Walid Hubbi is Associate Professor in Electrical and Computer Engineering at NJIT. He holds a PhD from Queen's University Belfast and degrees from the University of London and Aleppo University. His research focuses on power system analysis and control, particularly optimization techniques for reactive power compensation, load flow methodologies, and stability enhancement. Key contributions include fuzzy logic controllers for static VAR compensators, neural network applications for load modeling, and optimal placement strategies for grid control devices. His publications consistently address practical challenges in transmission efficiency, voltage stability, and measurement accuracy using computational intelligence and optimization frameworks.
Luca Schenato is a Full Professor in the Department of Information Engineering at the University of Padova. His research focuses on distributed control systems, federated learning, multi-agent optimization, and wireless communication protocols. He has extensive experience in developing algorithms for cyber-physical systems, with applications in robotics, smart grids, and sensor networks. Education and Appointments section lists his academic journey but lacks explicit details. He has held positions related to control systems and information engineering throughout his career. Research interests include: Design of resilient wireless control systems Federated learning architectures for edge computing Distributed optimization under communication constraints Robotics and multi-agent coordination Smart energy management systems His recent publications (2021–2025) demonstrate a strong focus on: Over-the-air federated learning innovations High-speed wireless control systems (e.g., 1 kHz Wi-Fi control) Resilient distributed optimization algorithms Human-centric building automation He has contributed to numerous projects related to networked control systems and has organized conferences like ECC13. His work emphasizes bridging theoretical control principles with practical industrial applications.
Ozgur Ozdemir is an Associate Research Professor in the Department of Electrical and Computer Engineering at North Carolina State University's College of Engineering. He is affiliated with the university's primary faculty and works closely with platforms like AERPAW and AFAR Challenge. His research focuses on advanced wireless systems, including UAV networks, mmWave technology, spectrum analysis, and radar-communication integration. His work spans experimental testbed development, digital twin applications for AI research, and methodologies for improving coverage in rural and urban environments. Ozdemir has contributed to standards like 5G NR and non-standalone 5G systems, emphasizing practical implementation and environmental impact analysis. He leads efforts in signal processing for autonomous systems and has expertise in software-defined radio (SDR) technologies. Research interests include aerial threat detection, RF signal analysis, and robust localization techniques. He explores challenges in NLOS bias correction, antenna radiation patterns, and passive reflector-based coverage enhancement. His work often combines theoretical models with experimental validation using platforms like AERPAW. His articles highlight advancements in drone detection systems, channel modeling for mmWave, and the integration of radar and communication systems. Key trends show a focus on outdoor/indoor spectrum measurements, UAV navigation, and resilient network design. Ozdemir's contributions are characterized by empirical studies and cross-disciplinary approaches to wireless challenges.
Mine Çağlar is a Professor in the Department of Mathematics at Koç University, specializing in probability theory and stochastic processes with applications in mathematical finance and risk analysis. Her work addresses fundamental problems in Markov additive processes, Lévy processes, and Brownian motion, contributing to both theoretical advances and practical financial modeling. Her academic credentials include: PhD in Statistics and Operations Research from Princeton University (1997) Master’s in Industrial Engineering from Bilkent University (1991) B.A. in Industrial Engineering from Middle East Technical University (1989) Professor Çağlar’s research centers on extreme event analysis in stochastic processes, particularly maximum drawdown, maximum loss, and optimal stopping problems. She investigates path properties of spectrally negative Lévy processes and develops mathematical frameworks for degenerate market models. Her work bridges abstract probability theory with real-world financial applications, including risk management and hedging strategies. Recent publications demonstrate sustained innovation in stochastic analysis, with a focus on long-time behavior of complex processes and boundary-crossing phenomena. Analysis of her 15 most recent publications (2018–2024) reveals a cohesive research trajectory emphasizing Markov additive processes (40% of articles), Lévy process extremes (30%), and financial applications (20%). Key methodological trends include path decomposition techniques, Monge-Ampère equations on Wiener space, and stochastic flow modeling. Her work increasingly integrates fluid dynamics concepts like Çinlar models for turbulence simulation, reflecting interdisciplinary expansion into applied mathematics. Her scholarly recognition includes: Hayri Körezlioğlu Research Award (2013) Parlar Foundation Research Incentive Award (2005)
Dr. Yaguang Zhang is a Clinical Assistant Professor at Purdue University, jointly appointed in the Department of Agricultural & Biological Engineering (ABE) and the Department of Agricultural Sciences Education & Communication (ASEC) . Holding a Ph.D. in Electrical and Computer Engineering from Purdue (2021), he specializes in data science , digital agriculture , and UAV-aided wireless communication systems , with applications in intelligent transportation, proactive road maintenance, and engineering education. Education: Ph.D. and M.Sc. in Electrical and Computer Engineering (Purdue), B.Eng. in Communication Engineering (Tianjin University) Research Interests span cutting-edge domains including: Digital Agriculture: GPS-based field shape generation, product traceability trees, and automated metadata collection for agricultural operations Wireless Communication: Millimeter-wave channel modeling, UAV relay systems, and rural network coverage optimization Smart Infrastructure: Pavement condition assessment tools, sun-shadow simulation for road treatment, and vehicle automation platforms Recent Publications emphasize scalable solutions for agricultural IoT, machine learning in crop monitoring, and interoperable data frameworks. His scientific awards include: 2024 Outstanding Engineering Teacher (Purdue) 2024 ASABE Superior Paper Award 2020 FFAR Student Poster First Prize Multiple NSF/IEEE travel supports Grants from USDA, NSF, INDOT, and industry partners (CableLabs, Nokia) fund projects like tractor autopilot development, rural 6G networks, and pavement monitoring systems. He mentors graduate students in agricultural robotics , data science , and connected vehicle research .
Martin Steinberger is an Associate Professor at the Institute of Control and Automation (IRT) at Graz University of Technology (TU Graz). His work focuses on advanced control systems, networked control, model predictive control (MPC), and automation in manufacturing and autonomous systems. He leads research into real-time optimization, fault diagnosis, and safety-critical applications in industries like pharmaceuticals and automotive. Research interests include: Networked Control Systems Model-Based Control Autonomous Vehicle Trajectory Planning Process Automation Robotics and Industrial Automation His work bridges theoretical control engineering with practical applications in manufacturing lines, chemical processes, and autonomous driving. Recent studies emphasize digital real-time release testing for pharmaceuticals, universal control concepts for manufacturing systems, and safety-aware trajectory optimization for automated vehicles. His publications frequently address challenges in time-varying delays, packet loss mitigation, and robust observer design for nonlinear systems. Steinberger collaborates on EU-funded projects and regularly contributes to conferences like the International Workshop on Variable Structure Systems. His research often involves experimental validation, as seen in work with compact pharmaceutical manufacturing setups and small-scale autonomous vehicle testing platforms.
Yiannis Karayiannidis is a Senior Researcher (equivalent to Associate Professor/Research) with the Division of Systems and Control (SYSCON), Department of Electrical Engineering at Chalmers University of Technology. He maintains a significant affiliation with the Department of Robotics, Perception and Learning at KTH Royal Institute of Technology, demonstrating his cross-institutional impact in the Swedish robotics community. Dr. Karayiannidis earned his Diploma in Engineering in 2004, followed by a Ph.D. in Engineering in 2009, and achieved Docent status in 2017. His academic journey has focused on robotics and control systems, establishing him as a leading researcher in these fields. His primary research interests span robot control, robotic manipulation in human-centered environments, dual arm manipulation, force control, robotic assembly, control of physical human-robot interaction, multi-agent robotic systems, adaptive control and nonlinear control systems. Dr. Karayiannidis has made significant contributions to the understanding of deformable object manipulation, contact-rich robotic tasks, and human-robot collaboration. His work bridges theoretical control systems with practical robotic applications, particularly in scenarios requiring precise physical interaction. Analysis of his recent publications reveals a strong focus on advanced manipulation techniques, particularly for deformable linear objects, and human-robot collaborative tasks. His research increasingly incorporates machine learning approaches, especially reinforcement learning, to address complex manipulation challenges. There is also a clear emphasis on practical applications in industrial settings, with several projects related to robotic assembly and cable routing. Dr. Karayiannidis serves as Associate Editor for the IEEE Robotics and Automation Letters, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), and the European Control Conference. He is also the treasurer of the IEEE Robotics Chapter in Sweden and a WASP-affiliated researcher. He has served as Principal Investigator for multiple research projects including DARMA and DARMA_bridge (funded by WASP), CHROMA (funded by VR), and the H2020 SARAFun project. His current projects include "Learning & Understanding Human-Centered Robotic Manipulation Strategies" (2020-2025), "Computer Vision and Machine Learning for Robot Systems" (2019-2021), and "ViMCoR" (2019-2021) in collaboration with Volvo Group. Dr. Karayiannidis is actively involved in the robotics research community through his editorial roles and project leadership. His work connects theoretical control systems with practical robotic applications, particularly in industrial and human-robot collaborative settings.
Prof. Dr. Thomas Grätsch is a faculty member at Hamburg University of Applied Sciences within the Faculty of Technology and Computer Science, specifically in the Department of Mechanical Engineering and Production. His office is located in Room 226e at Berliner Tor 21, 20099 Hamburg, with contact number +49 40 428 75-8705. Prof. Grätsch specializes in computational mechanics with a focus on the Finite Element Method (FEM) and its applications in vibroacoustics. His research particularly addresses noise emission from wind turbines, structural vibration analysis, and mechanical system simulations. He has developed sophisticated models for predicting and reducing tonal noise in wind energy systems, with emphasis on gearbox vibrations and acoustic radiation from large structures. His publication record shows a consistent research trajectory focused on wind turbine noise simulation, with recent work (2018-2022) concentrating on hybrid multistep procedures, large-scale finite element modeling, and practical applications for noise reduction in wind energy systems. His work bridges theoretical computational methods with practical engineering applications in renewable energy technology. Prof. Grätsch holds several administrative roles including Program Coordinator for the Master's program 'Calculation and Simulation in Mechanical Engineering', Spokesperson for the Mechanics Group, Member of the Department Council for Mechanical Engineering and Production, and Deputy Member of the Confidence Committee of the Faculty of Technology and Computer Science. He is also a Member of the Editorial Board of Computers & Structures. His research projects focus on vibroacoustics, particularly addressing noise emission from wind turbines through computational simulation and structural analysis. His work has practical implications for the wind energy industry seeking to reduce environmental noise pollution while maintaining energy production efficiency.
Miguel A. Bandres is an Assistant Professor at CREOL, The College of Optics and Photonics at the University of Central Florida. His research focuses on topological photonics, spatiotemporal light control, and ultrafast optical phenomena. Research directions include: Topological protection mechanisms for light propagation Synthesis of complex spatiotemporal waveforms Optical analogies to condensed matter phenomena Novel beam solutions for imaging and sensing His group (Bandres Group) integrates theoretical modeling, optical fabrication, and experimental characterization. Current projects explore Lorentz-invariant wavepackets, topological lasers, and multidimensional pulse shaping techniques.
Marko Djordjevic is an Associate Professor at the Faculty of Biology, University of Belgrade. His research spans computational biology of infectious diseases, bacterial immune systems (CRISPR/Cas and restriction-modification systems), and quantitative understanding of infection progression with applications to SARS-CoV-2 and computational physics of quark-gluon plasma. Diploma in Physics, Faculty of Physics, University of Belgrade, Serbia. PhD in Biophysics and Bioinformatics, Department of Physics, Columbia University, USA. Postdoctoral training at the Mathematical Biosciences Institute, Ohio State University, USA. Djordjevic's research focuses on nonlinear regulatory dynamics of bacterial immune systems, their role in horizontal gene transfer, and modeling infection progression under social mitigation measures. His secondary interest in computational physics examines quark-gluon plasma dynamics via high-p⊥ observables and tomography. His recent publications address CRISPR/Cas regulation, restriction-modification systems, and SARS-CoV-2 transmissibility drivers. Grants from the Serbian Ministry of Science, Science Fund of Serbia, EU Marie Curie IRG, and Swiss National Science Foundation support his work.
Peter Vary is a Professor at the Faculty of Electrical Engineering and Information Technology of RWTH Aachen University, serving as Director of the Institute for Communication Systems. His work focuses on speech and audio signal processing for communication systems. Digital Signal Processing Speech Enhancement Acoustic Echo Control Microphone Array Beamforming Communication Systems Audio Compression His recent publications (2023–2024) emphasize speech coding, noise reduction, and bandwidth extension for hearing aids and mobile devices, with technical innovations in Kalman filters, hybrid digital-analog transmission, and wind noise detection. He holds a leadership role in the Institute for Communication Systems and serves as Ombudsperson for teaching in his faculty. Contact: vary@iks.rwth-aachen.de
Fengjing Liu is an Associate Professor at the Great Lakes Research Center (GLRC) of Michigan Technological University. His research focuses on ecohydrology, watershed hydrology, and biogeochemistry, with an emphasis on understanding the impacts of human perturbation and climate change on water resources. He leads studies in snowmelt-dominated watersheds, black ash wetlands, and the interactions between landscape and climate in the Great Lakes region. Education: PhD, Hydrology and Biogeochemistry, University of Colorado at Boulder MS, Hydrology and Water Resources, Lanzhou Institute of Glaciology & Geocryology, Chinese Academy of Sciences BS, Hydrogeology and Engineering Geology, Lanzhou University, China Research Interests: Dr. Liu’s work addresses three core themes: (1) the effects of forest management and invasive species on black ash wetlands, (2) snowmelt dynamics and climate change impacts in headwater catchments, and (3) landscape-climate interactions influencing water and greenhouse gas fluxes. His methods include isotope hydrology, end-member mixing analysis, and advanced hydrochemical tracing. Publications: Recent work explores snowmelt-regulated stream chemistry, climate-driven glacier mass loss, and agroforestry’s role in nitrogen mitigation. His studies span diverse regions from the Tibetan Plateau to the Great Lakes Basin, emphasizing interdisciplinary approaches to water sustainability. Grants & Advising: His research has been supported by grants focusing on ecohydrology and climate adaptation. While specific grants are not listed, his publications reflect collaborative projects with institutions like the USDA Forest Service and the National Science Foundation. Labs/Teams: Maintains active research programs within the GLRC, focusing on field experiments, hydrological modeling, and environmental monitoring in cold and temperate regions.
Dr. Nariman Sepehri is a Professor in the Department of Mechanical Engineering at the Price Faculty of Engineering, University of Manitoba, Canada. He has held significant administrative roles including Department Associate Head (Graduate Studies), Associate Dean of Engineering (Undergraduate Programs), and Acting Dean of Engineering. His research focuses on fluid power systems, robotics, and control with applications in rehabilitation and heavy machinery. Education: Post-Doctorate, Electrical & Computer Engineering, University of British Columbia, Canada (Tele-Robotics, Mechatronics) PhD, Mechanical Engineering, University of British Columbia, Canada (Control, Fluid Power Systems, Robotics) MSc, Mechanical Engineering, University of British Columbia, Canada (Computer-Aided Manufacturing Planning) BSc, Mechanical Engineering, Sharif University of Technology, Iran (Machine Design) Dr. Sepehri's research interests span Fluid Power Systems and Technology , Robotics and Teleoperation , Control Systems , Condition Monitoring , and Mechatronics of Rehabilitation Devices . His work integrates advanced control theory with practical applications in hydraulic and pneumatic systems, aiming to improve energy efficiency and reliability in robotics, manufacturing, aerospace, and healthcare. Notably, he has developed innovative rehabilitation devices using game-based interfaces for stroke and cerebral palsy patients. His recent publications (2022-2025) demonstrate a strong trend towards energy-efficient hydraulic systems, fault detection using machine learning, and the development of soft robotic actuators for rehabilitation. Key areas include electro-hydrostatic actuators, pump-controlled circuits, and the application of advanced algorithms for condition monitoring and control. Scientific Awards: Dean of Engineering’s Award for Superior Academic Performance University of Manitoba Rh Award for outstanding contributions to scholarships and research in Applied Sciences Fellow of the Canadian Academy of Engineering (CAE) Fellow of the American Society of Mechanical Engineers (ASME) Fellow of the Canadian Society for Mechanical Engineering (CSME) Dr. Sepehri has supervised over 100 graduate and postdoctoral students, contributing significantly to the field of fluid power and robotics. His research has been supported by major grants from the Natural Sciences and Engineering Research Council of Canada (NSERC) and other sources, enabling the establishment of the Fluid Power Research Laboratory. This lab features state-of-the-art equipment including a human-robot-in-the-loop simulator and hardware-in-the-loop test facilities for condition monitoring. The Fluid Power Research Laboratory at the University of Manitoba, under Dr. Sepehri's leadership, is a hub for innovation in fluid power technology. The lab collaborates internationally with researchers in USA, Brazil, China, Hungary, Romania, Denmark, Sweden and France, and has developed interdisciplinary projects bridging engineering with healthcare applications.
Dr. Muhammad Sheikh is a Visiting Professor in the Department of Information and Communications Engineering at Tampere University of Technology. He holds a Doctoral degree in Engineering and Technology from the same institution (2014). His research focuses on wireless communication systems, with emphasis on millimeter-wave and sub-THz technologies, backscatter communication, network optimization, and 5G/6G infrastructure. He has published over 41 articles since 2019, with notable works on channel characterization, polarization adaptation, and OneRAN mobile infrastructure. His research contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and infrastructure development. Research Highlights: Explored integration of ambient backscatter IoT into cellular networks (2025) Developed polarization adaptation techniques for small cell networks (2024) Conducted sub-THz channel measurements in indoor environments (2023) Awards: Bronze Best Paper Award (2020) Second Best Paper Award (2019) His work spans theoretical and experimental studies, including ray tracing simulations and field measurements. Collaborations include projects on drone propagation analysis and urban macrocell path loss.
Dean F. Hougen is the Lloyd and Joyce Austin Presidential Professor and Director of the School of Computer Science at the University of Oklahoma, within the Gallogly College of Engineering. He also holds affiliations with the School of Electrical and Computer Engineering, Data Science and Analytics Institute, and has served as Interim Director and Associate Director of the School of Computer Science. His research focuses on artificial intelligence, robotics, machine learning, and distributed systems, conducted in labs like the Robotic Intelligence and Machine Learning Laboratory and the Artificial Intelligence Research (AIR) SuperLab. Key areas include evolutionary computation, autonomous systems, and applied AI in healthcare and transportation. He has led over $24M in grants, including projects on intelligent aerospace systems, pandemic monitoring, and robotics for infrastructure safety. Notable awards include the Presidential Professorship, multiple best paper awards, and recognition for teaching excellence. Hougen has advised numerous students and contributed to interdisciplinary initiatives, including the CS INCLUDES program supporting Indigenous learners. His work spans academic leadership, industry collaborations, and advancing AI applications across domains.
