Patrick McDaniel is a Professor in the School of Computer, Data & Information Sciences at the University of Wisconsin-Madison. He is a Fellow of IEEE, ACM, and AAAS, and leads the MadS&P (UW-Madison Security and Privacy) group. His research spans computer and network security, adversarial machine learning, and technical public policy. Academic Affiliation : Tsun-Ming Shih Professor of Computer Sciences Key Research Areas : Mobile/IoT security, election systems security, AI policy Research Trends : His recent publications and funded projects focus on adversarial machine learning, SDN security, and robustness of AI systems. Keywords include cybersecurity, machine learning, network security, and privacy. Grants and Leadership : He has secured over $5M in NSF funding for end-to-end trustworthiness of ML systems and leads collaborative projects with Army Research and UW-Madison. Awards : Multiple best/most influential paper awards (ICSE 2015, PLDI 2014, ACSAC 2024, EthiCS 2023) Advising : Mentored 13+ PhD students and postdocs now at top institutions like Google, Purdue, and University of Toronto
Michele Zorzi is a Professor of Telecommunications at the School of Engineering, University of Padova, Italy, where he has held a faculty position since 2003. He leads the SIGNET (Signal processing and Networking) Research Group, focusing on cutting-edge wireless networking challenges including mmWave communications and underwater networks. His extensive publication record exceeds 600 papers in top-tier journals and conferences, reflecting significant contributions to the field through both theoretical and experimental work. He received his Laurea Degree (1990) and Ph.D. (1994) in Electrical Engineering from the University of Padova. Prior academic appointments include Politecnico di Milano (1993-1996), University of California San Diego (1995-1998), and University of Ferrara (1998-2003), where he progressed from Associate Professor to full Professor. His educational trajectory demonstrates deep roots in Italian academia with international exposure. Professor Zorzi's research spans wireless communications and networking, with current emphases on mmWave networking for vehicular systems, underwater acoustic/optical communications, non-terrestrial networks, and AI-driven networking solutions. His group conducts experimental validations including at-sea trials for underwater systems and testbeds for vehicular networks. Key projects include PRATA for predictive QoS in autonomous driving and IoT-based environmental monitoring of the Venice Lagoon, demonstrating practical applications of theoretical work. Analysis of his 2022-2025 publications reveals strong trends in applying artificial intelligence to networking challenges across diverse environments. There is significant emphasis on vehicular networks (predictive QoS, teleoperated driving), underwater systems (acoustic/optical communications, AUV swarms), and satellite networks (Starlink integration, NTN security). Experimental validation in real-world scenarios like the Venice Lagoon monitoring project and underwater sea trials characterizes his applied research approach. His scientific accolades include: IEEE Fellow (2007) IEEE Communications Society Best Tutorial Paper Award (2008, 2019) Stephen O. Rice Best Paper Award (2018) Multiple best paper awards at IEEE conferences (2005-2020) As principal investigator for numerous European and US research projects plus 20+ industry-funded initiatives, Professor Zorzi has mentored over 35 PhD students and post-docs. Graduates now hold prominent positions at institutions including Stanford, UCSD, CTTC, and Huawei. His SIGNET group maintains active international collaborations and contributes to open-source networking tools via GitHub, demonstrating commitment to community engagement. The SIGNET Research Group, housed within the Department of Information Engineering, operates specialized experimental facilities for mmWave and underwater communications. Current initiatives include AI-based predictive QoS frameworks for vehicular networks, underwater optical communication systems using ultraviolet light, and large-scale IoT deployments for environmental monitoring. The group's GitHub presence indicates strong open-science practices, while recent sea trials confirm hands-on experimental capabilities beyond theoretical work.
Ming-Syan Chen is a distinguished academic holding dual roles as a Distinguished Research Fellow and Director of the Research Center for Information Technology Innovation (CITI) at Academia Sinica, Taiwan, and a Distinguished Professor jointly appointed across multiple departments at National Taiwan University (NTU), including Electrical Engineering (EE), Computer Science and Information Engineering (CSIE), and the Graduate Institute of Communication Engineering (GICE). His career spans academia and industry, with prior roles as a research staff member at IBM Watson Research Center and leadership positions in Taiwan's technology sector. Education: He earned a B.S. in Electrical Engineering from National Taiwan University, followed by M.S. and Ph.D. degrees in Computer, Information, and Control Engineering from the University of Michigan, Ann Arbor. Research Interests: Chen's work focuses on databases, data mining, machine learning, multimedia networking, and cloud computing. He has authored over 350 papers and holds numerous patents, contributing to foundational advancements in query processing, data management, and networked systems. Award Highlights: Recipient of ACM and IEEE Fellowships, National Chair Professorship (lifetime honor), Teco Award, Pan Wen Yuan Distinguished Research Award, and IBM's Outstanding Innovation Award. His contributions span research, teaching, and technology commercialization. Leadership & Service: Former Dean of NTU's College of Electrical Engineering and Computer Science, CEO of Taiwan's Networked Communication Program, and Editor-in-Chief of the International Journal of Electrical Engineering. He has chaired international conferences and served on editorial boards of journals like IEEE TKDE and VLDB. Labs & Teams: Leads the Network Database Laboratory and collaborates on national initiatives in information and communication technologies. His research groups focus on data science, distributed systems, and social network analysis.
Aditya K. Jagannatham is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). With expertise in wireless communications and signal processing, he has established himself as a leading researcher in 5G/6G technologies, MIMO systems, and cognitive radio networks. His educational background includes: PhD in Electrical and Computer Engineering from UC San Diego (2007) M.S. in Electrical and Computer Engineering from UC San Diego (2004) B.Tech. in Electrical Engineering from IIT Bombay (2001) Professor Jagannatham's research primarily focuses on next-generation wireless communication systems, with special emphasis on 5G and 6G technologies. His work spans OTFS modulation, Terahertz communications, Visible Light Communication (VLC), Intelligent Reflecting Surface (IRS) technology, Massive MIMO, mmWave MIMO, Non-Orthogonal Multiple Access (NOMA), and Filter-Bank Multi-Carrier (FBMC) systems. His research integrates theoretical analysis with practical implementation challenges, addressing critical issues in modern wireless networks. His recent publications demonstrate a strong trend toward advanced signal processing techniques for next-generation wireless systems, particularly focusing on Sparse Bayesian Learning approaches for channel estimation, cooperative communication systems with energy harvesting capabilities, and millimeter wave MIMO technologies. His work bridges theoretical communication theory with practical implementation challenges in emerging wireless standards. Professor Jagannatham has received numerous prestigious awards and fellowships: Arun Kumar Endowed Chair Professorship (2019) Qualcomm Innovation Fellowship (2018) P.K. Kelkar Young Faculty Research Fellowship for excellence in research (2015-2018) IEEE Signal Processing Society travel grant to attend ICASSP 2015 Gopal Das Bhandari Memorial Distinguished Teacher Award (2012-13) Cal(IT)2 fellowship for graduate study at UC San Diego As an educator, Professor Jagannatham has received commendation letters from the Director of IIT Kanpur for excellence in teaching courses including EE624 Information and Coding Theory, EE670 Wireless Communications, and EE320 Principles of Communication Systems. His research has attracted significant funding, though specific grant details are not provided in the available information. He likely supervises graduate students working on cutting-edge wireless communication research. Professor Jagannatham is based in the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, where he leads research in wireless communications. His work appears to be closely connected with the Center for Developing Intelligent Systems (CDIS) and other research centers at IIT Kanpur focused on next-generation communication technologies.
Anand Bhojan is an Associate Professor (Educator Track) at the Department of Computer Science, School of Computing, National University of Singapore (NUS). He is a member of the Communication and Internet Research Lab and serves on the Graduate Studies Committee. Dr. Bhojan is also the founder of Anuflora Systems and Virtual and Augmented Reality Labs (www.varlabs.org), and serves as Associate Editor of Computers and Electrical Engineering Journal, Elsevier, and Vice President of International Researchers Club, Singapore. Dr. Bhojan earned his Ph.D. in Computer Science & Engineering from NUS in 2011, where his thesis was nominated for the Best PhD Thesis Award. He also holds a Professional Master's in Computer Applications from Bharathidasan University (1999), a Bachelor's degree in Computing with Gold Medal (University topper) from Bharathiar University (1994), and a Postgraduate Certificate in Teaching Higher Education from University of Sheffield, UK (2003). His research spans multiple domains including Distributed Computing and Wireless Networks (IoT, Security, Blockchain), Artificial Intelligence (Generative AI, FinTech), and Entertainment Computing with focus on Games, VR/AR/Metaverse technologies. Dr. Bhojan leads the Metaverse Foundry research group which focuses on content generation for games & XR simulations across multiple domains including entertainment, healthcare, and architecture, while also experimenting with innovative teaching methods for entertainment media technologies. Dr. Bhojan's recent research has pioneered hybrid rendering techniques that strategically combine ray tracing and rasterization to create more realistic video game graphics without compromising performance. His work addresses critical challenges in real-time rendering, particularly in depth of field and motion blur effects, with the goal of making Hollywood-quality graphics accessible on a wider range of hardware. Earlier work focused on energy efficiency in mobile gaming, including power management techniques and latency optimization for cloud gaming. Among his notable achievements: 2012 Nominated for Best PhD Thesis Award (Wang Gungwu Medal & Prize), NUS 2011 Dean's Graduate Research Achievement Award (PhD), SoC, NUS 2006 Best R&D Project award from TOTE Board, Singapore 1995 Gold medal for first Rank (out of 4000) in Computing, Bharathiar University Dr. Bhojan has served as Organizing Chair and Program Chair for multiple international conferences and has delivered keynote talks at IEEE/ACM International Conferences. He teaches courses including Computer Networks Practice, Game Development, Interaction Design for Virtual and Augmented Reality, and Game Development Project. He leads the Metaverse Foundry research group and the Virtual and Augmented Reality Labs, where undergraduate and graduate students have won multiple research and innovation awards. His research bridges entertainment, education, and emerging technologies with practical applications in making immersive experiences more accessible across different hardware capabilities while maintaining energy efficiency.
Jindong Tan is a Professor in the Department of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville (since 2015). Previously, he held roles at Michigan Technological University (2002–2015) and Northeastern University, China (1995–1998). He specializes in medical/surgical robotics, human-robot interactions, wearable sensors, control systems, and mechatronics. His research integrates robotics, biomedical engineering, and computer science to advance minimally invasive surgical tools, wearable technology, and autonomous systems. Education: Ph.D. in Mechanical Engineering from Michigan State University (2002), M.S. from Northeastern University (1995), and B.S. from Lanzhou University of Technology (1992). Research interests focus on developing innovative medical robotic systems, including laparoscopic camera robots, magnetic actuation mechanisms, and human-robot collaboration frameworks. He has contributed to advancements in wearable sensors for healthcare, sensor networks for dynamic environments, and calibration techniques for bio-inspired robots. Key projects include the design of an untethered laparoscopic camera robot (s-CAM), magnetic localization for surgical tools, and frameworks for controlled robot language in human-robot collaboration. His work emphasizes practical applications in surgical environments and wearable health monitoring. Professional service includes roles with the IEEE Robotics & Automation Society, Engineering in Medicine and Biology Society, and the Association for Computing Machinery. Contact: tan@utk.edu, Perkins Hall 315.
Olga Saukh is an Associate Professor at the Institute of Technical Informatics, Graz University of Technology (TU Graz), and a Faculty member at the Complexity Science Hub Vienna (CSH). She leads the Embedded Learning and Sensing Systems research group, which operates across both institutions, focusing on the design and deployment of efficient AI-based systems on edge and mobile platforms. Her work bridges deep learning and embedded systems, with applications in environmental monitoring, precision agriculture, and digital health. Ph.D. in Computer Science, University of Bonn (2009) Habilitation in Embedded Systems, TU Graz (2020) Postdoctoral Training, ETH Zurich (2010–2016) B.Sc. in Applied Mathematics, Taras Shevchenko National University of Kyiv (2002) M.Sc. in Applied Computer Science, University of Freiburg (2004) Her research centers on efficient machine learning, particularly model optimization, neural network pruning, and contrastive learning for resource-constrained devices. She is deeply engaged in solving real-world challenges in IoT, sensor networks, and cyber-physical systems. Her work emphasizes data privacy, sustainability, and practical deployment of AI at the edge. The 15 most recent publications highlight a strong trend in efficient deep learning, including model compression, pruning, and transfer learning, applied to diverse domains such as environmental sensing (air quality, pollution tracking), digital agriculture (cattle farming), and embedded AI (sensor calibration, on-demand sensing). Her work frequently appears in top-tier venues like NeurIPS, ICLR, and IEEE/ACM IPSN, reflecting her leadership at the intersection of machine learning and embedded systems. Scientific awards include: CONET Ph.D. Academic Award (2010) Multiple Best Paper Awards at IEEE PerCom, ACM/IEEE IPSN, IEEE ICPADS, IEEE SECON, and UrbCom Spotlight and Oral presentations at ICML and CoLLAs workshops Ph.D. scholarship from IPVS, University of Stuttgart (2004–2005) Prizes in Ukrainian national mathematics competitions (1996–1998) Olga Saukh actively serves on program committees of leading international conferences in machine learning and embedded systems. She has advised multiple students and leads a collaborative research group spanning TU Graz and CSH Vienna. Her group develops practical AI systems for real-world deployment, with a focus on sustainability and privacy. She co-organizes the public EfficientML reading group and has secured recognition through numerous grants and awards. Her future work continues to explore the theoretical and practical challenges of deploying efficient, trustworthy AI in mobile and embedded environments. Her research group, Embedded Learning and Sensing Systems, operates jointly between TU Graz and CSH Vienna, fostering interdisciplinary collaboration across institutions. The team develops AI solutions for edge computing, sensor networks, and cyber-physical systems, with a strong emphasis on environmental sustainability and data privacy. Members work on joint challenges using advanced collaboration tools, reflecting the distributed nature of modern academic research.
Dr. Nanpeng Yu is a Full Professor at the University of California, Riverside , serving as Vice Chair and Graduate Advisor in the Department of Electrical and Computer Engineering . He maintains cooperative faculty affiliations with the Department of Computer Science and Department of Statistics , and directs the Energy, Economics, and Environment Research Center at UCR. Education : B.S. in Electrical Engineering from Tsinghua University (2006), M.S. in Electrical Engineering and Economics, and Ph.D. from Iowa State University (2010) Prior Industry Experience : Senior Power System Planner and Project Manager at Southern California Edison (2011-2014) Dr. Yu’s research bridges smart grid technologies , data-driven optimization , and machine learning for energy systems. Key areas include voltage control , renewable energy integration , transportation electrification , and grid resilience . His recent work focuses on physics-informed graph learning for unit commitment problems and adversarial purification in power system classifiers. The AI-Energy Nexus Laboratory under Dr. Yu has produced impactful publications in Applied Energy , IEEE Transactions on Power Systems , and Transportation Research series, covering topics like heavy-duty EV charging infrastructure and dynamic distribution network reconfiguration . Lab members have won the American-Made Digitizing Utilities Grand Prize ($300,000) from the U.S. DOE. Leadership Roles : Chair, IEEE Power and Energy Society Distribution System Operation and Planning Subcommittee Chair, IEEE Power and Energy Society Working Group on Data-Driven Modeling for Power Distribution Networks Associate Editor, IEEE Transactions on Smart Grid and IEEE Power Engineering Letters Scientific Awards : Regents Faculty Fellowship Regents Faculty Development Award Multiple IEEE Best Paper Awards
Nirupam Roy is an Assistant Professor at the Department of Computer Science, University of Maryland, College Park, and Director of the iCoSMoS research lab. His work bridges wireless networking, mobile computing, and acoustic sensing with applications in IoT, localization, healthcare, security, and wearables. Research Focus: Wireless Networking & Mobile Sensing Awards: Best paper award, MobiSys 2022 Best demo award, MobiSys 2021 CSL Ph.D. Thesis Award, UIUC 2019 Students: Nakul Garg, Yang Bai, Irtaza Shahid, Harshvardhan Takawale, Aritrik Ghosh, Ayushi Mishra, Sumbul Zehra, Justin Goodman Grants: NSF CAREER award (2023), Meta Research Award (2023)
Antony Franklin is an Associate Professor and Head of the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IITH), India. He leads the Networked Wireless Systems (NeWS) Lab and is actively involved in 5G research, wireless networks, and cybersecurity. He earned his Ph.D. from IIT Madras in 2010. Education: Ph.D. in Computer Science and Engineering, IIT Madras, 2010 Research Interests: His research spans wireless networks , 5G systems , mobile edge computing , low-latency transport protocols , and cybersecurity . He focuses on next-generation mobile systems, especially 5G, aiming to meet the demands of ultra-low latency, high data rates, and quality of experience for services like IoT, autonomous driving, and VR. He has been involved in developing testbeds and prototypes to validate real-world performance of 5G technologies, including network slicing, LTE-WiFi integration, and edge computing. Scientific Awards: Best Academic Demo Award, IEEE COMSNETS 2018 Second Best Paper Award, IEEE ANTS 2017 Grants & Projects: Network Slice Life-cycle Management for 5G Mobile Networks – SPARC, MHRD (2019–2021) DNS/IPv6 for IoT Security – NASSCOM (2018–2019) CCRAN: Energy Efficiency in Cloud RAN – Intel India (2018–2021) End-to-End 5G Test-Bed – DoT, GoI (2018–2021) M2SMART Smart Cities – SATREPS (2018–2023) Ultra-Reliable Low Latency Protocols – STINT, Sweden (2017–2018) Low Latency 5G Protocols – SERB ECR (2016–2019) Lab & Team: He leads the NeWS Lab (Networked Wireless Systems) at IITH, which focuses on 5G, wireless networks, and IoT systems. The lab is actively involved in developing real-world testbeds and publishing in top-tier conferences and journals.
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.
Hossam Hassanein is a Professor and Director of the School of Computing at Queen's University. He received his B.Sc. in Electrical Engineering from Kuwait University in 1984, M.Sc. in Computer Engineering from the University of Toronto in 1986, and Ph.D. in Computing Science from the University of Alberta in 1990. He joined Queen's University School of Computing in 1999 and has established himself as a leading researcher in telecommunications and networking. Dr. Hassanein's research interests span wireless sensor networks, mobile ad hoc networks, edge computing, Internet of Things (IoT), radio resource management, and data-centric networks. His seminal contributions include pioneering work on WSN planning, load-balanced routing protocols, and energy-efficient network designs. He has championed research in IoT, developing frameworks for smart spaces that use contextual information to enhance IoT applications in healthcare, transportation, and infrastructure. His recent publications (2023-2025) demonstrate a strong focus on cutting-edge areas including extreme edge computing, vehicular networks, and AI/ML integration in networking. Research trends show increasing emphasis on practical applications in telesurgery, digital twins, and industrial IoT, addressing challenges in resource allocation, task offloading, and real-time processing in constrained environments. Dr. Hassanein has received numerous recognitions for his work: Fellow of the IEEE Queen's University School of Graduate Studies Award for Excellence in Graduate Student Supervision (2015) Multiple best paper awards from top international conferences As founder and director of the Telecommunications Research Lab (TRL), Dr. Hassanein has supervised over 75 students who have made substantial contributions in academia and industry. The TRL is one of Queen's largest research groups with extensive international collaborations. Dr. Hassanein has successfully attracted significant research funding from government and industry sources in the competitive telecommunications field. The Telecommunications Research Lab has developed innovative platforms including SPROUTS, a rugged sensor platform used in mining, steel manufacturing, and smart-grid monitoring. TRL's work has had significant impact in WSN planning, data dissemination, and resource reuse in wireless networks, with contributions featured in IEEE Wireless Communications Magazine.
Prof Christina Lim is a Professor at the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. She serves as the Associate Dean of Research for the Faculty of Engineering and Information Technology (FEIT) and manages the Tucker Lab. Previously, she held roles as Research Group Leader of the Electronics and Photonics System group and Deputy Head of Department (Teaching and Operations) Education: PhD and Bachelors from University of Melbourne Research Interests: Radio-over-Fibre, Optical Wireless Communications, Microwave Photonics, Augmented Reality Displays, Reservoir Computing, Optical Crosshaul Networks Recent publications demonstrate expertise in optical waveguide design for AR, underwater optical wireless communications, photonic switching, and network optimization. Her projects focus on next-generation wireless infrastructure, including Photonics Computing Enabled Ultra-Broadband Wireless Communications (2024-2027, $598k ARC grant) and Additive Manufacturing of Optical Elements (2025). She has secured significant funding, including ARC Discovery Projects and Future Fellowships. Scientific Honors IEEE Fellow (2022) Optica Fellow (2018) ARC Future Fellow (2009-2013) ARC Australian Research Fellow (2004-2008) Professional Service Vice-President of Conferences, IEEE Photonics Society Deputy Editor, IEEE/Optica Journal of Lightwave Technology ARC College of Experts (2014-2016)
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)
Charles F. Harvey is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he investigates hydrology, carbon cycling, and groundwater contamination. His work spans tropical peatlands, arsenic pollution in South Asia, and coastal groundwater dynamics, with field sites in Borneo, Bangladesh, and Vietnam. Education: B.A. in Mathematics (Oberlin College, 1986), M.S. in Applied Earth Science (Stanford University, 1992), Ph.D. in Geological and Environmental Sciences (Stanford University, 1996). Harvey’s research focuses on hydrogeology , carbon sequestration , and contaminant transport . He explores how groundwater flow and biogeochemical processes interact in tropical peatlands and coastal systems, with significant implications for climate change and water security. His recent publications emphasize tropical peatland hydrology , arsenic mobilization , and coastal groundwater exchange , integrating field experiments, remote sensing, and computational models. Scientific Awards AGU Fellow GSA Fellow Meinzer Award (GSA) Prince Sultan bin Abdulaziz International Prize for Water M. King Hubbert Award for Hydrology NSF Young Investigator Award Harvey leads the Harvey Lab , mentoring students and researchers in projects ranging from groundwater arsenic mitigation to coastal marsh biogeochemistry . His work bridges terrestrial and marine systems , addressing critical planetary challenges.
