescence Correlation Spectroscopy), and NIROT (Near-Infrared Optical Tomography). He has pioneered deep-submicron CMOS SPAD technology, which is now mass-produced and used in smartphones, telemeters, and medical diagnostics. His recent work bridges cryo-CMOS circuits for quantum computing with advanced optical sensing techniques. Analysis of his recent publications reveals a strong trend toward integrating quantum technologies with practical imaging applications. His work spans from fundamental device development (SPAD sensors, cryo-CMOS circuits) to applied systems (LiDAR engines, medical imaging devices), with increasing integration of machine learning techniques for real-time processing. 2023 IISS Pioneering Achievement Award Fellow of the IEEE Distinguished visiting scholar, W. M. Keck Institute for Space at Caltech Fellow, Kavli Institute of Nanoscience Delft Distinguished lecturer, IEEE Photonics Society Professor Charbon has authored or co-authored over 500 papers and two books, and holds 27 patents. His research has been supported by collaborations with organizations including Bosch, X-Fab, Texas Instruments, Maxim, Sony, Agilent, and the Carlyle Group. He has driven significant innovation in CMOS SPAD technology, which is now commercially deployed in various applications. He leads the Advanced Quantum Architecture Lab (AQUA) at EPFL, which focuses on the development of advanced sensor systems combining quantum technologies with conventional electronics. The lab has been instrumental in creating SPAD-based imaging systems that push the boundaries of time-resolved optical detection.
Yongmin Liu is a Professor in Mechanical and Industrial Engineering and Electrical & Computer Engineering at Northeastern University, and a member of the Cross-College Magnetics Center. He holds a PhD in Applied Science and Technology from UC Berkeley (2009), with earlier degrees from Nanjing University. His research focuses on nano-optics, metamaterials, plasmonics, and their applications in optical devices and systems. His interdisciplinary work bridges engineering, physics, and AI, with notable contributions to metasurface design and optical neural networks. Education: PhD, Applied Science and Technology, UC Berkeley (2009) M.S. and B.S., Physics, Nanjing University (2003, 2000) Research Interests: Nano-optics, nanoscale materials engineering, metamaterials, plasmonics, and applied physics. His group develops novel optical materials and devices for applications like super-resolution imaging, efficient light harvesting, and biomedical detection. Recent projects include AI-driven photonic materials design and meta-optical neural networks. Key Achievements: Recipient of the Søren Buus Outstanding Research Award (2024) NSF CAREER Award (2017) and ONR Young Investigator Award (2016) Elected SPIE Fellow (2023) and Optica Fellow (2023) Lab & Collaborations: Head of the Yongmin Liu Research Group, collaborating with institutions like Georgia Tech and Purdue University. Recent grants include a $1.5M NSF DMREF grant for AI-driven photonic materials and a $468K NSF grant for meta-optical neural networks.
Distinguished Professor Dayong Jin is a leading academic in nanotechnology and biomedical engineering at the University of Technology Sydney (UTS). He holds roles including Director of the Institute for Biomedical Materials and Devices (IBMD), ARC Laureate Fellow, and Chair Professor at Southern University of Science and Technology (China). His research focuses on photonics, luminescent materials, and their applications in healthcare, including cancer detection, rapid diagnostics, and super-resolution microscopy. Key innovations include 'Nano Torch' technology for disease detection and 'Super Dots' nanocrystals for imaging and anti-counterfeiting. Education: PhD from Macquarie University (2007). Leadership: Established UTS's IBMD and multiple research hubs, including the ARC IDEAL Research Hub and Australia-China Joint Research Centre. Research Interests: Transforming nanophotonics into diagnostic tools, rapid antigen tests (e.g., for COVID-19), and biomedical devices. His work bridges physics, engineering, and biology to address global health challenges. Awards: Australian Museum Eureka Prize (2015), Prime Minister's Prize for Science (2017), ARC Laureate Fellowship (2021), and Fellow of the Australian Academy of Technology and Engineering. Grants: Overseeing funded projects on quantum biotechnology, deep-tissue imaging, and nanoscale thermometry. Active in interdisciplinary collaborations, including with Chinese institutions. Labs/Teams: Leads IBMD, the ARC IDEAL Hub, and the UTS-SUSTech Joint Research Centre, fostering innovation in wearable biomaterials and point-of-care technologies.
Prof. Casper Hoogenraad is a full professor in Molecular Neuroscience at the Department of Cell Biology, Faculty of Science, Utrecht University. His research focuses on understanding how intracellular protein trafficking underlies neuronal development and function, with particular emphasis on the microtubule cytoskeleton, synaptic cargo trafficking, and synaptic plasticity. He leads an active research group within Utrecht University's Cell Biology department and collaborates extensively with other neuroscience research groups. Education: PhD, Erasmus University Rotterdam (1996-2001) Postdoc, Massachusetts Institute of Technology (2002-2005) Hoogenraad's research spans three main themes: cytoskeleton dynamics during neurodevelopment and synaptic plasticity, motor proteins and adaptors as regulators of synaptic transport, and psychiatric and neurologic disease disorders linked to intracellular transport. His work combines genetics, biochemistry, molecular, and cellular biology methods in in vitro (neuron cultures), ex vivo (brain slices), and in vivo (mice) systems, along with advanced microscopy techniques including immunofluorescent confocal microscopy, high-resolution live cell imaging, and photo-activated localization microscopy (PALM). Analysis of Hoogenraad's recent publications reveals a strong focus on microtubule organization, neuronal polarity, and the molecular mechanisms underlying synaptic function and dysfunction. His work frequently explores how disruptions in intracellular transport contribute to neurological disorders including Alzheimer's disease, schizophrenia, and autism spectrum disorders, with particular attention to the relationship between cytoskeletal organization and cargo transport in neuronal compartments. Scientific Awards and Memberships: ZonMW-VIDI (2004) European Young Investigators (EURYI) award (2005) NWO-ALW VICI (2011) ERC Consolidator grants (2013) FENS-Kavli Network of Excellence (2014) European Molecular Biology Organization (EMBO) (2015) Young Academy of Europe (YAE) (2015) IBRO Kemali Prize (2016) Hoogenraad leads a research group studying neuronal development and function, with a particular focus on how intracellular transport mechanisms contribute to both normal brain function and neurological disorders. His laboratory employs a multidisciplinary approach combining molecular, cellular, and systems neuroscience techniques to investigate the molecular basis of neuronal polarity, synaptic plasticity, and the pathogenesis of neurological disorders. He has secured significant research funding through prestigious grants including ERC Consolidator grants. The Hoogenraad lab operates within the Cell Biology department at Utrecht University, collaborating with other research groups focusing on cellular dynamics, biophysics, and neurobiology. The lab utilizes advanced microscopy techniques including immunofluorescent confocal microscopy, high-resolution live cell imaging (spinning disc microscopy and total internal reflection fluorescence microscopy), and quantitative analysis using advanced high-resolution microscopy (photo-activated localization microscopy). Current lab technicians include Phebe Wulf and Bart de Haan.
Dr. Patrick Kung serves as Associate Professor and Associate Department Head for Undergraduate Programs in the Department of Electrical and Computer Engineering at the University of Alabama's College of Engineering. His research spans nanotechnology, quantum computing, and terahertz photonics with significant contributions to metamaterials and optical systems. Research Focus: Dr. Kung specializes in terahertz spectroscopy, polarization-sensitive imaging, and nanoscale material engineering. His work integrates machine learning with optical systems for applications in underwater imaging, quantum networking, and biodegradable polymers. Recent projects include $1 million Department of Energy funding for quantum networking research (2024) and development of materials for slowing light propagation. Publication Trends: His recent publications (2022-2025) demonstrate a clear trajectory toward multimodal sensing systems combining terahertz technology, polarization control, and AI-driven image processing. Key themes include underwater object recognition using single-photon LiDAR, compact drone-compatible imaging platforms, and cryogenic photonic components for quantum applications. The work consistently bridges fundamental nanophotonics with practical engineering solutions. Department of Energy Funding ($1 Million for Quantum Networking Research, 2024) Dr. Kung actively mentors students in EPA-funded water disinfection projects using UV-LED technology and collaborates with industry partners through the Southeast Executives-on-Roster program. His laboratory work focuses on nanowire-based thin films and metamaterial absorbers, with applications in environmental monitoring and quantum communication hardware.
Ulrich B. Wiesner is the Spencer T. Olin Professor of Engineering at Cornell University since 2008, with a career spanning over two decades in polymer-inorganic hybrid nanomaterials. His work bridges materials science, chemistry, and biomedical engineering, focusing on block copolymer self-assembly for multifunctional materials. Education: Diploma in Chemistry (University of Mainz, 1988), Ph.D. in Physical Chemistry (University of Mainz & MPI-P, 1991) Research Interests center on combining soft polymeric materials with inorganic/solid-state chemistry to create hierarchical hybrid materials. Key areas include: Energy conversion and storage via mesoporous oxides/non-oxides Clean water technologies through advanced materials Nanomedicine applications in cancer therapy and bioimaging Development of C-dots: ultrasmall fluorescent silica nanoparticles Structure-directing agents from dendron architectures His article trends reveal a focus on asymmetric porous structures (2024-2025), 3D-printed quantum materials (2024), and biomedical applications of C-dots for super-resolution microscopy and targeted drug delivery (2023-2025). Scientific Awards include: National Academy of Inventors Fellow (2024) "Ambassadeur pour la Chimie Française" (2019) Arthur K. Doolittle Award (2016) ACS PMSE Fellow (2015) NSF Creativity Award (2008) Cornell Teaching Excellence Award (2005) IBM Faculty Partnership Award (2001) Carl Duisberg Memorial Award (1999) As co-director of the MSKCC-Cornell Center for Translation of Cancer Nanomedicine (2015-present), he leads interdisciplinary teams developing clinical nanoparticle probes. His work has produced >250 peer-reviewed publications and numerous patents, with recent breakthroughs in antibody fragment-nanoparticle therapeutics for gastric cancer eradication.
Julian Adamek is a computational cosmologist and lead developer of gevolution , a general-relativistic N-body code for cosmological simulations. His work focuses on modeling relativistic effects in cosmic structure formation to better understand gravity’s role on large scales and dark energy. Research Interests: Computational Cosmology, Theoretical Cosmology, Large-scale structure of the Universe, Relativistic N-body simulations. Technical Leadership: Lead developer of gevolution , a public cosmological simulation code available via GitHub. Recent publications span diverse applications of deep learning in geospatial analytics, environmental monitoring, and computer vision, including phenology modeling, biomass mapping, conflict assessment, and 3D reconstruction from point clouds. Key Trends: Integration of AI/ML for environmental tasks, cross-domain applications (cosmology, ecology, forestry), and satellite data processing. Technical Focus: Transformer networks, diffusion models, super-resolution imaging, and ensemble learning for uncertainty quantification. Julian collaborates with researchers in cosmology and geospatial science, though specific students or awards are not mentioned in the provided texts.
Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.
Lu Wei is an Assistant Professor of Chemistry at the California Institute of Technology and an Investigator at the Heritage Medical Research Institute. She holds a B.S. from Nanjing University (2010) and a Ph.D. from Columbia University (2015), joining Caltech in 2018. Research Areas: Optical spectroscopy, Biophysics, Bio-imaging, Chemical probe development Education: B.S. Nanjing University (2010), Ph.D. Columbia (2015) Research Interests include next-generation optical imaging techniques based on nonlinear vibrational spectroscopy for live-cell dynamics. Her work spans super-resolution label-free imaging , quantitative polyQ aggregate analysis in Huntington’s disease, Raman-guided pharmacometabolomics for melanoma, and environmental sensing in subcellular systems. Recent Publications highlight trends in vibrational thermometry (2025), high-speed bond-selective imaging (2025), and photochromic Raman microscopy (2023), with applications from single-molecule to cellular biology . 2024 Margaret Oakley Dayhoff Award 2023 NSF CAREER Award 2022 Sloan Research Fellowship 2021 Scialog Fellow Students : 5 Ph.D. graduates (Dr. Jiajun Du, Dr. Kun Miao, Dr. Xiaotian Bi, Dr. Li-En Lin, Dr. Dongkwan Lee) and current advisees including Adrian, RJ, Phil, Yulu, Berea, and Kwan. The lab has received grants from the Chan Zuckerberg Initiative, NSF, Curci Foundation, and Eli Lilly. Labs & Collaborations : The Wei Lab at Caltech collaborates with Karthikeyan (metabolic imaging) and Mazmanian Labs (microbiome studies). They host interdisciplinary teams in physical chemistry and chemical biology.
Daniel Braun is a Professor at the University of Tübingen, affiliated with the Faculty of Mathematics and Natural Sciences and the Department of Physics. He holds the Theoretical Physics (Braun Chair) and has been active in academia since October 1, 2013. Email: daniel.braun@uni-tuebingen.de Research Interests: His work bridges quantum optics, metrology, and gravitational physics. He explores quantum-enhanced measurement techniques, nonlinear optical phenomena in curved spacetime, and mechanical systems for fundamental tests of physics. Institutional Affiliation: Institute for Theoretical Physics (ITP) Recent Publications (2025-2024): Focus on quantum-limited interferometry, machine learning applications in quantum channels, gravitational effects in particle accelerators, and nonlinear soliton dynamics in relativistic settings. Scientific Awards: No specific awards mentioned in the provided data.
Andrea Pickel is an Assistant Professor at the University of Rochester, holding joint appointments in the Department of Mechanical Engineering, Materials Science, and the Institute of Optics, while also serving as a Scientist at the Laboratory for Laser Energetics (LLE). She received her PhD in Mechanical Engineering from UC Berkeley (2019) and a BS from Carnegie Mellon University (2014). Her research focuses on nanoscale heat transfer, leveraging luminescent materials and super-resolution imaging to address challenges in thermal management, catalysis, and energy systems. Education: PhD, Mechanical Engineering, UC Berkeley, 2019 BS, Mechanical Engineering, Carnegie Mellon University, 2014 Research interests include luminescence nanothermometry, single-nanoparticle imaging, and high-temperature thermal metrology. Her work integrates experimental methods like stimulated emission depletion (STED) imaging and operando spectroscopy to advance understanding of energy transport at the nanoscale. Notable awards include the NSF CAREER Award (2022), ACS PRF Doctoral New Investigator Award (2020), and Furth Fund Award (2021). She was also named a Scialog Fellow in 2024. Advancing thermal measurement techniques, her group collaborates across disciplines to tackle applications in carbon capture, battery technology, and plasmonic photocatalysis. Current projects emphasize developing dual-mode sensing tools for real-time thermal and chemical monitoring. Labs/Teams: Active at the Laboratory for Laser Energetics (LLE) and leads the Pickel Research Group in the Department of Mechanical Engineering.
Lili Qiu is a Professor in the Department of Computer Science at The University of Texas at Austin, where she has been a faculty member since January 2005. She is an active member of the Wireless Networking and Communications Group (WNCG) and has made significant contributions to the field of networking research. Dr. Qiu previously spent 2001-2004 as a researcher at Microsoft Research in Redmond, WA, before joining UT Austin. Dr. Qiu's research spans Internet and wireless networking with a current focus on wireless network management and content distribution in mobile networks. Her work extends into diverse applications including acoustic imaging, metasurface applications, healthcare sensing technologies, and AI systems. She has pioneered research in areas such as acoustic motion tracking, passive RFID sensing, and wireless network optimization. Her research demonstrates a consistent pattern of innovation that bridges theoretical networking concepts with practical real-world applications, particularly in mobile and wireless systems. Her extensive publication record shows a clear evolution from fundamental networking research to increasingly interdisciplinary work that combines wireless systems with healthcare applications, AI, and novel sensing technologies. Recent publications demonstrate growing integration of machine learning techniques with traditional networking problems, as well as expansion into healthcare applications like Parkinson's disease modeling and non-invasive glucose monitoring. ACM Fellow IEEE Fellow National Academy of Inventors (NAI) Fellow ACM Distinguished Scientist NSF CAREER award Google Faculty Research Award Best paper award at ACM MobiSys'18 Best paper award at IEEE ICNP'17 Dr. Qiu has supervised numerous students, including a PhD dissertation that won the SIGMOBILE best dissertation award in 2020. She has served in significant leadership roles including chair of ACM SIGMOBILE, General co-chair for ACM MobiCom 2025, and various conference chair positions for IEEE ICNP, ACM CoNEXT, and other major networking conferences. Her research has been supported by substantial grants from NSF, Google, and other organizations, enabling her to lead cross-disciplinary research teams. As a member of the Wireless Networking and Communications Group at UT Austin, Dr. Qiu leads research efforts that combine networking expertise with innovations in sensing technologies, metasurfaces, and AI systems. Her lab has produced numerous influential results in mobile networking, wireless sensing, and network management, with applications spanning healthcare, consumer electronics, and communication infrastructure.
Fabrizio Falchi is a researcher at the Artificial Intelligence for Media and Humanities (AIMH) Lab of the Institute of Information Science and Technologies (ISTI) within Italy's National Research Council (CNR). He also maintains an associate position at the Biorobotics Institute of Scuola Superiore Sant'Anna. His work focuses on developing advanced multimedia retrieval systems, with the VISIONE platform being his most notable contribution, which has won international competitions including the Video Browser Showdown in 2024 and placed second in 2023. Falchi's educational background includes: Ph.D. in Information Engineering from University of Pisa (Italy) Ph.D. in Informatics from Faculty of Informatics of Masaryk University of Brno (Czech Republic) M.B.A. from Scuola Superiore Sant'Anna in Pisa His research spans deep learning, convolutional neural networks, deep features extraction, similarity search algorithms, distributed indexing systems, multimedia information retrieval, computer vision applications, and peer-to-peer systems. Falchi has made significant contributions to fine-grained visual understanding, cross-modal retrieval (particularly image-text matching), and robustness of deep learning systems against adversarial attacks. His work demonstrates a strong focus on practical applications of these technologies, particularly in video retrieval systems and safety monitoring solutions. Analysis of Falchi's recent publications reveals a strong focus on video and image retrieval systems, with the VISIONE platform being central to his work. His research shows increasing emphasis on fine-grained understanding in computer vision, cross-modal retrieval, and addressing practical challenges like cross-resolution face recognition. Recent work demonstrates innovation in making these systems more efficient through techniques like knowledge distillation (ALADIN) and leveraging virtual worlds for training data. His publications consistently bridge theoretical advances with practical applications in surveillance, safety monitoring, and multimedia search. Falchi's work has received significant recognition: Best paper award at CBMI 2024 for 'Is ClLIP the main roadblock for fine-grained open-world perception?' VISIONE 2024 won the Video Browser Showdown competition in Amsterdam VISIONE obtained second place at Video Browser Showdown 2023 in Bergen Best Paper Award for 'Learning Safety Equipment Detection using Virtual Worlds' at CBMI 2019 Falchi collaborates extensively with researchers at ISTI-CNR, particularly within the AIMH Lab. His work on VISIONE involves collaboration with Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. As co-chair of Ital-IA 2023, the 3rd National Conference on Artificial Intelligence, he plays an active role in the academic community. He is a member of ACM (since 2012), the Computer Vision Foundation, the Italian Association for Computer Vision Pattern Recognition and Machine Learning (CVPL), and the CINI Lab on Artificial Intelligence and Intelligent Systems. Falchi is a key member of the Artificial Intelligence for Media and Humanities (AIMH) Lab at ISTI-CNR, where he leads research on video retrieval systems. The lab has developed the award-winning VISIONE platform, which combines multiple scientific results in content-based video retrieval. His team focuses on developing systems that enable users to search for target videos using textual prompts, drawing objects and colors, or images as query examples. The lab's work demonstrates strong interdisciplinary collaboration, bridging computer science with practical applications in media, safety monitoring, and urban environments.
Peter Burke is a Professor of Electrical Engineering and Computer Science (joint appointments in Biomedical Engineering and Materials Science and Engineering ) at the Samueli School of Engineering, University of California, Irvine . His research bridges nanoelectronics with biotechnology , focusing on carbon nanotubes , graphene devices , and mitochondrial bioenergetics . He has received prestigious Young Investigator Awards from the Office of Naval Research and Army Research Office. Education: B.A. in Physics, University of Chicago (1992) Ph.D. in Physics, Yale University (1998) His work spans quantum electronics , high-speed semiconductor devices , and bio-nano interfaces . Recent publications highlight drone technology , mitochondrial electrical activity , and AI-driven nanoscale sensing . Research trends include terahertz spectroscopy , super-resolution imaging , and open-source medical devices like the NanoStat potentiostat . Scientific Awards Young Investigator Award, Office of Naval Research Young Investigator Program Award, Army Research Office As director of the BurkeLab , he develops nano-electronic interfaces for biological systems, including mitochondrial membrane potential assays and graphene-based biosensors . His lab's innovations in carbon nanotube arrays and scanning microwave microscopy have advanced bio-nano applications.
