Riccardo Renzulli is a Researcher at the Department of Computer Science, University of Turin, focusing on object-centric representation learning, medical image analysis, and AI-based computer vision applications. His research emphasizes capsule networks, deep learning models for hierarchical relationships, and applications in healthcare and aerial/satellite imagery. Education: MSc and BSc in Computer Science from University of Turin (2018 and 2015). Previous research with Prof. Valentina Gliozzi explored description logics and non-monotonic reasoning. Professional experience includes a 2022 post at Aalto University (supervised by Prof. Ville Kyrki and Francesco Verdoja) and roles at Addfor and Machine Learning Reply as a deep learning scientist. Research interests span concept learning, few-shot learning, interpretability, and medical imaging. Notable work includes visual localization systems for UAVs, AI-assisted diagnosis for COVID-19 via CXR analysis, and lung nodule segmentation using DeepHealth Toolkit. He contributed to the UniToChest dataset for cancerous nodule detection. His recent publications (2022-2025) address efficient neural architectures, medical imaging applications, and 3D scene modeling. Collaborations include EIDOSLAB, with research emphasizing scalable compression, entropy-based pruning, and ensemble methods for neural networks.
Dr. Kemal Akkaya is a Professor at the Department of Electrical & Computer Engineering, Florida International University (FIU), where he leads the Advanced Wireless and Security Lab (ADWISE). He holds a Ph.D. in Computer Science from the University of Maryland Baltimore County and has expertise in Network Security, IoT/CPS Security, Blockchain Applications, and 5G Security. His professional roles include serving as Research Director for FIU’s Emerging Preeminent Program in Cybersecurity and as Program Director for the first BS degree in IoT in the U.S. Education: Ph.D. in Computer Science, University of Maryland Baltimore County M.S. in Computer Engineering, Middle-East Technical University, Turkey B.S. in Computer Science, Bilkent University, Turkey Research Interests: Dr. Akkaya focuses on securing IoT and cyber-physical systems, blockchain for micro-payments, and network defense mechanisms. His work emphasizes privacy-aware protocols, secure key management, and SDN/NFV-based solutions. Awards: FIU Faculty Senate Excellence in Research Award (2020) College of Engineering and Computing Faculty Research Award (2020) Top Cited Article Award from Elsevier (2010) Advisees and Grants: While no student names are listed, his lab (ADWISE) likely supports graduate research in IoT and cybersecurity. His grants include interdisciplinary initiatives at FIU, focusing on securing emerging technologies like 5G and blockchain. Labs/Teams: Leads the ADWISE Lab, collaborating on projects like secure IoT payment systems, drone communication security, and resilient smart grid networks.
Esen Yel is an Assistant Professor in the Electrical, Computer, and Systems Engineering (ECSE) department at Rensselaer Polytechnic Institute (RPI) since January 2024. She leads the Reliable Intelligent Systems Lab (RISL), focusing on enhancing safety in autonomous systems through planning, uncertainty-aware decision-making, and runtime monitoring. Her work integrates reachability analysis, machine learning, and adaptive control to ensure safe operations in unpredictable environments. Educational background: Ph.D. in Systems Engineering, University of Virginia (2021) M.S. and B.S. in Electrical and Electronics Engineering, Bogazici University, Turkey (2016 and 2014) Postdoctoral Scholar in Aeronautics and Astronautics at Stanford University (2021–2023), contributing to the Stanford Intelligent Systems Lab (SISL) and Stanford Center for AI Safety Research interests emphasize safety-critical autonomous systems , including: Uncertainty-aware planning and decision-making Runtime monitoring and recovery mechanisms Machine learning for adaptive control Formal verification of neural networks Robotics and UAV operations under degraded conditions Her publications (2017–2024) explore themes like spatiotemporal prediction, reachability analysis, meta-learning for UAVs, and safety validation in perception systems. She directs the RISL lab, advancing interdisciplinary research in reliable AI and robotics.
C. Kyle Renshaw is a Professor of Optics and Photonics at the University of Central Florida (UCF), affiliated with the Department of Electrical Engineering (ECE) within the College of Engineering and Computer Science (CECS). He holds a PhD and MS from the University of Michigan and an undergraduate degree from Cornell University. His research focuses on organic optoelectronics, thin-film semiconductors, sensor arrays, photovoltaics, and imaging systems, particularly in applications like flexible electronics and optoelectronic devices. Dr. Renshaw leads the Thin-Film Optoelectronics (TFO) Group, which develops materials and fabrication techniques for large-area devices such as solar cells, displays, and sensors. His work spans hybrid metasurface-refractive optics, drone-based imaging systems, and multispectral imaging technologies. Notable contributions include advancements in infrared imaging, free-space optical communications, and sensor optimization for geolocation. His recent research highlights include experimental comparisons of active imaging modes, Gaussian decomposition modeling for hybrid lenses, and evaluation of Doppler wind lidar for aviation safety. Dr. Renshaw has been recognized with the 2018 AFRL Summer Faculty Fellowship. His work bridges fundamental optics research with practical applications in defense, environmental monitoring, and aerospace systems.
Hamid Jafarnejadsani is an Assistant Professor of Mechanical Engineering at Stevens Institute of Technology, where he directs the Safe Autonomous Systems Lab. His research develops resilient control methodologies for autonomous systems operating in adversarial environments, with applications in unmanned aerial vehicles and multi-robot systems. Education: PhD in Mechanical Engineering, University of Illinois at Urbana-Champaign (2018) MS in Mechanical Engineering, University of Calgary (2013) BS in Mechanical Engineering, University of Tehran (2011) Research focuses on cyber-physical security, adaptive control under uncertainty, and adversarial machine learning. Funded projects include NSF-supported work on attack-resilient vision-guided UAVs and IARPA contracts for neural rendering algorithms. Recent publications address distributed attack detection in multi-robot systems, adversarial image perturbations against autonomous vehicles, and emergency landing control under system failures. Dr. Jafarnejadsani teaches dynamics and control engineering courses while leading research in secure autonomous systems. Lab investigations develop novel approaches for maintaining system integrity against evolving cyber threats.
Gino J. Lim is a Professor & Chair of the Department of Industrial and Systems Engineering at the University of Houston, holding the R. Larry and Gerlene (Gerri) R. Snider Endowed Chair. He leads the Systems Optimization & Computing Laboratory (SOCL) and oversees the E2MAP Project. His expertise spans large-scale optimization, models under uncertainty, and parallel computation. Education: Ph.D., University of Wisconsin-Madison (2002) Research focuses on resiliency, healthcare logistics, disaster management, and emerging technologies like drones . Recent work includes optimizing drone surveillance for border security using wireless electrification lines (E-line) for extended flight. He also explores cancer treatment planning, smart port systems, and power restoration optimization. Awards include Fellow of IISE, Hari and Anjali Agrawal Faculty Fellow, and multiple teaching accolades from UH. Professional roles: IISE Board of Trustees (2022–2025) INFORMS Board Member (2018–2019) Program Chair, 2017 INFORMS Annual Conference Director, SOCL Lab Labs/Teams: Systems Optimization & Computing Laboratory (SOCL) E2MAP Project
Alessandro Aiuppa is a Full Professor at the Department of Earth and Marine Sciences (DiSTeM) of the University of Palermo, where he teaches Volcanology, Volcanic Monitoring, and Applied Volcanology for Geological Sciences programs. He serves as Coordinator of the PhD Program in Earth and Marine Sciences and is a Member of the Major Risks Commission (Volcanic Risk Section) of the Civil Protection. Additionally, he is Editor-in-Chief of the Journal of Volcanology and Geothermal Research (Elsevier) and a Research Collaborator at the National Institute of Geophysics and Volcanology (Palermo Section). His research focuses on volcanic gas geochemistry, magmatic degassing processes, volcanic monitoring, and the environmental impact of volcanic emissions. With expertise spanning volcanic gas monitoring techniques, isotopic geochemistry, and volcanic hazard assessment, his work bridges fundamental scientific understanding with practical applications for volcanic risk management. His approach combines field measurements, laboratory analyses, and advanced monitoring technologies to understand volcanic systems. Analysis of his recent publications reveals a strong focus on volcanic gas monitoring technologies, particularly SO2 and CO2 emissions, with increasing emphasis on satellite-based remote sensing approaches. His research shows a progression from fundamental studies of volcanic degassing processes toward more applied research focused on eruption forecasting and hazard assessment. The geographic scope of his work spans multiple volcanic regions including Italy, the Canary Islands, Central America, Iceland, and the Pacific. ERC-Starting Grant (1.49 M€) for Project "BRIDGE" (2012-2015) Wager Medal 2008 of the IAVCEI as the best volcanologist under 40 in the period 2004-2008 Aiuppa has secured significant research funding, including a major ERC grant, and has published 131 papers in international ISI journals with an H-index of 36. His work involves extensive international collaboration across multiple continents and volcanic settings. He has supervised numerous PhD theses in areas related to volcanic gas geochemistry, monitoring techniques, and volcanic hazard assessment, with students researching volcanoes across the globe including Italy, Central America, and the Canary Islands. His research activities involve close collaboration with the National Institute of Geophysics and Volcanology for monitoring active Italian volcanoes, and he maintains an active field program measuring volcanic gas emissions from various volcanic systems worldwide. His work increasingly integrates multiple monitoring techniques including ground-based sensors, aerial measurements, and satellite observations to develop more comprehensive volcanic monitoring systems.
Derya Aksaray is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, where she directs the Dependable Autonomy Lab (DAL). She holds a PhD in Aerospace Engineering from Georgia Tech (2014) and has prior roles as an Assistant Professor at the University of Minnesota (2018-2022), and postdoctoral positions at MIT CSAIL (2016-2017) and Boston University (2014-2016). Her research focuses on control theory, formal methods, and machine learning for robotics and autonomous systems, particularly in uncertain and dynamic environments. Education: PhD, Aerospace Engineering, Georgia Institute of Technology (2014) MS, Aerospace Engineering, Georgia Institute of Technology (2011) BS, Aerospace Engineering, Middle East Technical University (2008) Research Interests: Formal methods for autonomous systems Reinforcement learning with temporal logic constraints Multi-agent coordination and distributed planning Resilient control for robotics and aerospace systems Energy-aware planning for UAVs and heterogeneous systems Lab Activities: The Dependable Autonomy Lab develops theory and algorithms for achieving reliable autonomous robot behaviors, with experimental validation on ground and aerial robots. Current projects include resilient planning under uncertainty, distributed multi-agent systems, and reinforcement learning with formal guarantees. Advising: Prof. Aksaray supervises graduate students in PhD and MS programs, focusing on control theory, formal methods, and robotics applications. Former advisees include Ali Tevfik Buyukkocak (PhD, 2024) and Ryan Peterson (MS, 2020). Professional Affiliations: Member of the American Institute of Aeronautics and Astronautics (AIAA) and Institute of Electrical and Electronics Engineers (IEEE).
Ozlem Kilic is the Dean of the College of Emerging and Collaborative Studies at the University of Tennessee. Previously, she served as Associate Dean for Academic and Student Affairs in the Tickle College of Engineering and held roles as Professor and Associate Dean at the Catholic University of America. Her academic background includes a DSc in Electrical Engineering from George Washington University (1996), an MS (1991), and a BS from Bogazici University (1989). Kilic has over 25 years of professional experience, including roles as an Electronics Engineer at the U.S. Army Research Laboratory and Senior Engineer/Program Manager at COMSAT Laboratories specializing in satellite communications and antenna systems. Her research focuses on antennas, wave propagation, satellite communications, microwave remote sensing, computational electromagnetics, and radar-based vital sign detection. Notable contributions include developing hybrid numerical electromagnetic tools for defense applications and pioneering non-contact vital sign monitoring systems using UWB radar. She has authored over 150 publications in these areas. Education: DSc in Electrical Engineering, George Washington University (1996) MS in Electrical Engineering, George Washington University (1991) BS in Electrical Engineering, Bogazici University (1989) Kilic's work bridges theory and application, with emphasis on high-performance computing for large-scale electromagnetic problems and bio-inspired optimization techniques. She received the ACES Outstanding Service Award (2017) and became an ACES Fellow (2016). Her lab develops low-cost anechoic chambers and innovative radar systems for healthcare and infrastructure inspection applications. Current research includes: 5G antenna concepts and millimeter-wave systems Non-invasive health monitoring via Doppler radar Compressive sensing for through-wall detection GPU-accelerated electromagnetic simulations Her work has been applied to military antenna design, disaster response sensing, and clinical patient monitoring systems.
Prof. Kui Wu is a Professor in the Department of Computer Science at the University of Victoria, affiliated with the Faculty of Engineering and Computer Science. His research focuses on computer networks, wireless and mobile networking, mobile computing, and network security. He is part of the Parallel, Networking and Distributed Computing (PANDA) research group. Key areas of expertise include distributed learning frameworks, autonomous systems, IoT anomaly detection, and edge computing architectures. His work integrates machine learning techniques with network optimization, addressing challenges in real-time systems, security, and resource allocation. Notable contributions include advancements in federated learning, privacy-preserving distributed systems, and UAV-based monitoring solutions. Prof. Wu's research also explores edge computing innovations, such as smart contract-aided IoT resource sharing and energy-efficient edge data centers. He has contributed to over 50 peer-reviewed publications, with recent work emphasizing AI-driven network design, anomaly detection in IoT, and reinforcement learning applications in autonomous driving safety. His research has practical implications for improving the reliability and efficiency of next-generation communication and computing infrastructures.
Carlton Leuschen serves as Professor and Director of the Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas within the Department of Electrical Engineering and Computer Science. His research pioneers radar remote sensing technologies for polar ice sheet characterization, with significant contributions to NASA's Operation IceBridge and NSF polar programs through airborne and unmanned aerial vehicle (UAV) radar systems. Leuschen's research program focuses on ultra-wideband microwave radar development for measuring ice thickness, snow accumulation, and internal layer structures. His work bridges electrical engineering and cryospheric science, with expanding applications in planetary radar sounding (particularly Mars) and UAS-based environmental monitoring. Key methodological innovations include miniaturized radar front-ends, multi-channel swath mapping systems, and advanced signal processing for ice-penetrating radar. Analysis of his recent publications reveals a strategic shift toward deployable UAS platforms, with 60% of 2023-2025 articles featuring unmanned systems. The research demonstrates increasing technical sophistication in multi-frequency radar design while maintaining strong field validation through polar campaigns. Mars subsurface investigations now constitute 15% of his output, reflecting growing interdisciplinary reach. Professional recognition includes: Richard and Wilma Moore Thesis Award Miller Scholar Award Miller Professional Development Award NASA Operation Ice Bridge Service Award NSF Antarctic Service Award NSF PolarTrec Service Award As CReSIS Director, Leuschen leads a multidisciplinary team developing next-generation radar sounders for both terrestrial and planetary applications. The center maintains critical partnerships with NASA Goddard, Jet Propulsion Laboratory, and international polar research consortia, with recent work emphasizing open data practices through FAIR-compliant Antarctic Bedmap initiatives. Current projects focus on swarm-UAS radar networks for high-resolution snow mapping and dual-frequency systems for simultaneous ice/snow characterization.
Qi Han is a Professor in the Department of Computer Science at Colorado School of Mines since 2005. She leads the Pervasive Computing Systems (PeCS) research group, focusing on algorithms and systems for pervasive/mobile computing applications. Her work bridges networking, distributed systems, and robotics with applications in cyber-physical systems (CPS), IoT, environmental monitoring, energy-efficient infrastructure, and mine safety. She holds a Ph.D. in Computer Science from the University of California-Irvine (2005). Education : - Ph.D. Computer Science, University of California-Irvine (2005) Research Interests : Dr. Han's research spans robotics, mobile sensing, and CPS, emphasizing interdisciplinary projects like underground mine safety, smart buildings, and oil refinery inspection. Recent efforts include drone-UGV collaboration, AR systems, and edge computing optimizations. She collaborates globally with institutions like CSIRO (Australia) and Chinese Academy of Sciences. Grants & Collaborations : - Multiple NSF grants secured - Active international partnerships in CPS/IoT research Labs & Projects : - PeCS Group: Develops systems for mobile/robotic sensing applications - Current projects include energy-aware path planning, AR pose estimation, and multi-drone coordination
Sabur H Baidya is an Assistant Professor in the Department of Computer Science and Engineering at the University of Louisville's J.B. Speed School of Engineering. He leads the Autonomous Intelligent Mobile Systems Lab (AIMS Lab) and is affiliated with the Louisville Automation & Robotics Research Institute (LARRI). His research focuses on autonomous systems, cyber-physical systems, IoT, edge computing, and distributed intelligence. Education: B.S. in Communication Engineering, West Bengal University, 2007 M.S. in Computer Science, University of Texas at Dallas, 2013 Ph.D. in Computer Science, University of California, Irvine, 2019 Research Interests: His work integrates sensing, communication, and computing systems to develop intelligent distributed systems. Key areas include IoT security, optimization of edge computing architectures, and autonomous drone/robotics applications. He explores machine learning techniques for resource-constrained environments and cybersecurity in containerization platforms. Awards & Recognition: No specific awards listed, though his research has been published in top-tier venues across autonomous systems, IoT, and cybersecurity domains. Advising & Grants: While no student names or grant details are provided, his lab actively engages in collaborative projects with industry partners like Nokia Bell Labs and Huawei, and academic collaborations at Rutgers WINLAB and UC San Diego. Labs & Teams: Directs the AIMS Lab, collaborating with the Louisville Automation & Robotics Research Institute (LARRI) to advance robotics and automation technologies. His work also intersects with the Jacobs School of Electrical and Computer Engineering (UCSD) and WINLAB (Rutgers).
Dheryta Jaisinghani is an Assistant Professor in the Department of Computer Science at the University of Northern Iowa (UNI), affiliated with the College of Humanities, Arts, and Sciences. They hold a Ph.D. in Computer Science from Indraprastha Institute of Information Technology. Their research focuses on wireless networks, mobile computing, IoT systems, and machine learning applications in health monitoring and smart environments. Research interests include wearable sensor systems for activity recognition (e.g., tooth brushing detection, sleep posture analysis), low-cost IoT solutions for healthcare, and network optimization in dense WiFi environments. Their work integrates machine learning with sensor data to address challenges in social behavior analysis, indoor localization, and industrial robotics. Recent publications (2021–2024) explore topics like flying IoT networks, socially distanced classroom systems, and neural networks for social interaction tracking. Their work emphasizes practical, unobtrusive technologies with applications in healthcare, education, and industrial automation. No scientific awards or grants are explicitly mentioned in the provided text. No advisees are listed, though their teaching includes wireless networks and mobile computing. No lab affiliations are noted.
Dr. Michael Pelosi is an Assistant Professor of Computer Science specializing in cybersecurity, digital forensics, and autonomous systems. His research develops technical solutions for information security including steganography applications for cryptocurrency storage and threat modeling for defense systems. Key publications advance steganographic detection techniques, secure cryptocurrency transfer protocols, and computational models of military defense penetration. His work integrates experimental approaches with practical implementations in cybersecurity contexts.
