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Rui Zhang is an Associate Professor in the Department of Computer and Information Sciences at the University of Delaware. He holds a PhD in Electrical Engineering from Arizona State University (2013) and has held academic positions at the University of Hawaii and industry roles at UTStarcom. His research focuses on cybersecurity, wireless networks, and privacy-preserving technologies, with notable work on secure edge computing and mobile authentication systems. Education: PhD, Electrical Engineering, Arizona State University, 2013 M.E., Communication and Information Systems, Huazhong University of Science & Technology, 2005 B.E., Communication Engineering, Huazhong University of Science & Technology, 2001 Research Interests: Rui’s work spans secure wireless systems, mobile crowdsourcing, accessibility technologies for visually impaired users, edge computing, and social network privacy. He has led NSF-funded projects on trustworthy hierarchical edge computing and secure mobile cloud sensing. Grants & Awards: Recipient of the NSF CAREER Award (2017) and multiple NSF grants totaling over $1M. Current focus includes NSF-funded research on edge computing security and privacy-preserving data aggregation. Teaching: Has taught courses in algorithms, network security, and computer networks at both University of Delaware and University of Hawaii. Labs & Teams: Leads research projects in secure edge computing and collaborates with Arizona State University on federally funded initiatives. Active in organizing academic conferences like ISC 2016 and serving on editorial boards of IEEE journals.

• Cybersecurity
• Wireless Networks Security
• Mobile Systems for Disabled Individuals
• +5 more

Wei Xiang is an Assistant Professor of Economics at the University of Michigan's Department of Economics, housed within the College of Literature, Science, and the Arts. He earned his Ph.D. in Economics from Yale University in 2024, focusing on international trade, macroeconomics, and environmental economics. His research bridges economic theory with applied analyses, addressing global trade dynamics, macroeconomic policies, and environmental sustainability. Education: Ph.D. in Economics, Yale University (2024). Research Interests: His work explores the intersection of international trade policies, macroeconomic stability, and environmental regulations. He examines how trade agreements influence economic growth and environmental outcomes, with a focus on empirical methodologies to assess policy impacts. Additionally, he investigates macroeconomic models to understand global economic fluctuations and their implications for sustainable development. Publications: His recent articles highlight contributions to vehicle communication systems, signal processing, and wireless technologies, reflecting interdisciplinary engagement with engineering applications. These include real-time prediction models for GPS errors and beamforming optimization in vehicular networks. Labs/Teams: Not explicitly stated, but his research collaborations likely involve interdisciplinary teams in economics, engineering, and environmental science.

• Economics
• International Economics
• Macroeconomics
• +3 more

Danick Briand is a Senior Scientist at the Soft Transducers Laboratory within the Microsystems for Space Applications Group (LMTS) at École Polytechnique Fédérale de Lausanne (EPFL). His work focuses on MEMS and Microsystems for environmentally friendly technology , integrating flexible and printed electronics with applications in energy harvesting , smart sensing systems , and advanced gas sensing . Research Themes : Environmental sensors using microsystem technology Green microtechnologies and micromanufacturing Ultra-low energy MEMS Energy-saving and harvesting systems Recent Publications : Developed transient biodegradable sensors and microwave sensing technologies using printed and degradable materials Explored flexible piezoelectric systems and wearable sweat analyzers for biomedical applications Advanced inkjet-printed biosensors and eco-friendly fabrication methods Labs & Collaborations : Soft Transducers Laboratory (EPFL) Laboratory for Microsystems (LMTS)

• MEMS and Microsystems
• Flexible and Printed Electronics
• Energy Harvesting
• +4 more

Yimin D. Zhang is an Associate Professor in the Department of Electrical and Computer Engineering at Temple University's College of Engineering, where he leads the Advanced Signal Processing (ASP) Lab. His research spans statistical signal processing, array processing, radar, wireless communications, and convex optimization. Research Interests: Dr. Zhang's work focuses on cutting-edge signal processing techniques including compressive sensing, sparse arrays, time-frequency analysis, and robust beamforming. These are applied to radar systems, satellite navigation, assisted living, and wireless networks. His research addresses core challenges in target localization, direction-of-arrival estimation, and spectrum-efficient joint radar-communication systems. The recent publications highlight a strong trend in exploiting sparsity, virtual arrays, and deep learning to enhance resolution and robustness in radar and communication systems. Themes include multi-frequency processing, low-rank matrix recovery, and optimized OFDM waveforms for dual-function systems. Scientific Awards: 2016 IET Radar, Sonar and Navigation Premium Award 2017 IEEE Aerospace and Electronic Systems Society Harry Rowe Mimno Award 2018 IEEE Signal Processing Society Young Author Best Paper Award (coauthor) Advising and Grants: Dr. Zhang has served as Principal or Co-Principal Investigator on over $6 million in research funding from the NSF, AFRL, ONR, and DARPA. While student advisees are not listed, his leadership of the ASP Lab suggests active mentorship of graduate researchers. He contributes extensively to the academic community as an associate editor for IEEE Transactions on Signal Processing and editor for Signal Processing journal, and serves on key IEEE technical committees. Labs and Teams: He directs the Advanced Signal Processing (ASP) Lab at Temple University, which focuses on developing novel algorithms for real-world applications in radar, communications, and navigation. Previously, he led the Wireless Communications and Positioning Lab and the RFID Lab at Villanova University.

• Statistical Signal Processing
• Array Processing
• Radar Signal Processing
• +10 more

Maher Elshakankiri is an Assistant Professor, Teaching Stream at the University of Toronto's Faculty of Information. He holds a Ph.D. in Computer Engineering from Ain Shams University (Egypt), followed by a postdoctoral fellowship at the University of Regina. His research focuses on IoT, Wireless Sensor Networks (WSN), and pedagogical integration of technology and gaming. He has supervised over 100 student projects and authored a book on WSNs. Education: Ph.D. in Computer Engineering, Ain Shams University, Egypt M.Eng., B.Eng. in Engineering, Ain Shams University, Egypt Postdoctoral Fellowship, University of Regina, Canada Research Interests: IoT in healthcare, agriculture, and sports Active learning classrooms and technology in education Wireless communication protocols (V2V, UAV, RFID) Leadership & Grants: Director, Bachelor of Information (BI) Program (2024–present) Coordinator, Information Systems and Design (ISD) Concentration (2023) SSHRC Grant: 'Gaming in teaching towards a more inclusive class' (2022–2023) Professional Activities: Member, SCC IoT & Digital Twins Standards Committee Reviewer for journals including Wireless Networks , Telematics and Informatics , and Computational Intelligence Technical Program Committee member at multiple conferences Teaching: Courses include INF1340 (Programming for Data Science), INF1005/1006 (IoT Workshops), and INF452 (Information Design Coding).

• Internet of Things (IoT)
• Wireless Sensor Networks (WSN)
• Active Learning Classrooms
• +5 more

Dr. Binbin Xie is an Assistant Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA). She holds a Ph.D. from the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst, where she was a recipient of the prestigious Google PhD Fellowship in Mobile Computing. Her research focuses on wireless sensing, mobile health, cyber-physical systems, smart IoT, and wireless networking. Dr. Xie’s academic journey includes a tenure-track position at UTA since September 2024. She has received notable awards such as the Emerging Rockstar (IEEE Pervasive Computing, 2025), Rising STARs Award (UT System, 2024), and multiple scholarships including the Krithi Ramamritham Computer Science Scholarship (2023). Her work spans innovative applications in wireless sensing, leveraging LoRa, mmWave radar, and RFID technologies for real-world challenges like in-vehicle sensing and indoor localization. Her recent publications highlight advancements in LoRa sensing coexistence with communication, mmWave radar human sensing using secondary reflections, and combating interference in multi-target localization. She actively contributes to the academic community through service roles, including Technical Program Committee memberships for MobiSys 2025 and EWSN 2025, and as a reviewer for top-tier conferences like IMWUT/UbiComp and journals such as ACM Transactions on Sensor Networks. Dr. Xie’s teaching includes courses like CSE 4321 (Software Testing & Maintenance). Her research and educational efforts aim to bridge theoretical innovations with practical implementations in wireless and IoT systems.

• Wireless Sensing
• Mobile Health
• Cyber-physical Systems
• +5 more

Ruonan Han is a Professor of Electrical Engineering and Computer Science at MIT and serves as Associate Director of the Microsystems Technology Laboratories (MTL) and Director of the MIT-MTL Center for Integrated Circuits and Systems . His research focuses on ultra-high-frequency microelectronic circuits , particularly addressing the 'terahertz gap' in sensing, metrology, security, and communication. He leads the Terahertz Integrated Electronics Group at MIT's MTL, established in 2014. Education: B.S. in Microelectronics, Fudan University (2007) M.S. in Electrical Engineering, University of Florida (2009) Ph.D. in Electrical and Computer Engineering, Cornell University (2014) Research Interests: Terahertz (THz) integrated circuits and systems High-frequency CMOS technologies Quantum sensing and magnetometry RF systems for imaging, radar, and molecular sensing Energy-efficient communication systems His work bridges electronic circuits , electromagnetics , and quantum physics , with applications in defense, healthcare, and environmental monitoring. Awards & Recognition: 2023 IEEE SSCS New Frontier Award 2020 NSF CAREER Award 2019 Intel Outstanding Researcher Award 3× IEEE RFIC Best Student Paper Awards (2012, 2017, 2021) Advising & Leadership: Ph.D. advisor to over 10 students (many recipients of MIT MTL Dissertation Awards) Co-advises with Prof. Anantha Chandrakasan and Prof. Tomás Palacios Editorial roles at IEEE Transactions on Quantum Engineering and VLSI Systems Technical committee member for ISSCC, RFIC, and IMS Labs & Teams: Terahertz Integrated Electronics Group at MIT MTL: Focuses on chip-scale THz systems, quantum devices, and next-generation RF circuits Collaborations with industry (e.g., Apple, MediaTek) and academic groups (e.g., D. Englund's lab at MIT)

• Terahertz Electronics
• Integrated Circuits
• RF Systems
• +4 more

Prof. Ivan Martinovic is a Professor of Computer Science at the University of Oxford's Department of Computer Science, holding a Fellowship at the institution. He specializes in cyber-physical systems security, wireless network security, and behavioral biometrics. His research focuses on authentication mechanisms, intrusion detection, and trade-offs between security and performance in systems like satellite communications, EV charging infrastructure, and aviation networks. Education: PhD (TU Kaiserslautern); MSc (TU Darmstadt, Germany). Prior roles include postdoctoral research at UC Berkeley (2011) and UC Irvine (2009–2010), supported by a Carl-Zeiss Foundation Fellowship (2009–2011). He has also been an associate lecturer at TU Kaiserslautern. Research Interests: Cyber-physical systems security, wireless networks, behavioral biometrics (e.g., continuous authentication via physiological signals), robust communication protocols, and analysis of security vs. performance trade-offs in distributed systems. Technologies include software-defined radios, NFC/RFIDs, and EEG/eye-tracking devices. Scientific Awards: Carl-Zeiss Foundation Fellowship (2009–2011). Advising & Grants: No explicit student listings; however, his work involves interdisciplinary collaborations and has been funded by government and industrial grants. His research spans labs and teams focused on satellite cybersecurity, smart infrastructure security, and biometric systems. Labs/Teams: Engages with groups exploring satellite communication security, EV charging infrastructure vulnerabilities, and behavioral authentication systems, though specific lab names are not disclosed in the text.

• Cyber-Physical Systems Security
• Wireless Network Security
• Authentication Systems
• +3 more

Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.

• Networking and Distributed Systems
• Mobile and Sensor Systems
• Human-Computer Interactions
• +3 more

Jari Holopainen is a Senior Lecturer at the Department of Electronics and Nanoengineering , Aalto University. His work focuses on advanced antenna systems, wireless communication, and RFID technologies, with significant contributions to broadband, tunable, and wearable antenna designs. Current affiliation: Aalto University Academic role: Senior Lecturer Research interests span antenna design for mobile terminals, microwave engineering, and machine learning applications in RF systems. His publications highlight innovations in: Bluetooth antennas for metallic smartwatches and jewelry Wideband and dual-polarized antenna arrays RFID transponders with beam steering Machine learning-driven load optimization 3D-printed and capacitive-coupling antenna structures Wave propagation and scattering analysis Scientific contributions include: 15+ peer-reviewed articles (2025-2020) Collaborations with leading researchers in electromagnetics (e.g., Ville Viikari, Pertti Vainikainen)

• Antenna Design
• Wireless Communication
• RFID Technology
• +3 more

Professor Byung S. Lee is a distinguished faculty member in the Department of Computer Science at the University of Vermont's College of Engineering and Mathematical Sciences. He joined UVM in 1999 and continues to be actively engaged in teaching, research, and service. His office is located in Innovation Hall at the Burlington campus, where he maintains regular office hours and oversees his research lab. Professor Lee holds a Ph.D. from Stanford University, an MS from Korea Advanced Institute of Science and Technology, and a BS from Seoul National University. His educational background provided the foundation for his extensive career in computer science research and education. Professor Lee's research spans multiple domains within computer science, with a particular focus on database systems, data mining, and data science. His work increasingly integrates machine learning techniques with traditional database approaches, especially in the analysis of time series data. He has made significant contributions to graph theory applications, anomaly detection methods, and environmental data analysis. His research often bridges computer science with practical applications in healthcare, environmental science, transportation, and astrophysics through interdisciplinary collaborations. An analysis of his recent publications reveals a strong trend toward time series analysis and anomaly detection, particularly applied to environmental monitoring and healthcare data. His work demonstrates a consistent evolution from foundational database research to more applied machine learning approaches, with increasing emphasis on real-world problem solving across multiple scientific domains. Professor Lee has served as primary advisor for numerous graduate students across multiple cohorts, including PhD candidates, Master's students, and postdoctoral researchers. His advising portfolio reflects the breadth of his research interests, with students working on topics ranging from graph neural networks to medical informatics applications. He has also been actively involved in professional service, serving on program committees for major conferences including SAC, PAKDD, DASFAA, and CIKM. Professor Lee leads a vibrant research laboratory that focuses on cutting-edge data science methodologies and their applications. His team collaborates extensively with researchers in environmental science, hydrology, and healthcare, demonstrating the interdisciplinary nature of modern data science research. The lab maintains active projects in time series analysis, graph analytics, and environmental monitoring systems, often working with large-scale datasets from real-world applications.

• Database
• Data Mining
• Data Science
• +5 more

Tara Boroushaki is an incoming Assistant Professor in Electrical & Computer Engineering at Yale University. She completed her Ph.D. at MIT (expected May 2025), advised by Prof. Fadel Adib, with a focus on sensing and mobile technologies. Her research spans wireless networking, robotics, and human-computer interaction, emphasizing multi-modal sensing for environmental perception. Key achievements include the Microsoft Research PhD Fellowship (2022–2024) and the IEEE RFID '23 Best Paper Award. Her work on RF-based 'X-ray vision' has been featured in TEDxMIT and media outlets like the BBC and World Economic Forum. She co-founded Cartesian Systems, deploying sensing technologies in retail and supply chain. Research interests include non-line-of-sight perception, RFID localization, and robotic grasping. She has developed systems like FuseBot and RFusion, highlighted as transformative in MIT's '103 Ways to Make the World Better' initiative.

• Wireless Networking
• Cyber-Physical Systems
• Robotics
• +3 more

Dr. Yelda Turkan is an Associate Professor in the School of Civil and Construction Engineering at Oregon State University, where she leads research in automation, computer vision, and machine learning for sustainable infrastructure. She holds a PhD from the University of Waterloo and dual BS degrees in Civil Engineering and Geomatics Engineering from Istanbul Technical University. Her work focuses on leveraging lidar, digital twins, and BIM to improve construction operations and decision-making in the built environment. She has secured over $4M in grants from NSF, FHWA, and other agencies, and currently leads the NSF Convergence Accelerator-funded 'Deep Reality' project for AI-driven infrastructure management. Education: Ph.D., Civil Engineering, University of Waterloo, 2012 M.S., Engineering Informatics & Remote Sensing, Istanbul Technical University, 2006 B.S., Civil Engineering (double major in Geomatics Engineering), Istanbul Technical University, 2005/2003 Professional Roles: Vice President, International Association for Automation and Robotics in Construction (IAARC) Chair, ASCE Computing Division Education Committee Associate Editor, ASCE OPEN Journal Her research emphasizes automation in construction quality control, infrastructure inspection via drones and lidar, and immersive education tools using VR/AR. Recent projects include automated curb ramp compliance analysis, wildfire impact modeling, and digital twin development for timber structures. She has published over 80 peer-reviewed articles and actively promotes computing integration in civil engineering education and professional practice.

• Computer Vision
• Machine Learning
• Lidar Applications
• +7 more

Rajesh Krishna BALAN is a Full-Time Professor at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU) . His research focuses on Human-Machine Collaborative Systems , Pervasive Sensing , and Health & Wellbeing technologies. Based in Singapore, he leverages mobile computing to address urban sustainability and quality-of-life challenges. PhD from Carnegie Mellon University (2006) Specializes in WiFi sensing , VR/AR , and health monitoring Advises PhD students in areas like urban mobility , empathetic design , and cyber-physical systems Beyond academia, BALAN's work bridges ubiquitous computing and public health , with applications in ageing populations , mental health analytics , and smart city optimization . His recent publications highlight cross-disciplinary approaches to sleep analysis , group behavior modeling , and contactless physiological sensing . BALAN actively contributes to educational technology through projects like Technology-Enhanced Learning frameworks. He is also a mentor in collaborative research areas including biomedical informatics and lifestyle monitoring , with a focus on mobile GPU optimization and low-power systems .

• Human-Machine Collaborative Systems
• Pervasive Sensing & Systems
• Learning & Work
• +9 more

Dr. Rong-Hao Liang is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with both the Future Everyday Group (Department of Industrial Design) and the Signal Processing Systems Group (Department of Electrical Engineering). His research bridges intelligent sensing systems and user interface technology for ubiquitous computing and embodied human-computer interaction . He co-organized international ACM conferences (CHI, UIST, DIS) and has over 70 peer-reviewed publications and 10 patents. PhD in Computer Science (2014) and MSc in Electrical Engineering (2010) from National Taiwan University Founded GaussToys Inc. in 2015, focusing on magnetic-field sensors Cross-appointed to Electrical Engineering in 2021 His research explores intelligent sensing systems , tangible user interfaces , and physiological sensors for real-world challenges. Key trends in his work include ubiquitous health monitoring (e.g., preterm infants), wearable technology , and innovative interaction design . Articles like GaussBits and NFCStack demonstrate his focus on magnetic and RFID-based tangible systems . Scientific awards include the ACM CHI 2013 Best Paper Award , 2014 Honorable Mentions , and the ACM SIGGRAPH Asia 2012 Emerging Technologies Prize . He mentors passion-driven projects in user interface design and embedded systems , emphasizing technical rigor and creativity. His STRAP project (2020–2025) addresses heart disease prevention via big data and AI . Labs and teams include the Future Everyday Group and Signal Processing Systems Group , with collaborations across healthcare , education , and technology startups . His work aligns with UN Sustainable Development Goals , particularly good health and well-being .

• Human-Computer Interaction
• Tangible User Interfaces
• Intelligent Sensing Systems
• +7 more