Mojtaba Ahmadi is a Professor in the Department of Mechanical and Aerospace Engineering at Carleton University, cross-appointed within the Faculty of Engineering and Design. He holds a B.Sc. from Sharif University, an M.Sc. from the University of Tehran, and a Ph.D. from McGill University. His research focuses on robotics, mechatronics, and control systems with applications in rehabilitation, aerospace, and biologically inspired systems. Key areas include robotic locomotion, real-time control, and neuromorphic computing. He has contributed to advancements in FPGA-based neural network implementations, memristor circuits, and soft actuators. Dr. Ahmadi has served on technical committees for conferences such as CA2008, ICA2009, and CSME 2008, and organized special sessions on control applications. His work bridges theoretical models with practical hardware solutions, emphasizing interdisciplinary approaches. Publications span topics from spiking neural networks and neuromorphic vision systems to low-resource digital neuron implementations. He actively explores applications in healthcare robotics and energy-efficient computing architectures.
Peyman Mirtaheri is a full Professor of Biomedical Engineering at Oslo Metropolitan University's Faculty of Technology, Art and Design, leading the NIRS/optical lab established in 2009. He holds an adjunct professorship at Michigan Technological University's Biomedical Engineering department. His research focuses on developing novel sensor technologies for brain activity detection and applying fNIRS/EEG to study motion and balance in the cerebral cortex. As PI, he oversees major projects like PACER (RCN-funded), MgSafe (Horizon 2020), and Future Running Shoes (IP-N collaboration with Gaitline AS). He teaches medical sensors and actuators in the ACIT master's program and leads the ADEPT research platform integrating health intelligence and brain-inspired technologies across multiple faculties. Education details are not explicitly listed in the provided texts, but his academic roles imply advanced credentials in biomedical engineering. His research spans interdisciplinary domains including neurotechnology, wearable sensors, and clinical applications of brain monitoring. Over 70 publications demonstrate expertise in fNIRS signal processing, neuromorphic computing, and user-centered biomedical design. Professional networks include active Twitter (@PMirtaheri) and LinkedIn profiles. Current projects emphasize translational research and ethical design considerations in neurotechnology. His work bridges engineering, health sciences, and arts through collaborative platforms like ADEPT, addressing both technical innovation and societal impact.
Fei Wang is a Professor and Condra Chair of Excellence in Power Electronics at the University of Tennessee, Knoxville (UTK), affiliated with the Tickle College of Engineering and the Min H. Kao Department of Electrical Engineering and Computer Science. He serves as Technical Director of CURENT and holds a joint appointment at Oak Ridge National Lab. His expertise spans power electronics converters, motor drives, wide bandgap devices, and renewable energy systems. Education: B.S. in Electrical Engineering, Xi’an Jiaotong University, 1982 M.S. and Ph.D. in Electrical Engineering, University of Southern California, 1985 and 1990 Research Interests: Focuses on design, modeling, and control of advanced power electronics systems, including grid integration of renewable energy, electric vehicle drivetrains, and wide bandgap semiconductor applications. He has authored over 500 publications and holds 20 patents, with funding exceeding $65M and personal share over $18M. Key Contributions: Developed three-level NPC medium voltage drives at GE Co-founded CURENT and led its technical strategy Recipient of IEEE IAS Gerald Kliman Innovator Award (2018), Dushman Award (1998), and multiple research excellence awards Grants & Advising: Supervised 13 Ph.D. and 8 M.S. students, advised postdocs, and hosted over 35 visiting scholars. Active in IEEE standards development and editorial roles. Labs & Teams: Leads the CURENT Engineering Research Center, focusing on ultra-wide-area power grid resilience through advanced power electronics and system integration.
Antonio Rubio Solá is a Full Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the High Performance Integrated Circuits and Systems Design (HIPICS) group. He holds an M.S. in Industrial Engineering (1977) and a Ph.D. in Electronic Engineering (1982), both from UPC. His research focuses on semiconductor technology evolution, integrated circuit design, and memristor-based neuromorphic systems. Key interests include nanoelectronics, energy-efficient computing, and biomimetic circuits. Rubio has contributed to advancements in memristive logic, graphene nanoribbon devices, and fault-tolerant circuit architectures. His work bridges theoretical research and practical implementation, with notable contributions in neuromorphic hardware, in-memory computing, and radiation-hardened electronics. Recent publications emphasize memristor applications in biological systems emulation, stochastic resonance phenomena, and energy-efficient data processing. Rubio actively participates in Spain’s neuromorphic technology initiatives and promotes sustainable microelectronics education through digital tools. Publications are accessible via UPC FenixDoc and the HIPICS e-prints repository. His research is driven by interdisciplinary collaboration, addressing challenges in next-generation computing paradigms and emerging technologies.
Andrew Singer is the Dean of the College of Engineering and Applied Sciences and a Professor in the Department of Electrical and Computer Engineering at Stony Brook University. Previously, he held roles at the Grainger College of Engineering, University of Illinois Urbana-Champaign, including positions as Associate Dean for Innovation and Entrepreneurship. His research spans signal processing, underwater acoustic communications, biomedical acoustics, and entrepreneurship. He leads projects like the MAGIC Automated Acoustics Laboratory and Augmented Listening Technology, focusing on audio signal enhancement, wearable devices, and underwater communication systems. Research interests include adaptive signal processing, turbo equalization, and biomedical applications of acoustics. Notable contributions include high-data-rate ultrasonic communication through biological tissues and real-time video streaming using acoustic channels. His work integrates machine learning and physical models to address challenges in acoustics, communications, and biomedical engineering. Recent articles explore reliable measurement in unreliable systems, underwater source localization, and bio-inspired signal processing techniques. Awards and recognitions are not explicitly listed but his extensive publications and leadership roles highlight his contributions to the field. Advised students and collaborators span academia and industry, including roles at Apple, Amazon, and defense agencies. Current initiatives include developing mechatronic systems for acoustic research and advancing assistive listening technologies.
Prof. Dr. Ir. Wilfred van der Wiel is a full professor of Nanoelectronics at the University of Twente and director of the BRAINS Center for Brain-Inspired Nano Systems . He also holds a second professorship at the Institute of Physics, Westfälische Wilhelms-Universität Münster and serves as a visiting professor there. His research focuses on unconventional electronics for energy-efficient information processing , pioneering Material Learning at the nanoscale to realize computational functionality and artificial intelligence in designless nanomaterial substrates. Education : MSc and PhD in Applied Physics (cum laude) from Delft University of Technology (1997, 2002). Research : Intersects nanotechnology , physics , computer science , and neuroscience , developing artificial neural networks in materials . Grants & Awards : ERC Starting Grant (2009) World Economic Forum Outstanding Young Scientist Award (2013) EIC Pathfinder HYBRAIN (2022-2027) Take-off Grant (2020) Collaborations : Co-founded spin-off ECsens Initiated intensified collaboration with University of Münster International advisor for WISE-SSS program , Tokyo Institute of Technology
Dr. Mark Humphrys is an Assistant Professor at Dublin City University's School of Computing within the Faculty of Engineering and Computing. He holds a BSc in Mathematics and Computer Science from University College Dublin, a PhD in Computer Science from the University of Cambridge, and completed postdoctoral work at the University of Edinburgh. His research spans Artificial Intelligence, Reinforcement Learning, JavaScript-based educational platforms, and multi-agent systems. His research focuses on: Action selection methods in autonomous agents Reinforcement learning architectures JavaScript-based AI education platforms (Ancient Brain) Multi-author hybrid AI systems Turing Test implementations Urban mobility and transportation modeling Analysis of his recent publications reveals strong emphasis on: Educational technology innovations using JavaScript frameworks Financial market impacts on labor economics Distributed AI system architectures Urban transportation solutions and predictive modeling Human-computer interaction paradigms He has supervised 4 PhD students to completion and maintains the Ancient Brain coding platform hosting over 11,000 user projects. His work has received 686 citations with an h-index of 11. Dr. Humphrys leads several projects including Ancient Brain (JavaScript coding education), World-Wide-Mind (distributed AI research), and maintains research groups exploring multi-agent systems and transportation analytics.
Cecilia Diniz Behn is an Associate Professor in the Department of Applied Mathematics and Statistics at Colorado School of Mines. She holds adjunct appointments as an Adjoint Associate Professor in the Division of Endocrinology at the University of Colorado School of Medicine and an Assistant Professor Adjunct in the Department of Integrative Physiology at the University of Colorado Boulder. Her research focuses on multiscale mathematical modeling of sleep, circadian rhythms, and metabolic systems, with applications to insulin resistance and pediatric health. She has secured extensive NIH and NSF funding for her work, including grants on sleep-circadian interactions and glucose-insulin dynamics. Behn's education includes a PhD in Mathematics from Boston University (2006), MA from the University of Texas (2002), and AB from Bryn Mawr College (1999). She has taught advanced courses such as Mathematical Biology, Computational Neuroscience, and Dynamical Systems. Her research bridges applied mathematics with biomedical science, addressing critical questions in neurophysiology and metabolic health through innovative modeling techniques. Recent projects include analyzing light-melatonin interactions in circadian regulation, modeling disrupted sleep patterns in narcolepsy, and developing surrogate models to assess insulin resistance in adolescents. Her work emphasizes the interconnectedness of metabolic and sleep systems, with implications for obesity, diabetes, and pediatric neurology.
Dr. Robert Legenstein is a Full Professor and Institute Head at the Institute of Machine Learning and Neural Computation , Graz University of Technology. He serves as Speaker of the Graz Center for Machine Learning and Action Editor for Transactions on Machine Learning Research (TMLR) . His research bridges computational neuroscience and machine learning, focusing on neuromorphic computing systems that mimic biological neural networks. Research Leadership: Leads EU-funded projects like Adaptive Optical Dendrites (FET-Open) , SYNCH (FET-Proactive) , and Stochastic Assemblies in SNNs (FWF) . Scientific Contributions: Develops learning algorithms for spiking neural networks (SNNs), with applications to memristive architectures, neuroprosthetics, and energy-efficient AI systems. Key Publications: 15+ recent works on topics including dendritic computing, hardware-aware training, and context-dependent neural processing. Teaching Roles: Offers courses like Deep Learning , Principles of Brain Computation , and Data Structures & Algorithms . Contact: robert.legenstein@tugraz.at | +43 316 873 5824 | Inffeldgasse 16b/I, 8010 Graz, Austria.
Shuang Cui is an Assistant Professor in the Department of Mechanical Engineering at The University of Texas at Dallas , affiliated with the Erik Jonsson School of Engineering and Computer Science . She holds the distinction of being a Eugene McDermott Distinguished Professor Fellow . Her research focuses on advanced thermal energy storage materials, intelligent soft materials, nanoscale heat transfer, and grid-interactive building systems. Dr. Cui also serves as Joint Faculty at the National Renewable Energy Laboratory (NREL) since 2022, extending her work on renewable energy solutions. Education : Ph.D. in Mechanical Engineering (UC San Diego, 2018), M.S. in Thermal Engineering (Wuhan University, 2013), and B.S. in Energy Systems (Wuhan University, 2011). Research Interests : Her lab develops novel materials for energy-efficient buildings, including phase change materials, thermo-responsive desiccants, and additive-manufactured thermal systems. She integrates machine learning for materials design and explores nanoscale phenomena in energy conversion. Her work bridges fundamental science with practical applications, such as moisture control, thermal diodes, and radiative cooling. Awards : Recognized with UTD's 2024 ROAR Award, Broader Impact Award, and NREL's Key Contributor Award. She was highlighted in the Department of Energy's Women @ Energy initiative and participated in global symposiums on clean energy and women in engineering. Grants & Advising : Advised a DOE Jump into STEM Competition finalist team. Her research is supported by grants such as the ECO-CBET program. She collaborates across academia and industry to advance sustainable building technologies. Labs & Teams : Leads a multidisciplinary team at UTD and NREL, focusing on materials innovation for decarbonized energy systems. Her work emphasizes translational research for real-world impact.
Dr. Daniel Floryan is the Kalsi Assistant Professor of Mechanical & Aerospace Engineering at the University of Houston, affiliated with the College of Engineering. His research focuses on fluid mechanics, nonlinear dynamics, bio-inspired flows, applied mathematics, and scientific machine learning. He holds a PhD from Princeton University (2019) and undergraduate degrees from Cornell University (BS and BA). Key research interests include turbulence dynamics, flow control, and optimization of swimming and flying systems. His work bridges experimental, computational, and theoretical approaches. Recent studies explore particle dynamics in Rayleigh-Bénard convection, energy-efficient propulsion, and data-driven modeling of fluid systems. Notable awards include the Teaching Excellence Award (2024), Thomas J. R. Hughes Fellowship (2021), and the Sibley Prize (2014). He teaches courses on fluid mechanics and machine learning applications in fluids. His lab (FLO Lab) investigates fluid-thermal interactions and bio-inspired locomotion, emphasizing practical innovations in propulsion and energy systems. Publications span over a decade, addressing topics like flexible foil propulsion, turbulence structure decomposition, and optimal swimming gaits. Collaborations with industry and academic partners drive applied fluid dynamics research with real-world impact.
Erdem Erdemir is an Associate Professor in the Department of Computer Science at Tennessee State University , affiliated with the College of Engineering . His research bridges robotics, cognitive science, and nanotechnology with industrial R&D experience. Education : Postdoc (Vanderbilt), Ph.D. (Vanderbilt), M.Sc. (Boğaziçi), B.Sc. (Boğaziçi) Key Research Areas : Meso-scale robotics, Micro-scale robotics, Machine learning, Nanotechnology Research Interests : Dr. Erdemir investigates active locomotion for capsular robots in colorectal districts, CNT-based batteries , and nanorobots . His work combines neural architectures with developmental approaches for cognitive systems, focusing on triage assistance, gesture-sound coupling, and hybrid control systems for prosthetics. Scientific Contributions : His publications span cognitive control systems , neuromorphic architectures , imitation learning , and fuzzy-neural optimization , with collaborations at IEEE conferences and journals. Recent work explores obstacle avoidance in imitation learning and artificial muscle control . Teaching : Covers foundational and advanced topics including C/C# programming , artificial intelligence , and embedded systems .
Heather Lai is an Associate Professor in the Department of Engineering Programs at SUNY New Paltz. Her research focuses on acoustics, 3D printing materials, biomechanics, and wind energy. She leads projects on wind farm noise analysis using machine learning, psychoacoustic studies on acoustic perception, and structural dynamics of multi-material 3D printed systems. Her work bridges engineering and social science through community engagement initiatives involving residents near wind farms. Lai also develops innovative undergraduate courses integrating AI and low-cost lab equipment, emphasizing ABET student outcomes and interdisciplinary learning. Education: Not explicitly listed in provided text Her research interests span: Dynamic behavior of 3D printed lattice structures Wind farm noise mitigation strategies Biologically inspired viscoelastic materials Acoustic modeling of architectural spaces Vibration energy harvesting Recent publications emphasize wind turbine noise analysis, psychoacoustic listening studies, and 3D printing process optimization. Her work combines experimental validation with computational modeling, often involving student researchers in data collection and analysis. Awards/Honors: None explicitly listed Lai advises undergraduate researchers in multiple projects including wind farm acoustics, 3D printed prosthetics, and psychoacoustic studies. She collaborates with communities to integrate residents into noise monitoring through apps like Auditive. Her labs focus on low-cost experimental setups and material characterization. Lai's research groups engage in both fundamental material science and applied community projects, with a strong emphasis on undergraduate involvement in real-world problem solving.
Alison L. Barth is the Maxwell H. and Gloria C. Connan Professor in the Life Sciences at Carnegie Mellon University's Department of Biological Sciences, Mellon College of Science. She holds a Ph.D. from the University of California, Berkeley, and completed postdoctoral training at Stanford University School of Medicine. Her research focuses on how sensory experience shapes neural circuits in the cerebral cortex, particularly in mice. Key projects include studying synaptic plasticity mechanisms, developing fluorescence-based synapse analysis tools, and exploring neural network design principles for AI applications. Her lab employs advanced techniques like electrophysiology, electron microscopy, and computational modeling. Recent achievements include election as an AAAS Fellow (2024) and contributions to understanding PV interneuron roles, thalamocortical plasticity, and high-throughput connectomics. Ongoing work addresses learning algorithms, disease models (Alzheimer's/Parkinson's), and collaborative engineering initiatives for neural-inspired technologies. Publications span neuroscience, computational biology, and neuroengineering, with a focus on cortical circuits, synaptic mechanisms, and translational applications.
Leong Hon Wai is an Associate Professor at the National University of Singapore (NUS) in the Department of Computer Science under the School of Computing . He also participates in the University Scholars Programme (USP). With a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign and a B.Sc. in Mathematics (1st Class Honours) from the University of Malaya , Prof. Leong has been a cornerstone of NUS since 1987, previously serving as Division Head for Computer Science and Assistant Dean for Special Programmes . His work bridges computational theory with practical applications in bioinformatics , transportation logistics , and VLSI CAD . Education: B.Sc. in Mathematics, University of Malaya (1st Class Honours) Ph.D. in Computer Science, University of Illinois at Urbana-Champaign Research Interests span the design of efficient algorithms across diverse domains. Key areas include: Bioinformatics : Algorithmic solutions for genomic island detection, protein function prediction, and genome sorting. VLSI CAD : Applied research in computer-aided design for integrated circuits. Logistics : Algorithms for resource allocation, scheduling, and dynamic route planning. Computational Thinking : Pedagogical approaches to simplify complex concepts for non-computer science audiences. His publications reflect interdisciplinary collaboration, particularly at the intersection of algorithm design and biological systems , with a focus on problems like protein function prediction and genome rearrangement . The scientific community has recognized his contributions through fellowships and teaching awards , including the Annual Teaching Excellence Award and Inspiring Mentor Award from NUS. Awards & Honors : Fellow, Singapore Computer Society (2009) NUS Annual Teaching Excellence Award (2009) Inspiring Mentor Award (NUS, 2009) USP Teaching Award (2008) Best Paper Award (APCCAS-1992) Best Presentation Award (ICCD-1985) Excellent Instructor (UIUC, Spring 1985) Teaching & Outreach initiatives include founding Singapore’s Special Programme in DISCS , pioneering NUS’s modular curriculum aligned with ACM standards, and leading the National Olympiad in Informatics (NOI) since 1998. He also co-organizes the annual 24-hour Code::XtremeApps (CXA) competition, engaging primary school students through platforms like Scratch and micro-bit . His passion for computational thinking extends to the course GET1031 for non-majors and outreach programs in K-12 education. Professional Service includes leadership roles in the Singapore Computer Society (SCS), organizing conferences like SEARCC'99 , and serving on the SCS Executive Committee (1994–2007). He is a member of prestigious societies: ACM , IEEE , and ISCB .
