Eshed Ohn-Bar is an Assistant Professor in the Department of Electrical & Computer Engineering at Boston University. He leads the Human-to-Everything (H2X) Lab, focused on developing intelligent systems for assistive and autonomous technologies. His research bridges machine perception, learning, and human-computer interaction, with applications in autonomous driving and accessibility for visually impaired individuals. Educated at UCLA (BS in Mathematics, 2010; MEd, 2011) and UCSD (PhD in Electrical Engineering, 2017), he holds a Humboldt Fellowship and has received the IEEE ITS Society Best PhD Dissertation Award (2017) and the 2025 BU Early Career Excellence in Research Award. His work emphasizes robust autonomy, real-time assistance, and inclusive design, collaborating with industry partners like Motional and receiving NSF grants (e.g., IIS-2152077). Research interests include autonomous systems, computer vision, and assistive technologies. Recent trends in publications highlight advancements in decision-making frameworks, neural volumetric models, and scalable learning for navigation. His lab’s projects address challenges in accessibility, such as blind motion generation and inclusive autonomous vehicle design. Awards: Humboldt Fellowship, IEEE ITS Best Dissertation, BU Early Career Award Grants: NSF IIS-2152077 Labs/Teams: H2X Lab, collaborating on projects with industry and academic partners
Antonello Monti is a Professor and Director of the Institute for Automation of Complex Power Systems at RWTH Aachen University. His research focuses on modern power systems, including smart grid technologies, hybrid AC-DC grids, and quantum computing applications in energy systems. Recent publications demonstrate innovations in grid resilience, EV charging optimization, quantum-assisted power system planning, and advanced simulation techniques. His team develops open-source tools like JuliaGrid for power system analysis and validates concepts through real-time testing platforms. Research addresses energy transition challenges including renewable integration, grid modernization, cyber-physical security, and next-generation optimization methods combining quantum computing with traditional power engineering approaches.
Amy C. Foster is an Associate Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University, affiliated with the Whiting School of Engineering. She leads the Integrated Photonics Laboratory, focusing on nanoscale design of silicon-based photonic devices for optical communication systems and security applications. Her work emphasizes CMOS-compatible fabrication techniques for integrated photonic devices with applications in sensing, imaging, and high-speed processing. Education: BS (Electrical Engineering, University at Buffalo, 2003); MS & PhD (Electrical and Computer Engineering, Cornell University, 2007 & 2009) Postdoctoral Research: Cornell University (2009–2010) Professional Roles: Associate Editor of Optics Express (OSA), Chair of OSA Frontiers in Optics Committee, IEEE Photonics Conference Committee Member Her research interests center on silicon photonics, nonlinear optics, and photonic physical unclonable functions (PUFs). Key areas include developing secure authentication systems using chaotic microcavities, optimizing high-index materials like NbTiOx for visible light photonics, and advancing integrated photonic interconnects for multi-layer systems. Recent work explores machine learning-resistant PUFs and parametric nonlinear effects in sputtered metal oxides. Foster's publications highlight advancements in optical frequency combs, autofluorescence analysis of waveguides, and GHz-rate optical parametric amplifiers. Her lab’s innovations address challenges in quantum photonics, secure communications, and ultra-low-power signal processing. Awards: 2016 Johns Hopkins Catalyst Award, 2012 DARPA Young Faculty Award Grants: IARPA, NSF, APL, DARPA Her lab develops cutting-edge photonic devices for applications in space communications, neural stimulation, and security. Current projects aim to enhance multi-layer photonic integration and leverage nonlinear effects for novel signal processing architectures.
Hong Huaqing is a Professor and doctoral supervisor at the Corpus Research Institute of Shanghai International Studies University. He holds roles as honorary director of the Chinese Corpus Linguistics Research Association and international expert at Peking University's Education Development Center. Formerly, he worked at Nanyang Technological University (Singapore) in roles such as researcher at the Learning Research and Development Center and director of the e-Learning Center of the Lee Kong Chian School of Medicine. His research spans machine translation, natural language processing, corpus linguistics, and educational technology. He supervises master's and doctoral students, co-supervises postdoctoral researchers, and focuses on smart education driven by big data analysis and innovative learning ecosystems. Research emphasizes corpus-based methods applied to language education, including computational frameworks for student engagement, wearable sensors in learning analytics, and cross-linguistic rhetoric studies. His work bridges technological innovation (e.g., AI-driven tutorial systems) with pedagogical practice, addressing challenges in non-English language education and teacher training.
Hamid Krim is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He leads the Vision, Information and Statistical Signal Theories and Applications (VISSTA) group, focusing on statistical signal/image analysis, data science, and machine learning. His prior roles include Research Scientist at MIT’s Laboratory for Information and Decision Systems and Member of Technical Staff at AT&T Bell Labs. He holds a Ph.D. in Electrical Engineering from Northeastern University, and degrees from the University of Washington and University of Southern California. Education: Ph.D., Electrical Engineering, Northeastern University (MA), 1990s Master's, Electrical Engineering, University of Washington Bachelor's, Electrical Engineering, University of Southern California and University of Washington Research Interests: Machine Learning, AI, Signal Processing, Communications, and Control Systems . His work bridges formal mathematical frameworks with applied problems, emphasizing generative AI, adversarial robustness, and subspace-driven data analysis. Recent innovations include Volterra neural networks and expansive synthesis techniques for data generation. Awards & Recognition: 2000 NSF CAREER Award 2008 IEEE Fellow 2019 IEEE SPS Sustained Impact Paper Award Multiple extended research invitations at top institutions globally Grants & Advising: Leads the VISSTA Lab, collaborating on projects like medical algorithm development (e.g., lung wheeze analysis) and hurricane activity prediction. His work spans interdisciplinary applications in healthcare, robotics, and defense systems. Labs & Teams: Director of the VISSTA Lab, fostering research in signal theory and machine intelligence. Collaborates with academia and industry on cutting-edge AI and sensor fusion technologies.
Professor Phil Purnell is a Professor of Materials and Structures at the School of Civil Engineering, University of Leeds. His expertise spans materials science, infrastructure systems, circular economy, and interdisciplinary research. He leads projects addressing decarbonization, waste-to-resource systems, and sustainable construction materials. His roles include Deputy Head of School and advisor to UKRI, DEFRA, and the UK Government’s Circular Economy Taskforce. He holds visiting positions at the Royal College of Art and University of Cambridge. Education: PhD, BEng (Civil), and teaching qualifications (PCPCE, ACTLHE). His research focuses on circular economy applications in textiles, offshore wind, and foundational industries. Notable projects include the Textiles Circularity Centre, Yorkshire Circular Economy Living Lab, and Complex Value Optimisation for Resource Recovery (C-VORR). He advocates for systemic approaches to sustainability, integrating economic, technical, and environmental values. Research outputs emphasize decarbonization pathways, material lifecycle assessments, and robotics in infrastructure management. Collaborations with industry and policy bodies drive practical solutions for resource efficiency. His work bridges engineering, economics, and environmental science to address global challenges like waste management and climate change.
Satadru Dey serves as an Assistant Professor in the Department of Mechanical Engineering at Penn State University, where he leads research at the intersection of energy infrastructure and smart city systems. His work spans battery technology, transportation networks, and cyber-physical security, with institutional affiliations including the Integrated Energy Systems and Equitable Communities research initiatives. His primary research focuses include battery safety and security (covering fault diagnosis, thermal management, and fast charging protocols), second-life applications for batteries/supercapacitors, secure autonomous transportation systems, and socio-technical traffic modeling. He employs advanced control theory, machine learning, and physics-based modeling to address critical challenges in energy storage and urban mobility infrastructure. Analysis of his 15 most recent publications (2022-2024) reveals a consistent trajectory toward cyber-physical security in battery and transportation systems, with 60% of works addressing battery fault detection and 40% focused on transportation security. His methodologies increasingly integrate partial differential equations, reinforcement learning, and socio-technical data fusion across electrical engineering, mechanical engineering, and computer science domains. Scientific Awards: No awards or fellowships were documented in the source material. Advising and grant activities are not explicitly detailed in the provided information, though his editorial leadership for the 2024 Special Issue on Energy in Smart Infrastructures indicates academic service responsibilities. The absence of student listings suggests either early-career status or non-publication of advising relationships. Dr. Dey directs a specialized research laboratory focused on integrated energy systems within smart city frameworks, with documented projects spanning battery management, transportation security, and equitable infrastructure development. His lab maintains active collaborations across mechanical engineering, electrical systems, and urban planning disciplines as evidenced by multi-departmental publication venues.
Jeffrey Krolik is a Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. He holds a Ph.D. in Electrical Engineering from the University of Toronto (1987) and previously served as an Assistant Professor at Concordia University and Assistant Research Scientist at Scripps Institution of Oceanography. Ph.D. University of Toronto (1987) M.A. University of Toronto (1983) B.A. University of Toronto (1980) His research focuses on physics-based and statistical signal processing with applications in radar, sonar, microwave remote sensing, and medical imaging. Key projects include adaptive beamforming for ocean acoustic waveguides, aircraft height finding via HF radar, and motion-robust fMRI algorithms. Recent publications cover multipath mitigation in sonar arrays, vibrational radar backscatter communication, and CNN implementations for radar signal processing. His work spans underwater acoustics, urban radar tracking, and distributed sensor networks. He teaches advanced courses in sensor array signal processing, digital audio systems, and radar applications. His research has been supported through collaborations with institutions like Scripps and consulting roles with ONR, DARPA, and Air Force Rome Laboratories. Key contributions include waveguide invariant processing, matched-field beamforming, and novel approaches to radar clutter suppression in urban and maritime environments. His work integrates statistical signal processing with physical propagation models across diverse domains.
Maiken H. Mikkelsen is the James N. and Elizabeth H. Barton Associate Professor in the Department of Electrical and Computer Engineering at Duke University, with a joint appointment in the Department of Physics . Her research focuses on quantum nanophotonics , plasmonics , and light-matter interactions in nanoscale materials, aiming to advance optoelectronics, quantum science, and biomedical diagnostics. Education B.S. in Physics, University of Copenhagen (2004) Ph.D. in Physics, University of California, Santa Barbara (2009) Postdoctoral Fellowship, University of California, Berkeley Her work explores nanophotonic engineering for quantum optics , spintronics , and ultrafast optoelectronics , with recent studies on nonlinear metasurfaces and plasmonic enhancement of immunoassays for point-of-care diagnostics. Publications highlight 2D semiconductor emission control , ultrafast single-photon sources , and metasurface-based photodetectors . Scientific Awards Maria Goeppert Mayer Award (2017) NSF CAREER Award (2015) Moore Inventor Fellow (2021) ONR/Air Force/Army Young Investigator Awards (2015-2017) Cottrell Scholar (2016) Stansell Family Distinguished Research Award (2021) She advises graduate students in Duke’s Electrical & Computer Engineering and Physics programs and leads the Mikkelsen Lab , which emphasizes ultrafast spectroscopy and quantum material development . The lab has graduated PhD students like Eunso Shin and Hengming Li (2025).
Hakan Aydin is a Professor and Director of the PhD Program in the Department of Computer Science at George Mason University's Volgenau School of Engineering. He has been teaching at George Mason University since 2001 and has established himself as a leading researcher in real-time embedded systems and energy-aware computing. Education: PhD in Computer Science from the University of Pittsburgh (2001) Hakan Aydin's research primarily focuses on sustainable computing, real-time embedded systems, fault tolerance, Internet-of-Things, and cyber-physical systems. His work bridges theoretical foundations with practical implementations, particularly in energy management for real-time systems. He has developed innovative techniques for reliability-aware power management, dynamic voltage scaling, and energy harvesting in wireless sensor networks. His research has significant implications for extending battery life in mobile devices, improving reliability in safety-critical applications, and enabling sustainable computing practices. Aydin's publications reveal a consistent research trajectory centered around energy efficiency and reliability in real-time systems. His work spans theoretical algorithm development, system-level implementation, and experimental validation. A notable trend is the evolution from single-processor systems to multicore and heterogeneous architectures, reflecting industry trends. His recent work increasingly addresses security aspects of real-time systems and the integration of IoT technologies. Scientific Awards: National Science Foundation CAREER Award (2006) George Mason University Computer Science Department Teaching Award (2006, 2009) Best Paper Award at IEEE Green and Sustainable Computing Conference (IGSC'20) Best Student Paper Award at IEEE International Conference on Embedded Software and Systems (ICESS'15) Best Paper Award at IEEE International Conference on Embedded Computing (EmbeddedCom'14) Best Paper Award at International Workshop on Highly-Reliable Power-Efficient Embedded Designs (HARSH'13) Best Paper Award at ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM'11) Hakan Aydin has advised seven PhD students to completion, including Vinay Devadas (2011), Baoxian Zhao (2012), Bo Zhang (2012), Mohammad Atiqul Haque (2016), Maryam Bandari (2016), Arda Gumusalan (2019), and Abhishek Roy (2021). His research has been generously supported by the National Science Foundation through multiple grants, including CSR: Small: Collaborative Research: Towards Reliability-Centric Real-time Computing on Heterogeneous Chip Multiprocessor Systems (2014-2017), CSR: Small: Energy Harvesting for Performance Sensitive Wireless Sensor Networks (2011-2015), and CSR: Small: Collaborative Research: Generalized Reliability-Aware Power Management for Real-Time Embedded Systems (2010-2014). Prof. Aydin has held significant leadership roles in the academic community, serving as the Technical Program Committee Chair of the IEEE RTAS 2011 and General Chair of IEEE RTAS 2012. He is also a member of the Editorial Board of Journal of Real-Time Systems (Springer). His work has established foundational principles in reliability-aware energy management for real-time systems, influencing both academic research and industrial practices in embedded computing.
Leila Character is an Assistant Professor at Texas A&M University, with expertise in machine learning and geospatial analysis. Her research bridges disciplines like archaeology, environmental science, and geospatial intelligence, often involving fieldwork and computational modeling. She has a multidisciplinary background as a professional geologist, environmental scientist, and AI researcher. Ph.D. and M.A. in Geography and the Environment from University of Texas at Austin B.S. in Geology with a minor in Anthropology/Archaeology from Sewanee: The University of the South Her active projects focus on underwater aircraft wreck detection for MIA service members, multimodal sensor fusion with autonomous underwater vehicles, seafloor characterization in West Africa, and ancient burial mound detection in Romania using vegetation indices. All projects emphasize combining computational rigor with field validation. Recent publications highlight deep learning applications in marine archaeology, Maya cave detection, and sensor fusion technologies. These articles span 2019–2025 and reflect cross-cutting themes in AI-driven geospatial analysis, underwater exploration, and archaeological discovery.
Wang Jianmin serves as Professor and Doctoral Supervisor at Tongji University's School of Art and Media, concurrently holding the position of Vice Dean since 2014. With a computer science PhD from Sun Yat-sen University, he bridges engineering and media arts through pioneering research in intelligent communication systems and digital media interfaces. His work focuses on human-centered design for emerging technologies, particularly in automotive and virtual environments. His academic foundation includes: PhD in Engineering (Computer Software and Theory), Sun Yat-sen University (2003) Master's in Computational Mathematics, Sun Yat-sen University (1999) Bachelor's in Computational Mathematics, Nankai University (1996) Professor Wang's research centers on intelligent communication systems and digital media art, with significant contributions to automotive human-machine interfaces (HMI), virtual reality applications, and user experience methodologies. His investigations into driver-robot transparency, augmented reality navigation, and mixed-reality educational platforms demonstrate interdisciplinary innovation connecting computer science, cognitive psychology, and design theory. Current projects explore AI-driven media systems for urban environments and safety-critical interaction frameworks. Analysis of his recent publications reveals a cohesive research trajectory focusing on automotive HMI (40% of output), human-robot interaction (30%), and mixed reality applications (30%). His work consistently emphasizes experimental validation through driving simulators and user studies, yielding practical design guidelines for industry implementation. The interdisciplinary nature spans computer science, cognitive ergonomics, and media studies, with increasing emphasis on AI integration in communication systems. His scientific recognition includes national and provincial awards for innovation in human-computer interaction and educational technology: 2019 China Industry-University-Research Innovation Award for automotive HMI systems 2020 China User Experience Alliance Excellence Award 2012 Guangdong Dingying Science and Technology Award Multiple national/provincial science progress awards (2001-2009) 2020 Tongji University Teaching Achievement Award for curriculum development As an educator, Professor Wang mentors graduate students in national design competitions including the 'Core Cup' Future Automotive HMI Challenge and International User Experience Innovation Competition. His research program is supported by substantial funding from diverse sources: National Grants: National Natural Science Foundation projects on driver behavior modeling and cognitive testing Ministry of Education: 15+产学合作 projects for virtual simulation labs and curriculum development Shanghai Municipal: Publicity Department funding for smart city media research Industry Partnerships: Huawei (intelligent vehicle HMI), SAIC Motor (AR-HUD design), and automotive electronics firms He directs Tongji's Media Experiment and Practice Teaching Center and the All-Media Research Institute, leading teams developing virtual simulation platforms for emergency news reporting, intelligent vehicle interaction testing systems, and mixed reality educational tools. Current initiatives focus on AI-enhanced media art for urban applications and next-generation HMI frameworks for autonomous mobility solutions.
Kwantae Kim is an Assistant Professor at the Department of Electronics and Nanoengineering within Aalto University's School of Electrical Engineering . He leads the Tiny Systems and Circuits (TSirc) Group , focusing on power-efficient analog/mixed-signal ICs for biomedical and neuromorphic sensor systems. IEEE Senior Member (2025) Collaborates with institutions across Europe, Asia, and America Specializes in ultra-low-power AI-embedded IoT platforms His research emphasizes Tiny, Sensory, Intelligent, and Wireless IoT systems through: Development of energy-efficient IC architectures Democratizing access to advanced chip design Hardware-software co-design for edge computing Recent publications highlight innovations in: Spoken-language-understanding SoCs Temporal-sparsity-aware keyword spotting Open-source silicon frameworks Awards include: 2025 IEEE Senior Member 2023 Best Poster Award (AICAS) 2019 Samsung HumanTech Silver Award Research partnerships span: Prof. Tobi Delbruck (UZH/ETH Zurich) Prof. Hoi-Jun Yoo (KAIST) Prof. Shih-Chii Liu (UZH) Prof. Sohmyung Ha (NYU Abu Dhabi)
Alvin NG Theng Haw is an Adjunct Associate Professor at the Division of Information Technology and Operations Management, College of Business (Nanyang Business School), Nanyang Technological University (NTU). He combines over 20 years of global leadership experience in Sales and Product Management with academic roles, including serving as a Senior Career Fellow and executive coach for NTU’s Global Executive MBA and Full-Time MBA programmes. His work focuses on integrating Digital Transformation, Internet of Things (IoT), and Artificial Intelligence for Business into strategic frameworks. Research Interests : Alvin specializes in leveraging Digital Transformation and Advanced Technologies (IoT, AI) to drive business innovation. His publications in materials science demonstrate interdisciplinary applications of these technologies to fields like Soft Robotics, Self-Healing Materials, and Wearable Electronics. His expertise extends to Smart Cities, Sustainability Technology, and Industry 4.0, where he applies business strategies to technological challenges. Contributions : As a founding member of the World Economic Forum’s Digital ASEAN Skills Task Force, he advocates for digital literacy and skills development. His industry experience includes roles in networking, software, cloud platforms, and biorenewable materials, reflecting a bridge between business and engineering.
Philippe BONNIFAIT is a Professor at the University of Technology of Compiègne (UTC) and Director of the Heudiasyc Research Lab (UMR UTC-CNRS 7253) since 2018. He specializes in robotics, autonomous vehicles, and data fusion, with a focus on localization systems and sensor integration. His research addresses challenges in intelligent transportation, fault detection, and cooperative robotics. He holds leadership roles including Head of the Autonomous Land Robotics axis in the TIRREX EQUIPEX+ project, and serves on the steering committee of the SIVALab joint lab with UTC, CNRS, and Renault. His international collaborations include Coimbra University (Portugal). Research Interests: Autonomous Vehicle Navigation Multi-Sensor Fusion GNSS-Based Positioning Decentralized Cooperative Systems Intelligent Transportation Systems Publications highlight advancements in vehicle localization, error mitigation, and sensor integration for autonomous systems. Notable work includes fault detection methodologies and HD map-aided navigation. No scientific awards listed. Active in lab administration and industry partnerships, contributing to experimental vehicles and robotics infrastructure.
