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Dr. Amin Keramati is an Assistant Professor of Supply Chain Management at Widener University’s School of Business Administration. He holds a PhD in Transportation & Logistics from North Dakota State University and previously served as a graduate research assistant at the Upper Great Plains Transportation Institute. His work includes federally funded projects like the Mountain-Plains Consortium’s MPC-550 project, focusing on highway-rail grade crossing safety. Dr. Keramati teaches courses in enterprise resource planning, decision analytics, database management, transportation/logistics, project management, and data analytics. Education: PhD in Transportation & Logistics, North Dakota State University Graduate Research Assistant at Upper Great Plains Transportation Institute Research Focus: Dr. Keramati develops mathematical, statistical, and machine learning approaches to solve complex problems in transportation, supply chain, and logistics. Key areas include data mining, big data decision support, transportation network analytics, project scheduling, smart manufacturing, and accident analysis. His interdisciplinary work bridges supply chain optimization with emerging technologies like blockchain for healthcare and clinical trials. Awards & Recognition: Student Paper Award, American Association of State Highway and Transportation Officials (2017) Grants & Projects: Lead researcher on the Mountain-Plains Consortium’s MPC-550 project, which expanded his dissertation work on safety systems for highway-rail crossings. Collaborates on federally funded transportation safety initiatives and supply chain optimization for bioethanol and pharmaceutical industries. Labs/Teams: Active in Widener’s School of Business research groups focusing on supply chain innovation and interdisciplinary projects combining logistics with emerging technologies.

• Transportation & Logistics
• Supply Chain Management
• Data Analytics
• +4 more

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

Fadel Adib is an Associate Professor with Tenure at MIT, holding a joint appointment in the MIT Media Lab and the Department of Electrical Engineering and Computer Science (EECS). He leads the Signal Kinetics research group at the Media Lab and is the founder and CEO of Cartesian Systems. His work focuses on novel wireless technologies for sensing and connectivity in challenging environments, including underwater communication, health monitoring, and robotics. Education: B.Sc. from American University of Beirut (2011), M.Sc. and Ph.D. in Computer Science from MIT (2013 and 2016), where he won best thesis awards. His research has led to startups such as Cartesian Systems and Emerald Innovations, addressing applications in climate monitoring, healthcare, and logistics. Research Interests: Underwater backscatter networking, batteryless systems, non-line-of-sight perception, RFID localization, and wireless health monitoring. His innovations include the first battery-free underwater camera and systems for contactless vital signs monitoring. Awards: Sloan Research Fellowship (2021), NSF CAREER Award (2019), ACM SIGMOBILE Rockstar Award (2022), and Technology Review 35 Under 35 (2014). Grants: ONR Young Investigator Award, Google Faculty Research Award. Teams: Signal Kinetics research group at MIT Media Lab. Labs and Projects: Focus on cross-disciplinary initiatives such as wireless mapping (Cartesian Systems), underwater-to-air communication, and implantable medical devices.

• Wireless Technologies
• Underwater Communication
• Health Monitoring
• +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

Alanson Sample is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan (since 2018), leading the Interactive Sensing and Computing Lab. His research focuses on Human-Computer Interaction, Cyber-Physical Systems, and wireless technology innovations. He holds a PhD in Electrical Engineering from the University of Washington (2011), with prior postdoctoral work there developing implantable medical devices. Before academia, Sample held senior roles at Disney Research (2013-2018) as Executive Lab Director and Principal Research Scientist, leading teams in Robotics, AI, Computer Vision, and HCI. Earlier, he worked at Intel Labs (2008-2013) on energy harvesting for wearables and IoT. Key research themes include wireless power systems, embedded sensing, and privacy-aware technologies. Over 150+ publications span topics like magnetic sensing (MagDesk), acoustic gesture recognition (HandSAW), and privacy-preserving activity tracking (PrivacyMic). His work bridges academic and industry innovation, particularly in scalable interactive systems and medical technology. Notable projects include the Quasistatic Cavity Resonance wireless charging system, RFID-based sensing platforms (WISP), and wearable health monitoring devices. His lab develops hardware-software co-design frameworks for energy-efficient embedded systems. Current research emphasizes medical applications, smart infrastructure, and ubiquitous computing interfaces.

• Human Computer Interaction
• Cyber-Physical Systems
• Wireless Technology
• +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

Aline Eid is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Michigan Ann Arbor, directing the Beam Dynamics research group. Her work bridges electromagnetics, wireless systems, and autonomous technologies, with a focus on mmWave/sub-THz sensing, backscatter communications, and wireless power transfer. PhD in Electrical and Computer Engineering (Georgia Tech, 2021) MS in Electrical and Computer Engineering (American University of Beirut, 2017) Postdoctoral Associate at MIT Media Lab (Signal Kinetics group) Research Interests: She pioneers systems that use electromagnetic waves to address societal challenges in Sustainable energy networks Smart cities/infrastructures Autonomous vehicles/robots Her group develops mmID tags for radar vision, batteryless sensors, and 5G-based wireless power grids. Scientific Impact: Recognized with awards including IEEE RFID Best Paper (2023) Proceedings of the IEEE Best Paper (2023) IEEE MTT-S Graduate Fellowship (2020) She leads commercialization efforts for warehouse robotics via MTRAC grant and startup Atheraxon. Advising: Mentors 8 students across PhD (Skanda Harisha, Sepideh Ghasemi, Yunfei Liu), Master's (Longyu Guo), and undergraduates (Mohamed Safawi, Katherine Shih, Andy Wang, Adrian Velazquez) in projects spanning robotics, IoT, and electromagnetic engineering. Labs: Beam Dynamics group at U-M Radiation Laboratory, collaborating with Atheraxon and MTRAC for technology translation.

• Applied Electromagnetics
• RF Circuits
• Wireless Sensing
• +6 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

Zerina Kapetanovic is an Assistant Professor in the Department of Electrical Engineering at Stanford University, with courtesy appointments in Computer Science and Geophysics. She leads the S4 Lab, focusing on low-power wireless systems, IoT, and environmental/healthcare applications. Her work includes innovations in passive communication, energy-efficient sensing, and satellite connectivity. Education: PhD in Electrical Engineering (University of Washington, 2022) Postdoctoral Research: Microsoft Research (Networking and Research for Industry Groups) Research interests span wireless communication, IoT systems, and energy-efficient hardware. Notable projects include Johnson noise thermometry, satellite backscatter (SARLink), and carrier-free RFID communication. Awards include the Terman Faculty Fellowship and Yang Research Award. Advises doctoral students in IoT and wireless systems. Teaches courses on wireless sensing, engineering investigation, and special studies in EE. Active in grants and collaborations, including the Wu Tsai Human Performance Alliance. Labs/Teams: S4 Lab (Smart Sensing Systems) and involvement in FarmBeats IoT agriculture platform.

• Low-power wireless communication
• Sensing systems
• Internet of Things (IoT)
• +3 more

Douglas H. Werner is the John L. and Genevieve H. McCain Chair Professor in the Department of Electrical Engineering at Pennsylvania State University's College of Engineering. He directs the Computational Electromagnetics and Antennas Research Lab (CEARL) and holds a faculty position at the Materials Research Institute (MRI). His education includes B.S., M.S., and Ph.D. degrees in Electrical Engineering, along with an M.A. in Mathematics, all from Pennsylvania State University. Werner's research encompasses computational electromagnetics, antenna systems, metamaterials, and AI-driven electromagnetic design. Current work focuses on developing deep learning techniques for rapid simulation and inverse-design in electromagnetics/optics. Key areas include: Advanced computational methods (FDTD, FEM, MoM) Next-generation antenna systems (wearable, reconfigurable, RFID) Metamaterial physics and transformation optics Evolutionary optimization algorithms Awards and honors include: IEEE Antennas and Propagation Society Educator Award (2019) DoD Technical Achievement Award (2018) R.W.P. King Paper Award (2006) Fellowships in 5 professional societies 14 additional research/teaching awards He leads CEARL research group, holds 20 patents, and has supervised numerous graduate students. His publication record includes 900+ papers and 6 books.

• Computational Electromagnetics
• Antenna Theory and Design
• Metamaterials
• +7 more

Sauvik Das is an Associate Professor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII), directing the SPUD Lab. His research focuses on the intersection of HCI, AI, and cybersecurity, emphasizing user agency over personal data online. He previously held roles at Georgia Tech and co-founded FuguUX, an early-stage startup improving web usability. Key research areas include socially-aware cybersecurity, privacy collective action, and physically-intuitive privacy interfaces. Notable contributions include work on seed phrase management for cryptocurrency users, anti-surveillance RFID systems, and tools like Purpose Mode to combat social media distractions. His work has received accolades such as a CHI Best Paper (2024) and a USENIX Security Distinguished Paper (2024). He has secured grants from NSF, CMU, and industry partners, and his research is covered in outlets like The Atlantic and Dark Reading. Current projects include designing subversive AI systems against surveillance, exploring ethical agent simulations, and advancing privacy governance through collective action frameworks.

• Usable Privacy and Security
• Human-Computer Interaction
• Human-Centered AI
• +3 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

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

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