Associate Professor Lasantha Meegahapola is a Deputy Head of Department (Teaching & Learning) at RMIT University's School of Engineering in Melbourne, Australia. He holds an IEEE Senior Membership and serves as an Associate Editor for several prestigious journals, including IEEE Transactions on Power Systems and IET Renewable Power Generation. His research focuses on Power System Stability with Renewable Integration, Microgrid Control, and Smart Grid Technologies, addressing challenges like voltage stability, inverter-based grid dynamics, and renewable energy penetration. He has supervised 16 PhD students to completion and published over 200 articles. Key contributions include identifying stability issues in microgrids and advancing grid-forming inverter control strategies. His work aligns with UN Sustainable Development Goals 7 (Clean Energy), 9 (Infrastructure), and 13 (Climate Action). He is actively involved in IEEE committees, including the PSDP Task Force on Microgrid Stability. Teaching roles include Programme Manager for the Bachelor of Electrical Engineering (HK) and Subject Coordinator for Power System Analysis and Control courses. Collaborations span industry and international research institutions, emphasizing real-world applications of his research in power systems and renewable energy integration.
Klaus Mølmer is a Professor at the Niels Bohr Institute, University of Copenhagen, specializing in Quantum Optics and Photonics. His research spans quantum information, entanglement, and cavity QED, leveraging machine learning and Grover's algorithm for quantum state engineering. His recent work focuses on spin squeezing, Rydberg atom interactions, and mechanical resonator cooling. A leader in quantum simulation and superradiance, he collaborates on cavity-mediated emission and quantum network design. The 15 most recent articles highlight advancements in quantum state manipulation, entanglement protocols, and robust differential phase sensing. These studies bridge theoretical frameworks with experimental applications in cavity QED, Rydberg arrays, and zero-photon detection.
Dr. Madhav Manjrekar is an Associate Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte. He earned his Ph.D. from the University of Wisconsin–Madison in 1999. His research focuses on power electronics applications in utility systems, renewable energy interfaces, and cybersecurity of electricity infrastructure. Key areas include power quality improvement in microgrids, high-voltage direct current (HVDC) transmission, and advanced electrical machine design for electric vehicles and wind energy systems. His work emphasizes innovative solutions for energy storage integration, grid resiliency, and fault-tolerant power systems. Recent publications highlight advancements in DSTATCOM for microgrids, solid-state circuit breakers, and doubly salient electrical machines. He has contributed to projects like the US-Caribbean Super Grid and HVDC interconnectors for offshore renewable energy. Dr. Manjrekar’s research also addresses cybersecurity vulnerabilities in power infrastructure and explores next-gen semiconductor technologies like SiC MOSFETs. His interdisciplinary approach bridges power electronics, machine design, and grid stability, with applications in both academic and industry settings.
Anamitra Pal is an Associate Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His work focuses on power system resilience, renewable energy integration, and time-synchronized measurement analytics. He leads research initiatives combining artificial intelligence with grid modernization challenges. Ph.D. Electrical Engineering, Virginia Tech (2014) M.S. Electrical Engineering, Virginia Tech (2012) B.E. Electrical and Electronics Engineering, Birla Institute of Technology (2008) Prior to ASU, Pal conducted postdoctoral research at Virginia Tech's Network Dynamics and Simulation Science Laboratory (2014-2016). His research interests center on enhancing grid stability through: Advanced synchrophasor data analytics AI-driven power system security frameworks Renewable generation integration strategies Critical infrastructure protection during extreme events Recent publications demonstrate his focus on grid resilience during wildfires, deep learning-based state estimation, and innovative PMU applications. Pal has received multiple accolades including the NSF CAREER Award (2022) and IEEE Phoenix Section's Outstanding Young Professional Award (2019).
Professor Grahame Holmes is an Honorary Professor in the School of Engineering at RMIT University, Australia. His expertise spans electrical energy conversion, smart energy systems, renewable energy integration, power electronics, and grid infrastructure. He focuses on advancing technologies for sustainable energy storage, grid stability, and high-efficiency power conversion. Research Interests : Electrical and Electronic Engineering, Communications Technologies, Power Electronics, Renewable Energy Systems, and Grid Integration Solutions. His work emphasizes practical applications such as hydrogen energy storage systems, grid-interactive inverters, and modular multilevel converters. Recent Contributions : Prof. Holmes has published extensively on topics like advanced PWM techniques, resonant current controllers, and DC transformer designs. His research bridges theoretical advancements with real-world implementations, addressing challenges in smart grid stability and high-frequency power conversion. Advising & Grants : Supervised projects include 'Hydrogen Energy Storage System for Nanogrid' (2015) and 'Synchronised Control of Grid-Interactive Inverters' (2015). While specific grant details are not listed, his work aligns with major themes in sustainable energy research. Labs & Collaborations : Engages in collaborative research through RMIT's facilities, focusing on hardware-software co-simulation frameworks and FPGA-based real-time systems.
Seth Lloyd is a Professor in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT), with adjunct appointments at the Santa Fe Institute since 1988 and as a Fellow at the Institute for Scientific Interchange since 2000. His research spans quantum information science, quantum control theory, and complex systems analysis. His educational background includes: B.A. from Harvard University (1982) M. from the University of Cambridge (1984) Ph.D. from Rockefeller University (1988) Lloyd's work focuses on quantum computation, quantum communications, and quantum limits to control and sensing. He has pioneered research in quantum algorithms, quantum metrology, and applications of quantum information to complex biological and physical systems. His research bridges theoretical physics, computer science, and engineering, with over 200 publications and two patents in quantum information processing. Analysis of his recent publications reveals dominant trends in quantum machine learning, quantum metrology, and quantum communication protocols, with increasing interdisciplinary applications in quantum biology and quantum gravity. His work consistently explores fundamental limits of quantum information processing. His scientific awards include: Lindbergh Fellow (1994) Finmeccanica Professorship (1996) Edgerton Prize (2001) Fellow of the American Physical Society (2007) Quantum Communication, Measurement, and Computation Prize (2012) Lloyd serves on the editorial board of Quantum Information Processing and holds significant MIT service roles including Course 2 Undergraduate Committee coordinator and membership on the Institute Foreign Scholarships Committee. He teaches advanced courses in quantum information, dynamics, and computational methods, shaping the next generation of quantum scientists and engineers. As a member of the American Physical Society, he maintains active research collaborations across quantum information science, with ongoing work in quantum algorithms and quantum-enhanced sensing technologies.
Ruonan Han is a Professor of Electrical Engineering and Computer Science at MIT and serves as Associate Director of the Microsystems Technology Laboratories (MTL) and Director of the MIT-MTL Center for Integrated Circuits and Systems . His research focuses on ultra-high-frequency microelectronic circuits , particularly addressing the 'terahertz gap' in sensing, metrology, security, and communication. He leads the Terahertz Integrated Electronics Group at MIT's MTL, established in 2014. Education: B.S. in Microelectronics, Fudan University (2007) M.S. in Electrical Engineering, University of Florida (2009) Ph.D. in Electrical and Computer Engineering, Cornell University (2014) Research Interests: Terahertz (THz) integrated circuits and systems High-frequency CMOS technologies Quantum sensing and magnetometry RF systems for imaging, radar, and molecular sensing Energy-efficient communication systems His work bridges electronic circuits , electromagnetics , and quantum physics , with applications in defense, healthcare, and environmental monitoring. Awards & Recognition: 2023 IEEE SSCS New Frontier Award 2020 NSF CAREER Award 2019 Intel Outstanding Researcher Award 3× IEEE RFIC Best Student Paper Awards (2012, 2017, 2021) Advising & Leadership: Ph.D. advisor to over 10 students (many recipients of MIT MTL Dissertation Awards) Co-advises with Prof. Anantha Chandrakasan and Prof. Tomás Palacios Editorial roles at IEEE Transactions on Quantum Engineering and VLSI Systems Technical committee member for ISSCC, RFIC, and IMS Labs & Teams: Terahertz Integrated Electronics Group at MIT MTL: Focuses on chip-scale THz systems, quantum devices, and next-generation RF circuits Collaborations with industry (e.g., Apple, MediaTek) and academic groups (e.g., D. Englund's lab at MIT)
Hanbyul Joo is an Assistant Professor in the Department of Computer Science and Engineering at Seoul National University (SNU). Prior to joining SNU, he was a Research Scientist at Facebook AI Research (FAIR) in Menlo Park. He completed his Ph.D. in the Robotics Institute at Carnegie Mellon University, working with Yaser Sheikh, and received his M.S. in Electrical Engineering and B.S. in Computer Science from KAIST, Korea. Dr. Joo's educational journey began at KAIST, where he earned both his Bachelor's and Master's degrees. He then pursued his Ph.D. at Carnegie Mellon University's Robotics Institute, completing his dissertation titled "Sensing, Measuring, and Modeling Social Signals in Nonverbal Communication." His doctoral work focused on developing the Panoptic Studio, a unique sensing system with over 500 synchronized cameras for capturing social interactions. Dr. Joo's research primarily focuses on endowing machines and robots with the ability to perceive and understand human behaviors in 3D . His goal is to build "social Artificial Intelligence" that can interact with humans using social signals (body languages). He pursues this direction using data-driven methods where data is collected by measuring the wide spectrum of social signals transmitted during interpersonal social interaction. His research spans computer vision, machine learning, computer graphics, and robotics , with particular emphasis on 3D human pose estimation, human-object interaction, and social signal processing. His recent publications demonstrate a clear trend toward leveraging diffusion models for 3D reconstruction and generation tasks, with a focus on human-centric applications. His work bridges the gap between 2D image understanding and 3D scene reconstruction, often utilizing pre-trained models to overcome data limitations. The research consistently addresses fundamental challenges in understanding human behavior, interaction with objects, and social dynamics in 3D space. Dr. Joo is a recipient of several prestigious awards including the Samsung Scholarship and the CVPR Best Student Paper Award in 2018 . His paper "Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies" received this honor at CVPR 2018. His research has been widely recognized in top computer vision and AI conferences, with multiple oral presentations at venues like CVPR, ICCV, and ECCV. Dr. Joo actively mentors a large group of students, with approximately 15 current students working toward MS/PhD degrees under his supervision. His lab, the SNU VCLab, focuses on cutting-edge research in computer vision and graphics. He has secured significant research funding through his work, though specific grant details aren't provided on his website. Dr. Joo frequently serves as an area chair for major conferences including CVPR, ICCV, and NeurIPS, demonstrating his standing in the academic community. Dr. Joo leads the SNU VCLab, which has developed several notable datasets and tools including SNU ParaHome, FrankMocap, and the CMU Panoptic Studio Dataset. His lab maintains strong industry connections, with students interning at leading companies like Meta. The lab's research focuses on building the infrastructure and algorithms needed for social AI, with an emphasis on practical applications that can be deployed in real-world settings.
Hedvig Kjellström is a Professor at the Division of Robotics, Perception and Learning within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. She holds significant affiliations with the Swedish e-Science Research Centre and the Max Planck Institute for Intelligent Systems in Germany. Her work spans multiple interdisciplinary domains and she serves as Editor-in-Chief for CVIU and was Program Chair for CVPR 2025. Her research centers on Computer Vision as a sub-field of AI, with three interconnected themes: Computational Aesthetics (exploring aesthetic aspects of human communicative behavior), Communicative Behavior (developing models of how humans and animals perceive and produce non-verbal communication), and Embodied Artificial Intelligence (creating methodologies for robots and autonomous agents to perceive the world through sensors, primarily vision). Her work has significant applications in medical diagnostics, animal welfare, human-robot interaction, and creative arts. Analysis of her recent publications reveals a strong trend toward multimodal AI systems that integrate vision, language, and action understanding. Her research increasingly focuses on animal-centered applications, particularly equine pain detection and behavior analysis, while maintaining strong foundations in human communication modeling, gesture recognition, and 3D reconstruction techniques. The interdisciplinary nature of her work bridges computer science with veterinary medicine, neuroscience, and performing arts. Hedvig Kjellström actively supervises numerous PhD and Master's students across various projects and maintains extensive collaborations with institutions including Karolinska Institutet, Swedish University of Agricultural Sciences, and international partners. Her research is supported by major funding bodies including WASP, VR, and SeRC. She leads or participates in several notable projects including OrchestrAI (communication between conductor and orchestra), ANITA (Animal Translator), MARTHA (3D horse motion analysis), and STING (synthesis and analysis with transducers and invertible neural generators). Her work with ACAI (Animal Centered Artificial Intelligence), which she co-founded and directs, demonstrates her commitment to applying AI for animal welfare.
Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.
Fernando De la Torre is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, with an affiliation to the Robotics Institute where he has been a research faculty member since 2005. He holds a Ph.D. in Electronic Engineering from Ramon Llull University (2002). His research focuses on machine learning and computer vision, with applications in human health, augmented/virtual reality, generative models, and data-centric methodologies. He directs the Human Sensing Laboratory, which explores technologies for human behavior analysis and health monitoring. Notable contributions include founding FacioMetrics LLC (acquired by Meta), advancing facial recognition and 3D human digitization, and developing frameworks for robust visual models. His work bridges theory and practice, with over 225 peer-reviewed publications and editorial roles, including Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence. Recent research trends emphasize generative AI applications in satellite imagery analysis, VR/AR rendering optimizations (e.g., Gaussian splatting), and clinical motion recognition for healthcare. His projects often intersect with industry, addressing challenges in wearable health monitoring and immersive technologies. His lab collaborations span academia and industry, focusing on scalable solutions for 3D human modeling, adversarial robustness, and multimodal data fusion. Key achievements include pioneering work on 3D face animation from speech and garment reconstruction from single images.
Edwin van der Heide is a part-time Lecturer and researcher at Leiden University, affiliated with the Leiden Institute of Advanced Computer Science (LIACS) and the Academy for Creative and Performing Arts (ACPA). His work bridges sound, space, and interaction through installations, performances, and environments. Key roles include: Co-head of ArtScience Interfaculty (Royal Conservatoire & Royal Academy of Art, The Hague) until 2016 Edgard Varèse Guest Professor at TU Berlin (2009) Invited artist at Le Fresnoy (France) and HKB Bern University of the Arts (2019) Research Interests: Spatial sound composition, audience interaction, interdisciplinary art, and the intersection of technology with auditory perception. Notable projects include Whispering Wind (permanent installation at Leiden University) and Spiral of Time (MACBA, Barcelona). Recent Articles & Exhibitions (2023–2024): Focus on large-scale installations like Pneumatic Sound Field and Spiral of Time , emphasizing public engagement and spatial acoustics. Awards: Witteveen+Bos Art+Technology Award (2009), Best Paper Award for BAI (摆) (2018). Grants & Labs: Collaborations with institutions like NCCA (Russia), MAXXI (Italy), and involvement in projects like Evolving Spark Network (global sound art initiatives).
Jerome Engel, M.D., Ph.D. is a Professor at the Jane and Terry Semel Institute for Neuroscience and Human Behavior , University of California, Los Angeles (UCLA). He serves as Director of the Epilepsy Telemetry Unit within the Seizure Disorder Center and is a member of the Brain Research Institute and the Neuroscience GPB Home Area. His work spans neurology, psychiatry, and biomedical research. Research Focus: Epilepsy, epileptogenesis, high-frequency oscillations (HFOs), neuroimaging, surgical interventions, and biomarker development. Key Contributions: Pioneering studies on fast ripples as biomarkers, network-based surgical outcome prediction, and advanced HFO detection algorithms. Publications (15 most recent) address topics such as kainic acid models of epileptogenesis, thalamic sleep spindles in pediatric epilepsy, self-supervised HFO analysis, and graph theoretical measures for surgical planning. His work frequently employs medRxiv and Epilepsia as platforms for translational findings. Contact: engel@ucla.edu
Tariq Iqbal is an Assistant Professor at the University of Virginia , with joint appointments in the Department of Systems and Information Engineering and Department of Computer Science . He leads the Collaborative Robotics Lab (CRL) , specializing in human-robot teams and embodied AI . Previously, he was a Postdoctoral Associate at MIT's CSAIL , advised by Prof. Julie Shah , and earned his Ph.D. in Computer Science from University of California San Diego (UCSD) under Prof. Laurel Riek . Ph.D. in Computer Science, University of California San Diego (2017) M.S. in Computer Science, University of Texas at El Paso (2012) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2007) His research lies at the intersection of artificial intelligence and robotics , focusing on human-robot collaboration in dynamic environments. Key areas include motion prediction , multimodal fusion , trust modeling , and collaborative learning . His work integrates cognitive science and deep learning to enhance robotic fluency in naturalistic settings. Recent publications (2023–2025) highlight advancements in human-robot team dynamics , multimodal dataset creation , and motion prediction algorithms . Notable works include Energy-Based Transformers for scalable AI, PoseTron for motion prediction, and Accessible Navigation Mapping for assistive robotics. These contributions span trust modeling , cloud robotic infrastructure , and safety in close-proximity collaboration . National Science Foundation (NSF) CAREER Award Air Force Office of Scientific Research (AFOSR) Young Investigator Program (YIP) Award Commonwealth Center for Advanced Manufacturing (CCAM) Innovation Award As faculty, he has secured grants from NSF and AFOSR , mentored research students, and taught courses like Stochastic Modeling I (SYS 6005) and Robots and Humans (SYS 4582/6465, ECE 4502/6465, CS 6465) . His prior industry roles at IBM Watson Lab and Grameenphone Ltd. inform his applied research in telecom infrastructure and cognitive robotics . He leads the Collaborative Robotics Lab (CRL) at UVA, which develops multimodal datasets , real-time coordination algorithms , and adaptive pathfinding systems . Current projects explore human motion prediction , team synchrony , and embodied question-answering , reflecting his commitment to advancing human-robot fluency and contextual AI .
Andrew Warfield is an Adjunct Professor in the Department of Computer Science at the University of British Columbia (UBC) and a Senior Principal Engineer at Amazon. His research focuses on computer systems software, including virtualization, distributed storage, security, and high-availability systems. He previously held roles as Associate Professor at UBC, CTO at Coho Data, and Technical Director at Citrix Systems. His work has led to projects like Remus (high-availability replication), Tralfamadore (execution analysis), and secure hypervisor development with Xen. Warfield's education includes a PhD from the University of Cambridge's Computer Laboratory, where he researched I/O device virtualization under Steven Hand. He has held visiting roles at Intel Research Cambridge and internships at AT&T Research and Nortel Networks. Research Grants: Supported by Intel Research, NSERC, Network Appliance, and the Communications Security Establishment. Professional Activities: Technical Advisory Board Member at Teradici, and involvement in program committees for conferences like HotOS, EuroSys, and FAST. His research emphasizes practical systems, aiming to bridge the gap between theoretical computer science and real-world applications. Notable contributions include innovations in storage for virtualized environments, secure hypervisor architectures, and disaster-tolerant systems like SecondSite. Warfield is affiliated with UBC's Department of Computer Science and maintains active collaboration with industry partners. Though currently not actively recruiting students, his prior mentorship has influenced many in systems research.
