Athanasios Rontogiannis is an Associate Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA). He holds a PhD in Signal Processing from the National University of Athens (1997) and has held roles including Research Director at the National Observatory of Athens (2017–2021). His research focuses on signal processing, machine learning, and hyperspectral image analysis. Education: MEng (Electrical Engineering, NTUA, 1991), M.A.Sc. (University of Victoria, Canada, 1993), PhD (Signal Processing, National University of Athens, 1997). Research interests include adaptive algorithms, sparse representations, and tensor models. He has served on editorial boards of IEEE Transactions on Signal Processing and EURASIP journals, receiving an honorary distinction in 2020. He is a Senior Member of IEEE and affiliated with EURASIP and the Technical Chamber of Greece. Key contributions span hyperspectral unmixing, Bayesian algorithms, and space data exploitation. His work integrates machine learning for applications in space science and signal processing.
Marco Di Renzo is a CNRS Professor (Directeur de Recherche Titulaire) at University of Paris-Saclay, affiliated with CentraleSupelec and the Signals and Systems Laboratory (L2S). He serves as Coordinator of the Communications Networks Area at the DigiCosme Laboratory of Excellence and Editor-in-Chief of IEEE Communications Letters. His academic leadership includes membership in the Ph.D. School on ICT Admission Committee at Paris-Saclay University. His educational background includes a Laurea (cum laude) and Ph.D. in Electrical Engineering from University of L'Aquila, Italy (2003, 2007), and a Habilitation à Diriger des Recherches from University Paris-Sud (2013). Laurea (cum laude), Electrical Engineering, University of L'Aquila (2003) Ph.D., Electrical Engineering, University of L'Aquila (2007) Habilitation à Diriger des Recherches, University Paris-Sud (2013) Di Renzo's research focuses on next-generation wireless communications, particularly reconfigurable intelligent surfaces (RIS), 6G technologies, and stochastic geometry modeling. His work bridges theoretical communication theory with practical implementations in cellular networks, millimeter-wave communications, and ultra-wide band systems. Recent publications demonstrate leadership in holographic metasurfaces, integrated sensing and communication (ISAC), and AI-empowered network design, establishing him as a pioneer in electromagnetic wave manipulation for future networks. His award-winning publications span RIS-aided communications, channel modeling, and security frameworks. Analysis of his recent work reveals consistent focus on three pillars: (1) fundamental electromagnetic theory for wave manipulation, (2) practical RIS implementations across frequency bands, and (3) integration with AI for network optimization. His articles frequently address industrial applications including factory automation and space-air-ground networks. Di Renzo's scientific recognition includes: IEEE Fellow (2020) and IET Fellow (2020) Highly Cited Researcher (Web of Science, 2019) SEE-IEEE Alain Glavieux Award (2017) Multiple Best Paper Awards (IEEE ICC, EURASIP) Nokia Foundation Visiting Professorship (2020) As Principal Investigator for CNRS, he coordinates multiple Horizon 2020 projects including SURFER, PathFinder, and MetaWireless. His leadership extends to serving as Project Coordinator for H2020 5Gwireless, 5Gaura, MAPNET, and REDESIGN. With over 350 publications, 17,000+ citations, and h-index of 66+, his research group maintains strong industry partnerships with Nokia and other telecommunications leaders. Di Renzo directs the Signals and Systems Laboratory (L2S) at Paris-Saclay and coordinates the DigiCosme Excellence Lab's Communications Networks Area. His team specializes in electromagnetic modeling for wireless networks and has pioneered the European Telecommunications Standards Institute (ETSI) Industry Specification Group on RIS. The group maintains active collaborations with Aalto University (Finland), University of Technology Sydney (Australia), and University of L'Aquila (Italy).
Dr. Thanh-Son Pham is an ARC DECRA Research Fellow in the Geophysics Department at The Australian National University’s Research School of Earth Sciences. His research focuses on using seismic waves to study Earth’s interior structures, from polar ice sheets to the inner core. He has pioneered methods like teleseismic P-wave coda autocorrelation and coda correlation wavefield analysis, leading to breakthroughs such as detecting J-waves in the inner core and identifying an innermost inner core layer. His work has been featured in Science , Nature Communications , and international media. He holds a PhD from ANU (2019) and has supervised research projects on Antarctic seismology and earthquake source physics. Awards include the 2024 Zatman lectureship from SEDI. Current projects include probing Antarctic ice sheets via correlation seismology and advancing machine learning tools for deep Earth studies. Education: PhD in Geophysics (ANU, 2019), Graduate Diploma in Earth System Physics (ICTP, 2015), BSc in Applied Mathematics (Hanoi University, 2013) Research interests span seismic source inversion, Antarctic ice dynamics, and inner core anisotropy. His 2024 articles address Hunga Tonga eruption mechanics and PKIKP wave analysis using deep learning. Media highlights include BBC, NYT, and ANU press releases.
Professor Igor Wigman is a Professor of Number Theory at King's College London, affiliated with the Department of Mathematics within the Faculty of Natural, Mathematical & Engineering Sciences. He completed his PhD in Number Theory at Tel-Aviv University under Zeev Rudnick, followed by postdoctoral roles at CRM Montreal and KTH Stockholm. He joined King's in 2012 as a Lecturer, becoming a Reader in 2014 and Professor in 2018. His research focuses on analytic number theory, probability, and mathematical physics, with emphasis on nodal lines, random fields, and quantum chaos. Notable contributions include studies on the Gauss circle problem, eigenvalue clusters, and nodal volume distributions of random functions. Wigman co-organized the 2016 'Random Waves in London' workshop and delivered an inaugural lecture in 2023 on the interplay of number theory, random functions, and music geometry. His work bridges pure mathematics with applications in spectral geometry and stochastic processes.
Richard Allen is a Professor and the Class of 1954 Endowed Chair at the University of California, Berkeley, serving as Director of the Berkeley Seismological Laboratory. His work focuses on seismology, earthquake early warning systems, and seismic hazard mitigation. Research interests include earthquake rupture mechanisms, regional seismic structure and dynamics, mantle upwelling processes, fault interaction analysis, stress modeling in seismology, and machine learning applications in seismic data analysis. He pioneered smartphone-based seismic networks like MyShake and advanced technologies such as distributed acoustic sensing (DAS) for offshore monitoring. His recent publications highlight trends in earthquake early warning algorithms (EPIC, bEPIC), real-time ground-motion modeling, ShakeAlert system performance, and integration of multimodal data (e.g., social media, LLMs, DAS) for hazard mitigation. Collaborative efforts include global smartphone networks and cloud computing for seismic datasets. Allen leads the Berkeley Seismological Laboratory, driving innovations in seismic monitoring, structural health assessment, and public alerting systems to enhance disaster resilience.
Zeljko Pantic is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He holds a Ph.D. from NC State (2013) and B.S./M.S. degrees from the University of Belgrade (1998/2007). Before joining NC State in 2019, he served as an Assistant Professor and Associate Director of the Electric Vehicle and Roadway Research Facility at Utah State University. He is actively involved in editorial roles for IEEE Transactions on Transportation Electrification and serves on the IEEE IAS Transportation Systems Committee. Education: Ph.D., Electrical Engineering, North Carolina State University (2013) M.S., Electrical Engineering, University of Belgrade (2007) B.S., Electrical Engineering, University of Belgrade (1998) Research: Dr. Pantic specializes in electrified transportation systems, wireless power transfer (WPT), power converter design, and DC microgrid technologies. His work addresses challenges in EV charging infrastructure, magnetic circuit optimization, and energy conversion principles for transportation electrification. Recent projects include autonomous wireless charging systems for UAVs, marine DC microgrids, and road-embedded DWPT solutions. Awards & Recognition: 2019 IEEE JESTPE Second Prize Paper Award 2017 Outstanding Teacher of the Year (USU) 2012 NC State Mentored Teaching Assistantship Award Advisees & Grants: While specific student names are not listed, Dr. Pantic has advised graduate students on projects spanning WPT systems, EV infrastructure, and battery management. His work has been supported by grants focusing on dynamic charging, magnetic materials, and autonomous observatory nodes. Labs & Facilities: He leads research at NC State's Electric Vehicle and Roadway facility, focusing on roadway-integrated wireless charging and high-power WPT systems. Collaborations include ocean observatory development and autonomous system integration.
Marco Raiola is an Associate Professor at the Department of Aerospace Engineering , Universidad Carlos III de Madrid (UC3M). His research focuses on fluid dynamics, turbulence, and aerodynamics, with applications in flow diagnostics, heat transfer, and control systems. Research Interests: Turbulent flows, data-driven modeling, particle image velocimetry (PIV), convective heat transfer, and bio-inspired aerodynamics. Projects: Principal researcher in INFLUENTIA-CM-UC3M (2024-2026) and Diagnóstico del ruido de chorro (2022-2025). Collaborator in EU-funded initiatives like HumanIC and ODE4HERA . Contact: Email mraiola@ing.uc3m.es | ORCID: 0000-0003-2744-6347
Professor Atilla Ansal is a distinguished academic in Civil Engineering at Özyeğin University's School of Engineering, where he has served as a full-time professor since March 2012 and previously as the Founding Chair of the Civil Engineering Department from 2012-2019. With an extensive career spanning over five decades, Professor Ansal has held prominent positions at Istanbul Technical University, Bogaziçi University's Kandilli Observatory and Earthquake Research Institute, and has served as a visiting professor at numerous international institutions including Northwestern University, University of California, and Tokyo University. Northwestern University, 1978 (Doctorate) Civil Engineering, Istanbul Technical University, 1969 (Master's) Civil Engineering, Istanbul Technical University, 1969 (Bachelor's) Professor Ansal's research focuses on Earthquake Geotechnical Engineering, Soil Dynamics, Seismic Hazard Analysis, Landslide hazard analysis, Seismic Microzonation, and Laboratory and In-Situ Testing of Soil Properties. His work has significantly advanced our understanding of soil behavior under seismic loading, site response analysis, and seismic microzonation methodologies. His research has direct applications in urban planning, earthquake risk mitigation, and performance-based seismic design. Professor Ansal has pioneered approaches to site-specific earthquake characterization and developed methodologies for seismic microzonation that have been implemented in numerous Turkish cities and adopted internationally. His extensive publication record demonstrates consistent contributions to earthquake engineering, with recent work focusing on probabilistic seismic microzonation, 2D basin effects, site-specific response analysis, and performance-based design approaches. His research shows a clear evolution from fundamental soil behavior studies to practical applications in urban risk assessment and mitigation. 7th Prof.N.Ambraseys Lecturer (2024), European Association for Earthquake Engineering 15th Nonveiller Lecturer (2017), Croatian Geotechnical Society Third Prof.Dr. Rıfat Yarar Lecturer (2015), Turkish Civil Engineers Association Third Ord.Prof.Dr. Hamdi Peynircioglu Lecturer (1988) Professor Ansal has advised 15 PhD students and 27 Master's students, shaping the next generation of earthquake engineers. His leadership extends to editorial roles as Editor-in-Chief of the Springer journal 'Bulletin of Earthquake Engineering' since 2002 and Editor-in-Chief for the Springer book series on 'Geotechnical, Geological and Earthquake Engineering'. He served as Secretary General (1994-2014), President (2014-2018), and Vice President (2018-2022) of the European Association for Earthquake Engineering, significantly influencing the field internationally. His work has been supported by numerous grants from Turkish government agencies, international organizations including UNESCO, and collaborative research projects across Europe. Professor Ansal has been instrumental in establishing geotechnical monitoring systems in Istanbul, including vertical arrays for site response analysis. His leadership in the 'Earthquake Master Plan for Istanbul' and 'Seismic Microzonation for Municipalities' projects has created critical infrastructure for earthquake risk management in Turkey's most populous city. His work with GeoIst, Geotechnical Earthquake Engineering and Consultancy Inc. has translated academic research into practical engineering solutions for seismic risk mitigation.
Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.
Micheline B. Soley is an Assistant Professor in the Department of Chemistry at the University of Wisconsin-Madison with an affiliate appointment in Physics. She leads the Soley Research Group, which focuses on developing quantum computing algorithms, tensor-network methods, and quantum control strategies to address fundamental challenges in quantum dynamics and ultracold chemistry. Her research bridges theoretical chemistry, quantum information science, and computational physics. Education: Ph.D. in Chemical Physics, Harvard University (2020) A.M. in Chemistry, Harvard University (2016) Yale Quantum Institute Postdoctoral Fellow (2020-2022) Fulbright Fellow, Max Born Institute (2013-2014) B.S. in Chemistry and Music, Yale University, Magna Cum Laude (2013) Research Interests: Her work centers on three interconnected pillars: (1) Quantum computing algorithms and tensor-network methods for exact quantum dynamics, overcoming dimensionality limitations in chemical simulations; (2) Ultracold chemistry and quantum control, developing schemes to manipulate chemical reactions and analyze ultracold collisions; and (3) Theoretical spectroscopy, creating tools to simulate UV/X-ray pump-probe experiments for mechanistic studies of processes like isomerization and proton transfer. Publication Trends: Recent articles (2023-2025) demonstrate a strong focus on quantum algorithm development (error mitigation, amplitude estimation), tensor-network applications in quantum dynamics and biomolecular simulations, quantum hardware compilation, and fundamental studies of PT symmetry and ultracold collisions. Her work consistently integrates theoretical chemistry with quantum information science. Awards and Fellowships: American Chemical Society Kavli Emerging Leader in Chemistry Award (2023) Institute for Pure and Applied Mathematics Fellow (2021) Yale Quantum Institute Postdoctoral Fellowship (2020) National Science Foundation Graduate Research Fellowship (2014) Fulbright Fellowship (2013-2014) DAAD Graduate Scholarship (2013-2014) Beckman Scholars Fellowship (2012-2013) Phi Beta Kappa (2012) Advising and Group: She mentors graduate students from Chemistry and Physics programs, including Jingcheng Dai (Chemistry), Atharva Vidwans (Chemistry/Physics), and Henry Lin (Physics-Quantum Computing). Former advisees include Preetham Tikkireddi (Quantum Circuits Inc.) and Jaden Coles (Yale PhD). Her group explores quantum computing, tensor networks, ultracold collisions, and PT symmetry.
Babak Moaveni is a Professor in the Department of Civil and Environmental Engineering at Tufts University, serving as the Associate Chair since September 2024. He also holds a joint appointment as a Professor in Electrical and Computer Engineering. His research focuses on structural health monitoring, Bayesian inference, earthquake engineering, and offshore wind energy systems. Moaveni earned his Ph.D. in Structural Engineering from the University of California San Diego (2007), following an M.S. (2001) and B.S. (1999) from Sharif University of Technology in Tehran, Iran. His research interests span probabilistic system identification, signal processing, uncertainty quantification, and verification/validation of computational models. Notable grants include leadership in the PIRE project on offshore wind energy digital twins and the Coastal Virginia Offshore Wind Pilot Project. He has supervised multiple Ph.D. and M.S. students, with current advisees including Mehdi Akhlaghi and Nasim Partovi-Mehr. Moaveni has received the Best Presentation Award at the 2022 EDGE Symposium and serves on editorial boards for journals like Structural Health Monitoring and Frontiers in Built Environment . His lab, the Structural Health Monitoring Lab, specializes in infrastructure management and offshore wind energy systems. Key professional activities include membership in the American Society of Civil Engineers (ASCE) and roles on Tufts' Tenure and Promotion Committee. His teaching includes courses on structural health monitoring, numerical methods, and structural reliability.
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Massimo Canale is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , and a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His academic career spans over two decades, focusing on control systems engineering with applications in automotive technology. Scientific Branch: Systems and Control Engineering (IINF-04/A) ERC Sectors: Automotive Engineering, Control Engineering, Control Theory Dr. Canale's research bridges theoretical advancements in Model Predictive Control (MPC) with practical applications in autonomous vehicles , hybrid/electric propulsion , and active suspension systems . His work integrates reinforcement learning and dynamic programming for optimizing vehicle performance and energy efficiency. Recent publications demonstrate trends in autonomous driving architectures (2024), sliding mode control for highway scenarios (2024), and energy management for sustainable mobility (2023-2024). He has developed patented solutions for semi-active suspension control and autonomous vehicle guidance. Award: IEEE Transactions on Control Systems Technology Outstanding Paper Award (2011) Editorial Roles: Associate Editor, IEEE Open Journal of Control Systems (2022–present) Dr. Canale supervises PhD students like Francesco Cerrito and teaches courses on digital control technologies , automatic control , and reinforcement learning at Politecnico di Torino. His research is funded through competitive grants (e.g., MPC4AVP 2021-2022) and commercial contracts (AD Shuttle 2024).
Tommy Svensson is a Professor of Communication Systems at Chalmers University of Technology, where he leads research on wireless systems on air interface and wireless backhaul network technologies. He received his Ph.D. in information theory from Chalmers in 2003 and has extensive industry experience from Ericsson AB, working with core, radio access and microwave networks. His primary research interests include: Design and analysis of mobile communication systems Physical storage algorithms Multi-user access and resource allocation Cooperative/context-aware/secure communication mm-wave/sub-THz communication C-V2X and JCAS Satellite networks Sustainable design and comprehensive architecture Professor Svensson has been actively involved in numerous European research projects including WINNER I/II/+, ARTIST4G (contributing to 3GPP LTE standards), METIS, mmMAGIC, and 5GCar (towards 5G), and Hexa-X, RISE-6G, SEMANTIC, ROBUST-6G, and ECO-eNET (towards 6G). He also contributes to the Chase/ChaseOn and WiTECH antenna systems center of excellence at Chalmers, focusing on mm-wave and (sub)-THz solutions for various wireless scenarios. His publication record is extensive, with 6 books, 111 journal papers, 151 conference papers, and 80 public EU project deliverables to his name. Professionally, he serves as: Founding member/editor of the IEEE JSAC Series on Machine Learning in Communications and Networks Chair of the award-winning IEEE Sweden Vehicular Technology/Communications/Information Theory Societies chapter Editor of IEEE Transactions on Wireless Communications and IEEE Wireless Communications Letters Lead local organizer of EuCNC & 6G Summit 2023 Coordinator of the Communication Engineering Master's Program at Chalmers
Keith D. Koper is a Professor in the Department of Geology & Geophysics at the University of Utah and serves as Director of the University of Utah Seismograph Stations (UUSS). He is also the editor-in-chief of The Seismic Record . His work integrates academic research with operational seismic monitoring and public safety initiatives across Utah and the Intermountain West. Education: PhD in Geophysics, Washington University, 1998 BA in Math, Geology, and ISP, Northwestern University, 1993 Dr. Koper's research focuses on array seismology, forensic seismology, deep Earth structure (especially the inner core), earthquake rupture imaging, ambient seismic noise, and seismic hazards in the Intermountain West, including mining-induced and urban earthquakes. His work combines observational seismology with advanced signal processing and machine learning techniques to improve detection, discrimination, and imaging capabilities. He has led or contributed to major projects involving the Wasatch Front, Yellowstone, and regional seismic networks. His recent research emphasizes machine learning for earthquake detection, high-resolution relocation of aftershock sequences (e.g., Magna 2020, Bluffdale 2019), microseism generation in lakes, and fine-scale imaging of the Earth's inner core using seismic reflections. His studies often involve interdisciplinary collaboration, particularly with mining engineering and geodesy. Dr. Koper's research has been consistently funded by federal and state agencies, including the National Science Foundation (NSF), U.S. Geological Survey (USGS), Department of Energy (DOE), Air Force Research Laboratory (AFRL), and the Utah Department of Public Safety. His publications reflect a strong trend toward integrating computational methods with traditional seismological analysis to tackle complex problems in both natural and induced seismicity. Scientific Service and Leadership: Editor-in-Chief, The Seismic Record Director, University of Utah Seismograph Stations Secretary, U.S. Air Force Seismic Review Panel Former Chair and Vice-Chair, Utah Seismic Safety Commission Dr. Koper mentors graduate students in seismology and geophysics, including recent advisees Sean Hutchings and Alysha Armstrong. His research group actively engages in both fundamental and applied seismological research, with strong ties to national labs such as Sandia. The group is involved in deploying portable seismic arrays, analyzing large datasets, and developing new algorithms for event detection and classification. The University of Utah Seismograph Stations, under his leadership, plays a critical role in monitoring seismicity in Utah and Yellowstone, producing real-time earthquake information, ShakeMaps, and public outreach materials. The station also contributes to national and international efforts in nuclear test monitoring and volcanic hazard assessment.
