Dr. Meghdad Fazeli is a Senior Lecturer in the Department of Electronic and Electrical Engineering at Swansea University, Faculty of Science and Engineering. His research focuses on renewable energy integration, smart grids, and microgrid technologies, with a particular emphasis on virtual synchronous machines (VSM) and energy management strategies. He leads projects addressing climate change mitigation through decarbonized energy systems, aligning with UN Sustainable Development Goals 7, 11, and 13. Dr. Fazeli collaborates with National Grid ESO and colleagues across disciplines including Computer Science and Business School via the CARI initiative. He founded Innoverters-Ltd, a Swansea spin-out consultancy for future power systems innovation. His teaching uses blended learning, including MATLAB-SIMULINK integration and recorded lectures, coordinating modules like Power Systems (EG-342) and Advanced Power Systems (EGLM05). Research interests span renewable energy control, grid-forming inverters, and energy communities. Recent articles address VSM applications, peer-to-peer trading, and buffered microgrid designs. He advises PhD projects on topics like solar forecasting and grid-less power system architectures. His work emphasizes sustainable energy transitions, long-term resilience, and interdisciplinary solutions for net-zero systems.
Dao Zhou is an Associate Professor at Aalborg University's Department of Mechatronic Systems, part of The Faculty of Engineering and Science. His research focuses on power electronics reliability, wind turbine systems, and grid integration of renewable energy. He holds a PhD in Electrical Engineering from Aalborg University (2014), specializing in reliability assessment of wind turbine systems. His key research areas include power converter control strategies, semiconductor reliability, and grid-forming/grid-following inverter technologies. He has led projects such as the Physics-informed AI for Prognostics in Power Converters and the HELP laboratory platform initiative. Zhou has supervised four PhD students and authored over 198 publications, with notable awards including the IEEE ICPE 2023-ECCE Asia and MPCE 2021 Best Paper Award. Recent work emphasizes predictive maintenance via physics-informed neural networks and seamless control transitions between grid modes. His lab collaborations span Europe, focusing on improving renewable energy system reliability and educational lab infrastructure.
Dr. Maximilian Engel is an Assistant Professor (UD1, tenured) at the Korteweg-de Vries Institute for Mathematics (KdV Institute), University of Amsterdam. He concurrently leads the MATH+ Research Group on 'Random and Multiscale Dynamical Systems' at Freie Universität Berlin's Department of Mathematics and Computer Science. His research focuses on stochastic dynamics, metastability, synchronization phenomena, and applications in complex systems and machine learning theory. **Research Interests:** His work spans transient random dynamics, multi-agent systems, biochemical oscillators, and the theoretical underpinnings of deep learning. He actively collaborates on projects funded by NWO Vidi (e.g., 'Transient Random Dynamics'), MATH+, and Germany's DFG SPP 2298. **Grants & Leadership:** Principal Investigator (PI) for multiple projects including 'Metastability in Multi-Agent Systems' and 'Scaling Cascades in Complex Systems.' He oversees postdoc and PhD positions in his Vidi project. Engages in editorial roles for Physica D: Nonlinear Phenomena and organizes events like the One World Dynamics Seminar Series and SIAM Conference sessions. **Affiliations & Activities:** Maintains dual roles at UvA and FU Berlin, participates in international workshops (e.g., SIAM Conference 2025, Summer School on Random Dynamical Systems), and contributes to Dutch-German academic networks like NDNS+ and MATH+.
Dr. Abolfazl Zaraki is a Senior Lecturer in AI and Robotics at the University of Hertfordshire's Department of Computer Science, part of the School of Physics, Engineering & Computer Science. He leads the Robotics Research Group and previously held roles at Cardiff University's School of Engineering and the IROHMS Research Centre. His academic journey includes a Master's in Mechatronics from University Technology Malaysia (2010) and a PhD in Automatic Robotic and Bioengineering from the University of Pisa (2014). He has held Research Fellow positions in Italy and the UK until 2019. Dr. Zaraki's research focuses on AI-driven autonomous systems, social robotics, and assistive technologies. Key projects include the EASEL, BabyRobot, and JAMES EU initiatives, alongside the Innovate UK-funded InSight project. His work emphasizes Human-Robot Interaction (HRI), trusted autonomy, and applications in healthcare and industrial contexts. Notable contributions include the development of the Kaspar humanoid robot for autism therapy and advancements in reinforcement learning for robotic control. His recent publications (2021–2025) explore agentic AI, memory-driven systems, and personalized LLMs for HRI, alongside technical advancements in robotic control, communication systems, and bio-inspired robotics. His research bridges theoretical AI innovation with practical applications in healthcare, education, and industrial automation. Zaraki has collaborated internationally across institutions and industry partners, contributing to 35+ research outputs. His work aligns with global trends in ethical AI, explainable systems, and human-centric robotics design.
David Yau is a Professor in the Information Systems Technology and Design (ISTD) pillar at the Singapore University of Technology and Design (SUTD). He holds a B.Sc. from the Chinese University of Hong Kong and M.S./Ph.D. from the University of Texas at Austin, all in Computer Science. Previously, he was Distinguished Scientist at the Advanced Digital Sciences Center (ADSC) in Singapore and Qiushi Chaired Professor at Zhejiang University, China. His research focuses on network security, cyber-physical systems, and smart grid resilience. He has led over 15 research projects funded by agencies like Singapore's NRF, A*Star, and the U.S. NSF. Notable awards include the IBM Fellowship, NSF CAREER Award, and Best Paper awards at IPSN 2017 and IEEE MFI 2010. Yau has advised numerous PhD/Master’s students, many now in academia and industry. His work spans secure protocols, intrusion detection in critical infrastructures, and privacy-preserving smart grid technologies. He has authored over 100 peer-reviewed publications and served on editorial boards of ACM Transactions on Sensor Networks and IEEE journals.
Dr. Yuanhong Chen is a Postdoc Researcher at the Australian Institute for Machine Learning (AIML) within the University of Adelaide's Division of Research and Innovation. His work focuses on advancing computer vision, multimodal learning, and generative models, particularly in medical image analysis and audio-visual perception. He explores integrating large language models for cross-modal understanding to enhance AI systems' interpretability and robustness. Research interests include: Interpretable AI frameworks for medical imaging Semi-supervised and self-supervised learning techniques Audio-visual contextual learning and binaural audio generation Applications in breast cancer screening and disease classification Recent publications highlight innovations in prototype-based learning for medical diagnosis, cross-modal segmentation, and unsupervised anomaly detection. His work on Braix risk score and AutoCumulus demonstrates contributions to automated medical biomarker development. Collaborations within AIML and interdisciplinary projects at the University of Adelaide underscore his commitment to bridging foundational AI research with real-world healthcare applications.
William Howe is an Assistant Professor at the School of Neuroscience, Virginia Tech, where he joined in Fall 2019. He earned his Ph.D. in Neuroscience from the University of Michigan under Martin Sarter, followed by industry experience at Pfizer and postdoctoral training at the Icahn School of Medicine at Mt. Sinai with Paul Kenny. Education : Ph.D. University of Michigan His research focuses on neurobiological mechanisms underlying reward learning, motivation, and executive control, particularly how dysregulation in orexin, cholinergic, and dopaminergic systems contributes to neuropsychiatric and neurodegenerative disorders. His lab employs multidisciplinary methods, including optogenetics, viral gene manipulation, and optical neural activity measurement. Recent publications highlight his work on nicotine addiction, depression, and attention resilience, with trends spanning cholinergic signaling, striatal networks, and gene-editing applications. Key journals include Nature , Nature Neuroscience , and Current Biology .
Francesco Picariello is a Researcher at the Department of Engineering (DING) at the University of Sannio, specializing in Electrical and Electronic Measurements (ING-INF/07). His academic profile shows extensive expertise in measurement systems, data acquisition, and signal processing with applications across multiple domains including biomedical engineering, structural health monitoring, and wireless communications. His research interests focus on the design, implementation, and metrological characterization of mobile measurement systems, wireless sensor networks, data acquisition systems based on compressed sensing, signal processing, and image processing. These research activities have been applied to intelligent transportation systems, aerial photogrammetry using UAVs, indoor navigation, motion tracking, power consumption analysis of processors, wideband data acquisition systems, and physiological monitoring applications. Dr. Picariello's work demonstrates significant trends in compressive sampling techniques, with numerous publications on ECG signal processing, RF emitter localization, and structural health monitoring systems. His research shows a clear progression toward IoT integration, wearable medical devices, and security applications for communication channels. His scientific collaborations include institutions such as the University of Naples 'Parthenope', Military University of Technology of Warsaw, National Institute of Standards and Technology (NIST), Keysight Laboratories, CERN Institute, and the University of Tokyo, reflecting the international recognition of his work. As an active researcher with publications spanning from 2016 to 2025, Dr. Picariello has made substantial contributions to measurement science, particularly in the development of novel techniques for data acquisition, signal processing, and system metrological characterization across multiple application domains.
Linda Olafsen is an Associate Professor in the Department of Electrical & Computer Engineering at Baylor University’s School of Engineering and Computer Science. She holds a PhD in Physics from Duke University and has held academic positions at the University of Kansas and Baylor University since 1999. Her research spans photonics, semiconductor optoelectronics, and biomedical device development. PhD, Physics, Duke University (1997) MA, Physics, Duke University (1994) AB, Physics, Princeton University (1991) Her research focuses on mid-infrared semiconductor lasers, optoelectronic devices, graphene-semiconductor integration, and biomedical applications such as endovascular navigation and glucose monitoring. She leads the Semiconductor Optoelectronics Laboratory, where her team develops advanced mid-IR lasers, characterizes 2D/3D material interfaces, and engineers sensors for medical use. Her work bridges fundamental physics with practical engineering solutions in healthcare and defense. The recent publications show a strong trend toward mid-infrared optoelectronics , particularly interband cascade lasers , graphene-based contacts , and biomedical sensing . Her team integrates optical, thermal, and electrical characterization to improve laser efficiency and device performance. Applications span infrared countermeasures, chemical sensing, and endovascular robotics. Scientific Awards and Professional Leadership: Chair, Congressional Visit Day Subcommittee, MRS (2012–2016) Chair, Policy Outreach Working Group, MRS Government Affairs Committee Book Review Board Chair, MRS Bulletin Editorial Board Member, MRS Bulletin Lifetime Member, American Physical Society, OSA, and SPIE Senior Member, IEEE and IEEE Photonics Society Linda Olafsen actively mentors undergraduate and graduate students, involving them in research on laser development, material characterization, and biomedical device design. She has secured funding for projects in mid-IR lasers and sensing technologies. Her lab offers opportunities in device fabrication, graphene integration, beam profiling, and LabVIEW programming. She leads the Semiconductor Optoelectronics Laboratory , which focuses on: Mid-infrared semiconductor laser development Graphene-semiconductor optoelectronic devices Endovascular navigation using shape-memory alloys In vivo infrared and ultrasound sensing Beam and thermal profiling Device fabrication and characterization
Dr. Enrique Blair is an Associate Professor in the Department of Electrical and Computer Engineering at Baylor University, where he has served since 2015, advancing to his current rank in 2021. His academic journey includes prior roles as a Military Instructor at the U.S. Naval Academy and service in the U.S. Navy submarine force. He is actively engaged in research, teaching, and mentoring within the College of Engineering. His research focuses on the theoretical and computational aspects of quantum engineering, particularly in quantum-dot cellular automata (QCA), open quantum systems, and quantum information sciences. He explores molecular computing paradigms, quantum decoherence, and the quantum mechanical basis of olfaction, aiming to develop ultra-dense, low-power nanoelectronic devices and novel quantum technologies. His interdisciplinary work bridges electrical engineering, physics, chemistry, and materials science. The recent articles highlight a strong trend in molecular QCA design, quantum simulation for NISQ devices, and the application of ab initio methods to understand counterion effects and molecular stability. His research increasingly integrates machine learning for material discovery and emphasizes robustness in quantum circuits against environmental noise and external fields. The publications reflect a consistent focus on foundational quantum phenomena with practical applications in computing, sensing, and security. Research Grant, Office of Naval Research, Code 312 Nanoscale Computing Devices and Systems (May 2020 - May 2023) Summer Sabbatical, Baylor University (Summer 2019) Senior Member, IEEE (2019) Outstanding Faculty Award (untenured, tenure-track faculty), Baylor University (2018) Proposal Development Award, Office of the Vice Provost for Research, Baylor University (2017) Rising Star Program, Baylor University (2017-2018) Undergraduate Research and Scholarly Achievement Award, Office of the Vice Provost for Research, Baylor University (2017-2018) Rising Star Program, Baylor University (2016-2017) Graduate Research Fellowship Program, National Science Foundation (2010-2015) National Defense Science and Engineering Graduate Fellowship, American Society for Engineering Education (2010-2013) Dr. Blair has advised multiple Ph.D. and Master’s students, including Colin Burdine, Nischal Gautam, and Nishat Liza, and has mentored numerous undergraduate researchers. His research is supported by competitive grants, particularly from the Office of Naval Research, reflecting the strategic importance of his work in nanoscale computing. He integrates teaching and research, offering courses such as Quantum Mechanics for Engineers and Introduction to Quantum Computing, and promotes scholarly productivity through tools like Emacs Org Mode and LyX. He leads an active research team focused on molecular QCA and quantum information, with current members including Ph.D. students and undergraduates. The team conducts simulations, theoretical modeling, and design of quantum devices, contributing to advancements in nanoelectronics and quantum computing. Collaborations with experts in chemistry, physics, and computer science further extend the impact of the research.
Franceschiello Benedetta is an Associate Professor at HES-SO Valais-Wallis School of Engineering, specializing in Technical and IT disciplines. She holds a PhD in Mathematical Neuroscience from Université Pierre et Marie Curie (Paris). Her work bridges applied mathematics, computational neuroscience, and neuroimaging, with a focus on visual perception modeling, MRI techniques, and neural dynamics. Teaching: Linear Algebra courses across multiple engineering bachelor programs Expertise: Combines mathematical modeling with neuroscientific applications to study optical illusions, brain connectivity, and ophthalmic diagnostics Key Affiliations: ISMRM, Organization for Human Brain Mapping (OHBM), Association for Research in Vision and Ophthalmology (ARVO) Research Interests: Computational modeling of visual cortex mechanisms underlying geometric optical illusions Development of MRI-based methods for eye structure segmentation and axial length estimation Analysis of brain network reliability through standardized MRI protocols Optimization techniques for medical imaging reconstruction (e.g., weighted LASSO problems) Recent Work Trends: Focus on integrating psychophysical experiments with computational models to elucidate perceptual mechanisms, emphasizing synergistic interactions between physical stimulus parameters. Active in advancing MRI applications for both clinical diagnostics and fundamental neuroscience research.
Wouter van Toll is a Lecturer at the Academy for AI, Games & Media, specializing in crowd simulation and real-time systems. His research focuses on path planning, crowd behavior modeling, and fluid dynamics in agent-based simulations. He has contributed to advancing algorithms for microscopic crowd simulation and integrating techniques like Smoothed Particle Hydrodynamics (SPH) to handle extreme crowd densities. Key research interests include sketch-based interaction design for steering behaviors, navigation mesh optimization, and topological strategies for agent coordination. His work bridges computational methods with creative applications in game development and artificial intelligence. Received Best Paper Award Honorable Mention (2022) for his work on sketch-based steering behaviors in crowd simulation. Active collaborations in Europe and North America, particularly in crowd simulation software development. Publications span algorithmic advancements in crowd simulation, navigation systems, and interdisciplinary applications combining physics-based methods with agent-based models. Current research emphasizes real-time simulation efficiency and human-centered design tools for behavior specification.
Arpan Gujarati is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Systopia Lab. His research focuses on real-time systems, distributed systems, fault tolerance, and reliability analysis in cloud and cyber-physical systems domains. He holds a PhD from the Max Planck Institute for Software Systems (MPI-SWS) and has postdoctoral and research experience at MPI-SWS and UBC. Education: PhD in Real-Time Systems (MPI-SWS/TU Kaiserslautern, 2020), Postdoctoral Researcher at MPI-SWS (2020), Research Associate at UBC (2022–2023), B.Sc. from Birla Institute of Technology and Science (BITS Pilani, India). Research interests include distributed real-time systems, reliability analysis of cloud applications, fault-tolerant machine learning, and scheduling algorithms. His work bridges theory and practice, addressing challenges in ultra-reliable CPS and resilient distributed systems. Awards: Best Dissertation Award (SIGBED, 2020), Best Paper Awards (RTSS 2022, ECRTS 2018), Distinguished Artifact Award (OSDI 2020). Advising: Supervises PhD and undergraduate students in distributed systems and resilience engineering. Active in UBC’s Computer Science Graduate Program, teaching courses like CPSC 416 (Distributed Systems) and CPSC 538G (Topics in Computer Systems). Labs/Teams: Leads the Systopia Lab, collaborating with industry partners on projects like robotic arm datasets and self-driving lab tools (RABIT). Involved in research groups focused on machine learning resilience and real-time systems.
Cassandra Hart is a Professor of Education Policy at the University of California, Davis, School of Education . She evaluates the impacts of school, state, and national education programs on student achievement and equity in outcomes. Ph.D., Human Development and Social Policy, Northwestern University (2011) Master of Public Policy, University of Chicago (2006) Bachelor of Science in Foreign Service, Georgetown University (2002) Her research focuses on school choice programs , school accountability policies , early childhood education , and the demographic alignment of teachers and students . She also examines virtual schooling effects in K-12 and post-secondary settings. Recent work includes studies on community college responses to the pandemic , online instructor training , and student performance in asynchronous vs synchronous courses . Key findings show that Black students matched with Black teachers are less likely to be incorrectly identified for special education services and more likely to graduate and attend college. Scientific awards include the Outstanding Reviewer Award (2024) and Thomas A. Downes Award (2019). She has received grants from the Spencer Foundation , Institute of Education Sciences , and Arnold Ventures for online education research. Hart serves as Co-Editor of Education Finance and Policy (2023–present) and holds affiliations with the UC Davis Center for Poverty and Inequality Research , California Education Lab , and Wheelhouse: Center for Community College Leadership .
Chris Brace is a Professor of Automotive Propulsion and Deputy Director of the Powertrain Vehicle Research Centre at the University of Bath. His work focuses on advanced measurement, analysis, and control of multi-cylinder engine systems under dynamic conditions, with extensive collaboration with industry leaders like Ford Motor Company and Jaguar LandRover. He contributes to the United Nations Sustainable Development Goals (SDGs), particularly in sustainable mobility and low-emission propulsion systems. Education : Sandwich degree at University of Bath (1990), PhD (1996). Research interests encompass powertrain systems , internal combustion engines , hybrid electric vehicles , battery technology , and low-emission propulsion . His projects integrate nonlinear control systems, fault-tolerant designs, and data-driven validation architectures. Recent publications highlight advancements in emission control algorithms, adaptive critic networks for rotary engines, fault-tolerant motor control, and battery parameter modeling. These works reflect trends in automotive electrification , hybrid systems , and environmental sustainability . Supervision : Supervised PhD research on hybrid electric vehicle control strategies (Christopher Vagg, 2015). Grants & Projects include Innovate UK-funded initiatives like Battery Integrated Wing (2025–2028) and EPSRC-supported JLR Prosperity Partnership (2021–2026). He also leads the IAAPS Institute for Advanced Automotive Propulsion Systems. Key Collaborations : Ford Motor Company, Jaguar LandRover, West of England Combined Authority.
