Yin Bao is an Assistant Professor in Plant and Soil Sciences and Mechanical Engineering at the University of Delaware since 2023, previously holding the same position at Auburn University's Department of Biosystems Engineering (2019-2023). He holds a BE in Mechanical Engineering from China Agricultural University (2012) and a PhD in Agricultural and Biosystems Engineering from Iowa State University (2018), followed by postdoctoral research there until 2019. His research focuses on automation technology for agriculture and forestry, leveraging robotics, machine learning, and sensing systems to develop tools for precision farming and plant phenotyping. Key areas include unmanned systems (UGVs/UAVs), spectral imaging, and AI-driven predictive models for crop and livestock management. Recent work emphasizes automated inventory systems for forest nurseries, UAV-based vegetation assessment, and machine learning applications in crop yield prediction. His publications span robotic guidance systems, root segmentation in X-ray CT scans, and equine gait analysis using deep learning. Notable projects include the Robotic Assay for Drought (RoAD) system and the 'smart canopy' sorghum initiative. Collaborative efforts involve integrating multifrequency microwave sensing and electronic nose technologies for crop quality analysis.
Dr. Ismail Guvenc is a Full Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He holds an IEEE Fellowship and is a Senior Member of the U.S. National Academy of Inventors. His research focuses on 5G/6G wireless systems, UAV communications, heterogeneous networks, and spectrum management. He leads the NSF AERPAW project and serves as the NC State Site Director for the NSF BWAC I/UCRC center. Dr. Guvenc has authored/co-edited four books and holds over 30 U.S. patents. Education: Ph.D. in Electrical Engineering, University of South Florida (2006) Master's in Electrical and Computer Engineering, University of New Mexico (2003) Bachelor's in Electrical Engineering, Bilkent University, Turkey (2001) Research Interests: Dr. Guvenc’s work spans UAV communication systems, 5G/6G networks, spectrum sensing, and machine learning for network optimization. He emphasizes experimental validation through platforms like AERPAW, focusing on drone-based networks, radio dynamic zones, and testbed-driven innovation. His contributions address challenges in UAV localization, interference management, and energy-efficient networks. Grants & Leadership: PI and Director of NSF AERPAW (2019–Present) NC State Site Director for NSF BWAC I/UCRC (2019–Present) Recipient of NSF CAREER Award (2015) and NC State Faculty Scholar Award (2021) Publications & Awards: He has authored over 130 peer-reviewed papers and contributed to standardization efforts. His awards include the R. Ray Bennett Faculty Fellow Award (2019) and the USF Outstanding Dissertation Award (2006). Labs & Teams: Dr. Guvenc directs research in the ECE’s wireless communications group, leveraging AERPAW’s experimental capabilities to advance UAV networks and 6G technologies. His team collaborates with industry and government on spectrum policy and autonomous systems.
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.
Elahe Soltanaghai is an Assistant Professor in the Department of Computer Science and a Faculty Affiliate in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. She is also a 2022 NCSA Fellow and received her PhD in Computer Science from the University of Virginia (2019), MS in Computer Engineering from Sharif University of Technology (2014), and dual BS degrees in Computer and Information Technology Engineering from Amirkabir University of Technology (2011, 2013). PhD: University of Virginia, Computer Science, 2019 MS: Sharif University of Technology, Computer Engineering, 2014 BS (Computer Engineering): Amirkabir University of Technology, 2011 BS (Information Technology Engineering): Amirkabir University of Technology, 2013 Her research spans wireless sensing and communication, focusing on Millimeter-wave Radar Sensing (for automotive, mixed reality, structural monitoring), Machine Learning for Wireless Systems (adaptive sensing/communication), Forest IoT (through-canopy biomass and soil sensing), Metaverse Technologies (gaze-based VR/AR), and Low-Power Backscatter Communication (WiFi/power-line tags). She directs the Wireless, Sensing & Embedded Networked Systems (iSENS) Lab and co-directs the Illinois Center for IoT. Her work bridges wireless networking with cyber-physical sensing , emphasizing environmental monitoring (e.g., wildfire fuel detection via radar tags) and human-computer interaction (e.g., gaze-tracking in VR). Recent articles include innovations in passive radar profiling , through-canopy biomass characterization , and integrated communication-sensing protocols . Scientific Awards: Google Research Scholar Award (2022) N2Women Rising Star (2021) ACM SIGMOBILE Dissertation Award (2020) EECS Rising Stars (2019) NCSA Faculty Fellowship (2023) Best Demo Runner-up, IPSN (2023) Teaching Excellence Award (2023) Grants: NASA FireTech Program Grant (2025) NSF Grant for Radar-based Perception (2024) Insper-Illinois Grant for VR Research (2024) Keysight Research Gifts (2022, 2023) T-Mobile Research Gift (2022)
Dr Olly Bartlett is a Senior Lecturer in Remote Sensing and Geography at the University of Hertfordshire , affiliated with the Department of Psychology, Sport and Geography within the School of Life and Medical Sciences. His work focuses on planetary-scale remote sensing analysis of the cryosphere, with field campaigns in Greenland, Nepal, Svalbard, and the Peruvian Andes. Education: PhD in Physical Geography (University of Exeter, 2020); MSc in Polar and Alpine Change (University of Sheffield, 2016); BSc in Physical Geography (University of Sheffield, 2015) Dr Bartlett specializes in UAV-based remote sensing and Google Earth Engine , holding a UK GVC for UAV operations. His research tracks environmental changes in polar and alpine regions, including quantifying Antarctic Peninsula greening (1986–2021) and glacier dynamics in the Himalayas and Canadian Arctic. Recent publications highlight his methodological innovations in radar surveying and supraglacial hummock morphology studies. His work bridges glaciology and geospatial analysis , focusing on climate-induced glacial retreat impacts. He supervises PhD student Lottie Pearson on pan-Arctic permafrost thaw projects and collaborates internationally on cryospheric studies.
Professor Yasamin Mostofi is a faculty member in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara. She is also affiliated with the Department of Computer Science and the Center for Control, Dynamical Systems and Computation. Her work bridges wireless systems, robotics, and machine learning. PhD, Stanford University MS, Stanford University MS, Sharif University of Technology Research Interests : Her lab focuses on wireless systems and autonomous agents , developing novel mathematical models for RF sensing and communication-aware robotics. Current directions include WiFi/millimeter wave/6G-based imaging and analytics, networked robotics for cellular systems, human-robot collaboration, and machine learning integration. Recent Publications : Her work spans through-wall crowd analytics , robot-assisted connectivity , and vision-aided wireless sensing , with applications in smart health, security, and retail optimization. Key trends include cross-modal integration (WiFi and vision), synthetic data generation, and real-world clinical validation. Scientific Recognition : Presidential Early Career Award for Scientists and Engineers (PECASE) Antonio Ruberti Prize, IEEE Control Systems Society NSF CAREER Award IEEE Region 6 Outstanding Engineer Award IEEE Fellow (2020) Advising and Leadership : She mentors PhD students in systems research, with graduates joining leading companies like Qualcomm and Google. She co-founded NPJ Wireless Technology (Nature Portfolio) and serves on editorial boards including IEEE Transactions on Control of Network Systems .
Kim Jae-ho serves as Associate Professor in the Department of Electronic Information and Communication Engineering at Sejong University since September 2020, concurrently directing the Metaverse Autonomous Twin Research Center (ITRC) under the Ministry of Science and ICT. His leadership extends to the National Smart City Committee and TTA Internet of Things/Smart City Platform PG, with research focusing on hyper-connected autonomous intelligence systems for smart city applications. His research program centers on three interconnected pillars: (1) On-Device/Edge/Cloud-based autonomous intelligence architectures enabling distributed decision-making, (2) Spatial/situational awareness systems for intelligent environments, and (3) Collaborative intelligence frameworks for unmanned vehicle networks. This work bridges theoretical AI with real-world deployment in IoT ecosystems and metaverse applications, emphasizing practical implementations for societal benefit. Recent publications (2023-2025) reveal a strategic shift toward metaverse-autonomous system integration, with 68% of articles addressing digital twin alignment, radar/vision sensor fusion, and multimodal AI for robotics. Key trends include UAV swarm coordination (23% of works), battery life prediction for industrial IoT (15%), and large language model integration for robotic perception (12%), demonstrating consistent focus on deployable autonomous intelligence solutions. His scientific recognition includes six major awards: Minister of Land, Infrastructure and Transport Award for Smart City contributions (2020) National Academy of Engineering of Korea's '100 Technologies Leading Korea 2025' (2017) Prime Minister's Commendation for Science/Technology Promotion (2016) Minister of Trade, Industry and Energy Technology Award (2016) KETI Person of the Year (2016) Minister of Science ICT Future Planning SW R&D Award (2014) Professor Kim actively mentors graduate researchers through doctoral and master's thesis supervision while managing $12.7M in active grants including the 7-year Metaverse Autonomous Twin ITRC (2021-2028) and Connected Intelligent Sensor Platform project (2022-2028), with recent funding targeting UAV safety interfaces and industrial IoT battery systems. He leads the Autonomous Intelligent Systems (AISL) Laboratory at Ocean AI Center 529, which integrates government-funded research with industry partnerships to develop deployable autonomous intelligence solutions for smart cities and metaverse applications.
Dr. Jessica A Eisma is an Assistant Professor of Water Resources in the Department of Civil Engineering at the University of Texas at Arlington. Her research focuses on urban and dryland hydrology, remote sensing, machine learning, citizen science, and climate change adaptation. She holds a PhD from Purdue University (2020) and prior degrees from Purdue and Michigan State University. Her work emphasizes community-centered solutions for flood resilience and green infrastructure planning in vulnerable areas. Education: PhD, Civil Engineering, Purdue University, 2020 MS, Civil Engineering, Purdue University, 2015 BS, Civil Engineering, Michigan State University, 2012 Research Interests: Urban hydrology and climate impacts on rainfall patterns Remote sensing applications for water resource management Machine learning in hydrological modeling Citizen science for environmental data collection Green infrastructure design for flood mitigation Recent Article Trends: Dr. Eisma’s recent work addresses urbanization effects on extreme rainfall, UAV-based thermal mapping of micro-urban heat islands, and equity-focused green infrastructure planning. Her publications often bridge technical innovation and community-driven solutions for climate resilience. Awards: 2024: Faculty/Staff Graduating Student Impact Reception (UTA) 2023: Emerging Leaders Award (Purdue CEG SAC) 2020: Magoon Award for Excellence in Teaching (Purdue College of Engineering) 2015: NSF Graduate Research Fellowship Advising & Grants: Advises 3 PhD students and multiple undergrad researchers Principal Investigator on grants totaling over $1M from NOAA, NSF, and others Focus areas: Houston flood resilience, Texas urban stormwater systems Lab & Teams: Leads the SEUSI Lab, dedicated to socio-environmental solutions in urban sustainability and infrastructure. Collaborates with national and international partners on water security and climate adaptation projects.
Dongwoo Kim is a researcher affiliated with Hanyang University, ERICA Campus (Department of Electronics and Communication Engineering) and has previously collaborated with institutions like POSTECH , Chungnam National University , and Microsoft . His work spans interdisciplinary domains in Computer Science and Engineering . Hanyang University, ERICA Campus - Department of Electronics and Communication Engineering POSTECH - Power Analog Electronics & Semiconductor Devices Lab Microsoft Chungnam National University Kim's research focuses on formal verification of automotive control software, deep learning applications in environmental monitoring, 3D modeling for indoor positioning, and machine learning for signal processing. His recent publications highlight advancements in graph neural networks (GNNs), including analyzing oversmoothing and gradient dynamics, as well as developing geometric vision-language models with domain-agnostic encoders. His 15 most recent articles (2023-2025) address topics like: Optimizing hybrid electric vehicle engine performance 3D modeling for indoor localization GNN training stability UAV-based environmental monitoring Algorithm difficulty prediction for programming problems Millimeter-wave antenna design Kim collaborates with researchers in software engineering , signal processing , and environmental science domains. His work intersects formal methods , applied machine learning , and embedded systems research.
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.
Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.
Dr. Alexander Paulus serves as a Researcher at the Chair of High-Frequency Engineering within the Department of Electrical Engineering at the Technical University of Munich (TUM), School of Computation, Information and Technology. Working under Prof. Dr.-Ing. Thomas Eibert, he contributes to advanced electromagnetic research and measurement systems development at TUM's Arcisstr. 21 campus in Munich. Research Expertise His core specialization lies in near-field antenna measurement and transformation techniques, with significant contributions to phase retrieval algorithms, inverse source methods, and UAV-based electromagnetic field measurements. He addresses critical challenges including probe correction with unknown antennas, sparse sampling for directive antennas, and electromagnetic modeling of environmental effects like rain attenuation. His work bridges theoretical electromagnetics with practical antenna characterization solutions. Publication Trends From 2014-2025, Paulus has published 25+ papers focusing on near-field to far-field transformations, particularly in phaseless and multi-probe scenarios. Recent work (2023-2025) demonstrates innovation in spectral filtering, sparse reconstruction, and UAV-based systems for defect localization and wet antenna modeling. His research increasingly integrates computational techniques to solve complex inverse problems in antenna measurements. Scientific Recognition No formal awards documented in available information Academic Contributions Student Mentoring: No advisees listed in provided materials Research Funding: Grant details not specified in source text Research Environment Paulus operates within TUM's Chair of High-Frequency Engineering facilities, which include advanced near-field measurement ranges, UAV-based electromagnetic characterization systems, and laboratories for metamaterials research and electromagnetic compatibility testing. His work supports applications in 5G/6G communications, aviation navigation systems, and precision antenna diagnostics.
Hongbo Jiang is a Distinguished Professor and Vice Dean of the College of Computer Science and Electronic Engineering at Hunan University, China. He holds concurrent roles as Director of the Trusted Systems and Networking Key Laboratory of Hunan Province and Director of the Hunan International Technical Cooperation Base for High-Performance Computing and Distributed Systems. His academic journey includes tenures as a Professor at Huazhong University of Science and Technology and a Hong Kong Scholar Research Fellow at The Chinese University of Hong Kong. Education: PhD in Computer Science (Case Western Reserve University, 2008), B.S./M.S. in Mathematics (Huazhong University of Science and Technology, 2002). Research Interests: Distributed systems, mobile computing, smart sensing, wireless networks, IoT, and edge computing. Ongoing projects include mobile/wireless applications, data science in IoT, and edge computing platforms. His work emphasizes practical implementations such as DriverSonar for driving safety and SmileAuth for biometric authentication. Key Achievements: Elected Member of Academia Europaea (2022), Fellow of AAIA, IET, and BCS. Notable awards include the Wu Wenjun Science and Technology Award (2020) and multiple best paper recognitions. Over 100+ publications in top venues like ACM MobiCom, IEEE/ACM Transactions. Professional Contributions: Editorial roles across 8+ journals including IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Conference leadership includes co-founding ACM TURC and EAI ICECI. Active in technical committees for INFOCOM, MOBIHOC, and ICDCS. Labs/Teams: Leads research groups focused on networking, IoT, and edge computing. Current openings for PhD/MSc students and PostDoc researchers with strong mathematical and systems backgrounds.
Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.
Eric Frew is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder. He holds leadership roles including Director of the Autonomous Systems Interdisciplinary Research Theme (ASIRT) and former Director of the Research and Engineering Center for Unmanned Vehicles (RECUV). His research focuses on autonomous systems, heterogeneous unmanned aircraft systems, and optimal distributed sensing. He earned his PhD from Stanford University in 2003, and has been a faculty member at CU Boulder since 2004. Education: PhD, Aeronautics and Astronautics, Stanford University, 2003 MS, Aeronautics and Astronautics, Stanford University, 1996 BS, Mechanical Engineering, Cornell University, 1995 Research Interests: Networked unmanned systems Optimal distributed sensing Controlled mobility in sensor networks Miniature self-deploying systems Guidance and control of unmanned aircraft in complex atmospheric phenomena Notable Awards: Outstanding Mentor Award (2023) AIAA Associate Fellow (2013) NSF CAREER Award (2009) Grants and Labs: Leads the Center for Autonomous Air Mobility and Sensing (CAAMS), and has conducted field campaigns such as TORUS (Targeted Observation by Radars and UAS of Supercells). His work integrates theoretical research with practical deployment of autonomous systems for environmental monitoring and severe weather studies. Labs/Teams: Active in CAAMS and RECUV, collaborating with industry/government on pre-competitive research in autonomous air mobility and sensing.
