Mikael B. Skov is a Vice Dean and Professor at the Technical Faculty of IT and Design of Aalborg University , Denmark. His research spans human-AI interaction, robotics, and user experience, with a focus on trust signaling in clinical AI, swarm robotics, and sound zones for domestic environments. Role: Vice Dean for Research Department: Computer Science Research Interests: Skov investigates how humans interact with AI and robots in healthcare and domestic settings, emphasizing trust calibration, alert design, and acoustic comfort. His work includes developing frameworks for UX maturity in robotics organizations and studying long-term adoption of sound zone systems. Recent Projects: As principal/co-investigator, he leads the HERD project on human-AI collaboration in robot swarms (2021–2025) and supervises Data og Bæredygtig Mad (2020–2023), an HCI perspective on sustainable food systems. Publications: His 2024 work includes studies on AI explanations in clinical training, music applications with intermittent interactions, and multi-robot supervision. Earlier projects (2001–2020) focused on mobile device usability, UX practices, and context-aware computing.
Sean Carroll serves as the Homewood Professor of Natural Philosophy at Johns Hopkins University and holds External Faculty status at the Santa Fe Institute. His research bridges cosmology, quantum mechanics, and philosophy, focusing on foundational questions about spacetime emergence, quantum interpretation, and complexity across cosmic scales. Carroll earned his Ph.D. from Harvard University in 1993. His academic trajectory reflects deep engagement with theoretical physics and philosophical inquiry, culminating in his current named professorship at Johns Hopkins. Carroll's research centers on the intersection of physics and philosophy, with significant contributions to quantum foundations, cosmology, and the nature of emergence. He is a leading proponent of the many-worlds interpretation of quantum mechanics and has pioneered work on the thermodynamic arrow of time, quantum decoherence, and the fine-tuning of initial cosmic conditions. His recent investigations explore discretized quantum systems, holographic principles in gravity, and the philosophical implications of quantum gravity. Analysis of his 2022-2025 publications reveals a pronounced shift toward computational approaches in quantum gravity, with increasing emphasis on finite-dimensional Hilbert spaces and GPU-accelerated modeling. His work consistently integrates quantum information theory with cosmological questions, particularly examining how spacetime geometry emerges from quantum entanglement and how complexity evolves in closed systems. Carroll's scientific recognition includes: National Science Foundation Fellowship NASA Fellowship Sloan Research Fellowship Packard Fellowship Fellow of the American Physical Society American Institute of Physics Award Fellow of the Royal Society Guggenheim Fellowship Fellow of the American Association for the Advancement of Science His research has been sustained through major fellowships from NSF, NASA, Sloan, and Packard foundations, enabling interdisciplinary collaborations across physics and philosophy. Carroll actively mentors graduate students at Johns Hopkins and contributes to public discourse through his popular science books (including the Biggest Ideas in the Universe series) and the weekly Mindscape podcast. As Fractal Faculty at the Santa Fe Institute, Carroll participates in cross-disciplinary research on complex systems, exploring how emergent phenomena arise from fundamental physical laws. His work bridges theoretical physics with broader questions about complexity in biological, cognitive, and social systems.
Axel Gandy is a Professor of Statistics at the Department of Mathematics, Imperial College London. He serves as Director of the EPSRC CDT in Modern Statistics and Statistical Machine Learning , overseeing PhD supervision and advanced statistical training.
James C. Gumbart is an Adjunct Professor in the School of Physics at Georgia Institute of Technology, with additional affiliation to the School of Chemistry and the Institute for Bioengineering and Bioscience . His research leverages molecular dynamics simulations to decode the atomic-level mechanisms of bacterial proteins and cellular structures. B.S., Physics and Mathematics, Western Illinois University, 2003 Ph.D., Physics, University of Illinois at Urbana Champaign, 2009 Dr. Gumbart's work bridges computational biophysics and biochemistry to understand: Mechanisms of bacterial membrane protein insertion and nutrient import Structural dynamics of cell wall mechanics SARS-CoV-2 spike protein interactions with ACE2 Free-energy calculations for protein-ligand binding Applications of machine learning in biomolecular simulations His publications reflect trends in membrane protein biophysics , viral dynamics , and computational drug design , with a strong emphasis on interdisciplinary techniques. Awards include multiple fellowships and grants from NSF , DOE , and NIAID . He has mentored numerous PhD students, including Zijian Zhang , David Ryoo , and Andrew Pang , whose work has advanced understanding of bacterial systems and viral proteins. The Gumbart Lab integrates high-powered supercomputing and advanced software to model biomolecular processes, fostering collaborations with institutions like the National Institutes of Health and Argonne National Laboratory .
Michael John Janik is a Professor in the Department of Chemical Engineering at Pennsylvania State University, with significant affiliation to the Institute of Energy and the Environment (IEE). His academic profile demonstrates exceptional research productivity with 270 research outputs, 25 funded projects, and substantial scholarly impact reflected in 17,238 citations and an h-index of 61. His research expertise centers on computational chemistry with particular focus on Density Functional Theory applications to catalysis and electrocatalysis. The fingerprint analysis of his work reveals strong concentrations in Density Functional Theory (76%), Oxidation Reactions (36%), Carbon Dioxide research (29%), Adsorption phenomena (27%), and First Principles Chemistry (22%). His work significantly contributes to UN Sustainable Development Goals related to clean energy and climate action. Analysis of his recent publications (2020-2025) reveals a strong research trajectory in electrocatalysis, particularly examining cation effects on CO 2 reduction mechanisms, intermetallic catalyst design, and computational modeling of electrochemical systems. His work bridges fundamental computational chemistry with practical applications in sustainable energy conversion. h-index of 61 17,238 total citations Multiple high-impact publications in journals including Nature Catalysis, Journal of the American Chemical Society, and Science Advances Professor Janik actively leads and collaborates on numerous research projects, particularly with Dr. Rioux and other colleagues, focusing on advanced catalyst development and electrochemical energy conversion systems. His current research portfolio includes multiple active NSF-funded projects extending through 2027 that address critical challenges in electrocatalysis, CO 2 reduction, and intermetallic catalyst design. His research group maintains strong connections with the Institute of Energy and the Environment, positioning his work at the intersection of fundamental computational chemistry and applied energy solutions. Current projects include combining DFT with classical simulations to predict solvation effects, developing high-entropy alloys for catalysis, and studying oxide overlayers in CO 2 reaction systems.
Mark D. Hill is a Professor at the University of Wisconsin—Madison, renowned for transformative contributions to computer architecture spanning memory systems and parallel computing. His work earned the ACM-IEEE CS Eckert-Mauchly Award in 2019 and ACM Fellowship in 2004. Hill pioneered the 3C model for cache misses, SC for DRF memory consistency (with Sarita Adve), and transactional memory via LogTM (with David Wood). His simulation frameworks—Dinero, GEMS, gem5, and BadgerTrap—enable advanced analysis of memory behavior and virtual systems, while concepts like 'page reservation' directly impact Linux kernel design. Research spans cache optimization, heterogeneous processor memory models, and scalable parallel evaluation techniques. Hill's accolades include: ACM-IEEE CS Eckert-Mauchly Award (2019) for contributions to memory systems and parallel computer design/evaluation ACM Fellow (2004) for innovations in memory consistency models and memory system architecture With over 160 co-authors and 20,000+ citations, Hill mentored influential researchers like Sarita Adve. His grant-supported projects—including the Wisconsin Wind Tunnel simulator—produced industry-adopted tools cited thousands of times, driving real-world implementations in programming languages and operating systems. Hill leads critical research initiatives at Wisconsin, developing the Dinero cache simulator, GEMS/gem5 full-system simulators, and BadgerTrap virtual memory analyzer. These projects underpin modern architecture research and continue to evolve for emerging heterogeneous computing challenges.
Irina Oleinikova is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Electric Energy, Faculty of Information Technology and Electrical Engineering. She leads the Power System Operation and Analysis research group and serves as the NTNU Smart Grid Team Leader. She is a steering committee member of the European Energy Research Alliance (EERA) Joint Programme on Smart Grids and an expert in the International Smart Grid Action Network (ISGAN) WG6. Research Interests : Power System Operation, Digital Power System Protection and Control, Grid Resilience, Energy Flexibility, Cybersecurity in Power Systems, and Hydrogen Technology Integration. Her work focuses on advancing smart grids, grid flexibility, and cybersecurity through projects like FME CINELDI, HONOR, ASAP, and ZeroKyst. Key Projects : CINELDI : Developing intelligent electricity distribution grids. HONOR : Cross-sectoral energy flexibility markets. ASAP : Next-generation system protection schemes. ZeroKyst : Hydrogen and charging infrastructure along Norway’s coast. COSPAT : Stability of AC/DC transmission grids via co-simulation. Advising & Grants : Supervises PhD students in digital protection and cybersecurity. Active in projects funded by RCN, STATNETT, and EU Horizon 2020. Leads the Power System Operation and Analysis group and collaborates with SINTEF and industry partners. Labs/Teams : NTNU Smart Grid Team and the Power System Operation research group.
Thomas Demeester is an Associate Professor at the Internet Technology and Data Science Lab (IDLab), Ghent University - imec, Belgium. Appointed as Assistant Professor in 2019, he leads an AI research group focused on health applications and drug design, co-directing the Text-to-Knowledge research cluster with Prof. Chris Develder. His educational background includes: M.Sc. in Electrical Engineering from Ghent University (2005), completed with thesis work at ETH Zurich Ph.D. in Computational Electromagnetics from Ghent University (2009), funded by Research Foundation - Flanders (FWO) Demeester's research spans artificial intelligence with emphasis on deep learning and neuro-symbolic methods. Current tracks include energy-based models (Hopfield Networks, Deep Equilibrium Models), diffusion models for drug design, and clinical reasoning systems. His work bridges NLP, healthcare informatics, and generative AI with strong industry partnerships. Recent publications (2023-2025) reveal strategic expansion from NLP into health-centric AI: BioLORD biomedical encoders (2023), synthetic medical data frameworks (UAI/NeurIPS 2024), and novel diffusion model guidance (ICLR 2025). This evolution demonstrates convergence of generative modeling, clinical data analysis, and protein design. He actively mentors 24 PhD students across diverse AI domains: Current Research: Conversational agents, emotion analysis, clinical reasoning, antibody design, and diffusion model optimization Recent Graduates: Interpretable language models, biomedical semantics, task-oriented dialogue, and social media knowledge extraction Research is supported by imec funding and collaborations with Flemish biotech companies, building on his post-doctoral experience securing media-sector projects. Within IDLab, he co-leads the Text-to-Knowledge cluster driving NLP innovations for healthcare, legal, and economic applications.
Dr. Karim El-Basyouny is a Killam Laureate Professor and City of Edmonton Urban Traffic Safety Research Chair at the University of Alberta's Faculty of Engineering, where he serves as Associate Dean (Research Infrastructure and Innovation) in the Civil and Environmental Engineering Department. A licensed Professional Engineer in Alberta, he holds advanced degrees in Transportation Engineering from the University of British Columbia and has dedicated his career to advancing road safety through data-driven management frameworks. His academic credentials include: Doctor of Philosophy, Civil Engineering, University of British Columbia, 2011 Engineering Management Sub-specialization, Civil Engineering, University of British Columbia, 2010 Master of Applied Science, Civil Engineering, University of British Columbia, 2006 Bachelor's degree (ABET Equivalent), Civil & Environmental Engineering, United Arab Emirates University, 2003 El-Basyouny's research pioneers the integration of remote sensing, machine learning, and statistical modeling to enhance transportation safety. His work develops automated tools for infrastructure digitization, collision prediction, and speed management, treating safety as a systemic product requiring management frameworks. Key contributions include LiDAR-based road feature extraction, network-level safety evaluations, and frameworks for vision-zero outcomes that address both human-driven and autonomous vehicle contexts. His recent publications demonstrate a cohesive research trajectory centered on leveraging point cloud data and computational intelligence for safety management. Over 15 major publications since 2021 focus on automated infrastructure assessment (light pole detection, clear zone mapping, vertical clearance evaluation), weather-impact modeling, and enforcement resource optimization. This body of work bridges transportation engineering with computer vision and operations research to create scalable safety solutions. His scientific contributions have been recognized with prestigious honors including: 2024 Killam Annual Professorship Award 2024 Road Safety Achievement Award from TAC 2023 Donald Stanley Award for environmental engineering 2022 Faculty of Engineering Graduate Teaching Award 2021 Daniel B. Fambro Student Paper Award As an academic leader, El-Basyouny actively mentors graduate students and secures significant research funding through his endowed chair position. He currently recruits fully-funded PhD and postdoctoral candidates specializing in remote sensing applications, machine learning, and geomatics for road digitization projects. His research group collaborates with national safety committees and municipal agencies to translate findings into policy, while he serves on editorial boards for Transportation Research Record and Analytic Methods in Accident Research. The research group operates at the intersection of transportation engineering and computational science, developing automated frameworks that merge sensor technologies with data processing tools. Current projects focus on semantic segmentation of 3D point clouds, safety implications of infrastructure digitization, and machine learning applications for road feature extraction in both urban and rural environments.
Laureate Professor Behdad Moghtaderi is a globally recognized chemical engineer at The University of Newcastle's School of Engineering. He leads research in clean energy technologies, including the GRANEX heat engine, greenhouse gas abatement, and chemical looping processes. His work addresses critical challenges in energy efficiency, renewable energy systems, and reducing fugitive methane emissions from coal mines. With over $48M in research funding and 220+ publications, he directs the Newcastle Institute for Energy and Resources (NIER) and holds leadership roles in national and international energy initiatives. Education: PhD (University of Sydney), MEng (University of Sydney), BSc (Shiraz University) Administrative Roles: Director of NIER, former Head of School of Engineering, and member of global energy advisory bodies Research interests span energy systems, combustion science, and sustainable technologies. Notable innovations include the VAMCO system for methane abatement and solar thermal GRANEX installations. Awards include the Carrick Teaching Citation and multiple engineering excellence recognitions. Scientific contributions include 14 PhD completions and over 20 funded projects. Current focus areas include hydrogen safety, carbon capture, and thermochemical energy storage. His labs (NIER) collaborate with industry partners like Siemens Energy and the Australian Hydrogen Council.
Professor Gregor Verbic is a faculty member at the University of Sydney in the School of Electrical and Computer Engineering , where he serves as Director of the Centre for Future Energy Networks . Previously, he held an assistant professor position at the University of Ljubljana and was a NATO-NSERC Postdoctoral Fellow at the University of Waterloo. His career spans academic research, industry leadership as Head of Interenergo's Investment Department, and extensive collaboration with IEEE. PhD in Electrical Engineering (University of Ljubljana) Senior IEEE Member Research Interests focus on transforming power systems to zero-carbon grids through: Aggregation and control of distributed energy resources (DERs) Frequency control with wind generation and electric vehicles Stochastic optimization for multi-energy systems Smart home energy management with phase change materials Notable Contributions include: 2006 IEEE prize paper for voltage instability prediction 2010-2024: 15 recent publications on DER coordination, network tariffs, and low-inertia grid stability Teaching includes courses on: ELEC3203/ELEC9203: Electricity Networks ELEC5213: Engineering Optimisation ELEC5206: Sustainable Energy Systems Labs & Initiatives Centre for Future Energy Networks The Net Zero Institute
Pelin Berik Giwa is a Lecturer in the Department of Mechanical and Aerospace Engineering at the University of Central Florida (UCF). She holds a doctorate in mechatronics engineering from Johannes Kepler University and a Diplom degree in mechanical engineering from Vienna University of Technology. Her postdoctoral research spanned California State University, North Carolina State University, and Virginia Tech, with visiting roles at UCLA and Loyola Marymount University. Education : Ph.D., Mechatronics Engineering, Johannes Kepler University Diplom, Mechanical Engineering, Vienna University of Technology Research Interests : Focuses on piezoelectric actuators, nanotechnology applications in aerospace, and vibration control in aerospace structures. Her work integrates experimental benchmarking, finite element simulations, and material characterization to advance smart materials and actuator designs. Article Trends : Her publications emphasize piezoelectric crystal actuation, shear-mode sensors, and lead-free materials. Key themes include torsional actuation, nonlinear response analysis, and material optimization for aerospace applications. Awards : Erwin Schrödinger Fellowship, Austrian Academy of Sciences Max Kade Fellowship Teaching & Advising : Instructs courses like Engineering Analysis – Dynamics and Modeling Methods in MAE. While no formal advisees are listed, her roles reflect mentorship in academic and postdoctoral settings.
Max Lau is an Assistant Professor in the Department of Biostatistics and Bioinformatics and the Department of Epidemiology at Emory University. His research focuses on integrating machine learning and computational methods with epidemiological and genomic data to study infectious disease dynamics. He teaches courses such as BIOS 790R (Advanced Seminar in Biostatistics) and DATA 534 (Applied Machine Learning). Dr. Lau's work emphasizes scalable Bayesian inference, graph neural networks, and stochastic modeling to address challenges in disease transmission, outbreak control, and pathogen evolution. His recent research includes developing tools like ScITree and Epilearn, and he has contributed to understanding measles dynamics, tuberculosis treatment, and livestock disease management. His academic contributions span over 30 publications since 2010, with a particular focus on phylodynamics, epidemic modeling, and vaccine strategy evaluation. His interdisciplinary approach bridges computational methods with public health applications, aiming to enhance disease prediction and intervention efficacy.
Oussama Damen is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering. His research focuses on advanced wireless communication systems, particularly in MIMO (Multiple-Input Multiple-Output) systems, signal processing, and machine learning applications in telecommunications. He is actively involved in developing innovative solutions for beamforming, hybrid precoding, and distributed decoding in massive MIMO and millimeter-wave networks. Damen's work also extends to optical fiber communication, federated learning in wireless systems, and optimization of resource allocation in next-generation networks like 5G/6G. His research interests include wireless communication theory, antenna system design, channel modeling, and algorithm development for improving spectral and energy efficiency. He has contributed extensively to the theoretical foundations of MIMO detection, lattice reduction techniques, and statistical signal processing methods. Notable trends in his publications emphasize bridging theoretical performance limits with practical implementations, particularly in scenarios involving channel impairments, limited backhaul capacity, and multi-core fiber transmission. His work often addresses fairness and optimization in distributed systems, including federated learning frameworks and hybrid beamforming architectures. No scientific awards or grants are explicitly mentioned in the provided information. Damen has advised no listed students, and no specific lab affiliations are noted.
Mustafa Yavuz is a Professor and Director of the Nano and Micro Systems Lab (NMSL) at the University of Waterloo, Canada, affiliated with Mechanical & Mechatronics Engineering, System Design Engineering, and Electrical & Computer Engineering. He holds cross-appointments in multiple departments and has been a faculty member since 2009. His research focuses on Opto-Nano/MEMS devices, quantum electronic solids, graphene, and superconductors. Yavuz has supervised over 28 graduate students and postdoctoral fellows, leading to impactful contributions in sensors, nanomaterials, and energy harvesting. He has authored/co-authored numerous articles and holds patents in MEMS and nanotechnology. His awards include the University of Waterloo Research Excellence Award (2018) and international fellowships from MINATEC and JSPS. Education: Ph.D. Materials Engineering (University of Wollongong, 1996) Ph.D. Applied Physics (University of Wollongong, 1995) M.Sc. Materials Engineering (Middle East Technical University, 1991) B.Sc. Materials Engineering (Middle East Technical University, 1989) Research Interests: Yavuz specializes in advanced materials and MEMS/NEMS technologies, including opto-nano-MEMS devices, quantum electronic solids (superconductors, graphene), and functional nanomaterials for sensors and energy systems. His work integrates fabrication, packaging, and reliability testing of nanoscale devices for applications in photonics, biomedical sensing, and environmental monitoring. Recent trends in his articles highlight innovations in resonant MEMS mirrors, graphene-based biosensors, and laser-functionalized 2D materials. Scientific Awards: MINATEC Fellowship (2019) Waterloo Engineering Research Excellence Award (2018) International Nanoarchitectonics Fellowship (2017) JSPS Fellowship (2007) Advising & Grants: Yavuz has supervised 26 doctoral students and 28 postdoctoral researchers. His labs, including the NMSL and BioGraph Sense Inc., focus on MEMS packaging, nanojoining, and plasmonic biosensors. He has led projects funded by NSERC, CFI, and industry collaborations with companies like Apple, Samsung, and Smarter Alloys. Labs/Teams: Director of the Nano and Micro Systems Lab (NMSL), co-founder of BioGraph Sense Inc., and collaborator in the Waterloo Institute for Nanotechnology (WIN). His research group develops cutting-edge nanoscale devices with applications in healthcare, energy, and environmental sensing.
