Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.
Ambuj Varshney is an Assistant Professor at the National University of Singapore (NUS) School of Computing , leading the WEISER research group . His work bridges electronics, wireless communication, computer science, and AI with a focus on creating ultra-low-power embedded systems for sustainable IoT deployments. University of California, Berkeley: Postdoctoral Scholar (2020-2022) Uppsala University: PhD in Sustainable Networked Systems NXP Semiconductors: Software Engineer (prior to PhD) Bachelors in Information & Communication Technology Research interests center on overcoming wireless systems' energy asymmetry through tunnel diode oscillators , LiFi-RF hybrid networks , and battery-free communication architectures . His group develops STICORS —sticker-like computers for industrial and medical monitoring. Recent publications demonstrate AudioCast 's FM-band utilization for 130m transmission, TunnelSense 's vital monitoring, and PixelGen 's diffusion model cameras. These works combine IoT sustainability, spectrum efficiency, and hardware innovation . 2024: Google Research Scholar Award 2023: MobiSys Best Demonstration 2021: Berkeley FORM+FUND Fellowship 2019: ABB's $300K Research Award As an educator, he teaches CS4222 Wireless Networking and CS5272 Embedded Software Design . Past students include Wenqing Yan (NUS/UCB PhD), Qiao Yukai , and Kunjun Li . His team collaborates with Prabal Dutta (UCB), Christian Rohner (Uppsala), and Prateek Saxena (NUS).
Professor Tongming Zhou is a faculty member in the Department of Civil, Environmental and Mining Engineering at the School of Engineering, The University of Western Australia (UWA) . He serves as Director of the UWA Boundary Layer Wind Tunnel Laboratory and Program Chair for Civil Engineering , contributing to both academic leadership and industrial applications. His work bridges fundamental fluid mechanics with practical engineering challenges. Education : PhD in Fluid Mechanics from The University of Newcastle (1999) Teaching : Coordinates core units like CIVL2551, CIVL5551, and CIVL4402/CIVL3402 Hydraulics, emphasizing real-world application and industry collaboration Research Interests focus on: Suppression of vortex shedding and vortex-induced vibrations (VIV) in cylindrical structures Enhancement of VIV and galloping for renewable energy harvesting Wave resonance in floating LNG facilities Sloshing dynamics in tanks with Newtonian/non-Newtonian fluids Wind tunnel testing for industrial wind load analysis Recent Research Trends show interdisciplinary work combining experimental and numerical fluid dynamics, with applications to offshore engineering, maritime safety, and energy systems. His projects explore VIV in flexible risers, gas leakage effects on pipelines, and triboelectric nanogenerators for wind energy. Grants : ARC Grant (2019-2021): Development of novel inerter-based dampers ARC Grant (2013-2015): Local Scour below Offshore Pipelines ARC Grant (2011-2015): Vortex & Force Characteristics of Inclined Cylinders UWA Grant (2008): Control of Vortex Shedding with Helical Strakes Facilities Leadership : Upgraded UWA’s Boundary Layer Wind Tunnel , Hydraulic Laboratory Water Flume , and 6DOF Hexapod motion platform , acquiring advanced equipment like PIV systems and high-precision load cells.
Qing Li is an Associate Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.E. in Electronics Engineering from Tsinghua University (2006) and a Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology (2013). Prior to CMU, he worked as a postdoctoral researcher at the National Institute of Standards and Technology (NIST), where he developed quantum frequency conversion and microresonator-based optical systems. His research focuses on light-matter interactions in integrated photonics, emphasizing nonlinear optics and quantum information processing. He has pioneered silicon carbide and aluminum nitride platforms for chip-scale quantum technologies and optical metrology. Dr. Li has been recognized with prestigious awards including the Darpa Young Faculty Award (2019), OSA Paul F. Forman Team Engineering Excellence Award (2020), and Sigma Xi Best Ph.D. Thesis Award (Georgia Tech). His work bridges classical and quantum information systems, with applications in secure communication, atomic systems interrogation, and high-precision frequency synthesis. He actively contributes to the Pittsburgh Quantum Institute (PQI), advancing regional quantum engineering initiatives. His research group’s key projects include developing compact optical frequency synthesizers, soliton microcombs for communication grids, and entangled photon pair sources for quantum networks. Grants and collaborations support his exploration of novel photonic materials and devices, targeting advancements in both fundamental science and applied technologies.
Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.
Zoya Popovic is a Distinguished Professor and holds the Lockheed Martin Endowed Chair in RF Engineering at the University of Colorado Boulder's Department of Electrical, Computer, and Energy Engineering. She earned a Dipl.Ing. from the University of Belgrade (1985) and a PhD from Caltech (1990). She has advised over 50 PhD students and was a visiting professor at Technical University of Munich (2001). Her research focuses on high-efficiency microwave/millimeter-wave circuits, smart antenna arrays, wireless powering systems, and biomedical microwave applications. Notable contributions include quasi-optical imaging techniques and low-noise amplifier designs. Key awards: IEEE Microwave Prizes (1993/2006), Humboldt Research Award (2000), Terman Medal (2001) Lab Group Website: [Link] Recent work emphasizes in-band full-duplex systems, GaN MMICs, and quantum-based waveform modulation. Her group maintains advanced facilities for millimeter-wave and terahertz research.
Suresh Krishna is an Associate Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on the neurophysiological and computational basis of sensory processing, attention, and eye movements, with applications to brain-machine interfaces and human health. He works with human subjects, non-human primates, and open datasets using in-vivo electrophysiology, eye-tracking, and computational modeling. Research interests include visual attention mechanisms, saccadic eye movement control, neural coding of motion perception, and the interplay between attention and decision-making. His work bridges basic neuroscience with translational applications such as improving neural prosthetics and understanding perceptual disorders. Recent work highlights how neural remapping processes during saccades underlie spatial perception, and how attention modulates neural activity patterns in visual cortex. The lab's publications reveal critical insights into the temporal dynamics of attentional shifts and their neural substrates, particularly in areas MT and MST. Dr. Krishna's team also investigates auditory temporal processing in the inferior colliculus, exploring correlations between neuronal responses to sound modulation. Their findings contribute to understanding how sensory systems encode temporal information across modalities. Research is conducted in the M2B3 Lab (http://m2b3.lab.mcgill.ca), which integrates experimental and computational approaches to study brain mechanisms underlying perception and action. No specific awards are listed, but ongoing work involves major contributions to primate neurophysiology and translational neuroscience.
Prof. Dr. Amelie Hagelauer holds a professorship in Micro- and Nanosystem Technology at the TUM School of Computation, Information and Technology, Technical University of Munich. Her work focuses on advanced electronics and systems integration across quantum computing hardware, resistive memory technologies, and high-frequency RF systems. She has contributed to innovations in superconducting qubit readout architectures, multi-level RRAM designs, and 3D-integrated CMOS-compatible quantum devices. Research interests span quantum hardware design, nanoelectronic devices, RF front-end systems, and emerging memory technologies. Her work emphasizes practical implementation challenges such as low-power operation, high-voltage handling in RF switches, and wafer-scale fabrication processes. Recent projects include D-band radar systems, energy-efficient 60 GHz transceivers, and antenna tuning solutions for 5G applications. Publications from 2023-2025 showcase advancements in resistive switching device characterization, mitigation of TLS losses in superconducting qubits, and reconfigurable AI accelerators using RRAM-based digital twins. Her work bridges theoretical device physics with practical integrated circuit design, addressing scalability and reliability in next-gen electronics. Awards and grants: None explicitly listed in provided texts. Active collaborations include EU-funded projects on quantum computing platforms and TUM's Electronic Photonic Integration initiatives. Leads research teams in microsystem technology with emphasis on cross-disciplinary approaches combining CMOS processes, MEMS, and quantum engineering.
Andrew Yonelinas is a Professor in the Department of Psychology at the University of California, Davis, where he directs the Human Memory Lab. He holds additional leadership roles as Associate Director of the Center for Mind and Brain and is an affiliated faculty member with the UC Davis Center for Neuroscience. His research bridges cognitive psychology and neuroscience to investigate fundamental memory mechanisms and their neural substrates. His educational background includes a Ph.D. in Experimental Psychology from McMaster University (1995) and a B.S. in Cognitive Science from the University of Toronto (1990). These foundational studies established his expertise in experimental methodologies and cognitive theory. Yonelinas specializes in dual-process models of memory, distinguishing between recollection (detailed contextual retrieval) and familiarity (vague recognition). His lab employs process dissociation, remember/know procedures, and ROC modeling alongside neuroimaging (fMRI, ERP) and clinical studies with amnesic and Alzheimer's patients. Recent work expands into auditory working memory, multisensory integration, and the impact of mental illness on cognitive processes, revealing hippocampal roles across memory systems. His research consistently addresses how memory fails in clinical conditions while developing unified theoretical frameworks. Analysis of his 2024-2025 publications shows a strong focus on memory mechanisms across sensory modalities, with increasing emphasis on clinical applications. Key trends include hippocampal contributions to visual/auditory working memory, EEG-based biomarkers for mental illness, and the interplay between schema knowledge and memory distortion in aging populations. His work demonstrates methodological innovation through model-based EEG phenotyping and multisite clinical collaborations. His scientific recognition includes: American Psychological Society’s Shahin Hashtroudi Memorial Award University of California Chancellor’s Fellow Award European Brain and Behavior Society International Lecture Award Yonelinas actively shapes his field through editorial roles at top journals including Proceedings of the National Academy of Sciences and Journal of Experimental Psychology, while serving as a grant reviewer for NIH, NSF, and international funding bodies. His Human Memory Lab trains next-generation researchers in memory theory and methodology, with recent projects examining stress effects on memory precision and neural mechanisms of action slips. The Human Memory Lab operates within UC Davis's neuroscience ecosystem, collaborating closely with the Center for Mind and Brain on projects involving clinical populations and neuroimaging. Current initiatives include the CNTRACS Consortium for EEG standardization in mental illness and investigations into how stress modulates memory binding through hippocampal mechanisms.
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).
Lee Miller is a Professor in the Department of Neurobiology, Physiology, and Behavior at the University of California, Davis, College of Biological Sciences. His research integrates neural engineering, physiology, and computational methods to develop communication restoration technologies and investigate sensory processing mechanisms. His primary research interests include neural engineering for speech neuroprosthetics, electrophysiological analysis of speech production, auditory neuroscience, and geometric approaches to neuromuscular signal decoding. He employs surface electromyography (EMG), electroencephalography (EEG), and computational modeling to study brain-machine interfaces for speech restoration and multisensory integration. Recent publications reveal a dominant focus on EMG-based speech neuroprostheses, with geometric and topological analysis of neuromuscular signals emerging as a key methodology. His lab has pioneered non-invasive approaches to speech articulation decoding, created standardized EMG databases, and investigated neural mechanisms of attention in speech-in-noise processing. This work bridges engineering innovation with fundamental neuroscience to address communication disorders. Professor Miller leads the Miller Lab at UC Davis, which specializes in neural engineering for communication restoration. The lab develops real-time speech synthesis systems from neural signals and investigates the physiological basis of speech production and perception using multimodal recording techniques.
Prashant Mehta is a Professor of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign , affiliated with the Coordinated Science Laboratory . His research focuses on controlled interacting particle systems and machine learning applications , particularly in human activity recognition using motion sensors. Education: Ph.D. in Mathematics, Cornell University (2004) M.S. in Electrical & Computer Engineering, University of Massachusetts Amherst (1996) B.E. in Electrical & Electronics Engineering, Birla Institute of Technology & Sciences (1993) Mehta's work has pioneered the feedback particle filter (FPF) algorithm for nonlinear estimation, applied in robotic systems and gesture recognition. His research spans control of combustion instabilities in jet engines, mean-field games , and dynamical systems in aerospace engineering. His publications emphasize nonlinear control theory and stochastic filtering , with recent trends in sensor data pattern recognition and cyber-physical systems . He has received multiple scientific awards , including the MURI award for the Cyberoctopus project and Excellence in Undergraduate Advising Awards . Scientific Honors: MURI Award (2019) for Cyberoctopus Excellence in Undergraduate Advising (2010, 2008) Outstanding Teaching Assistant Award (1994) Senior Member, IEEE Control Systems Society Member, ASME Energy Systems Subcommittee Member, SIAM Dynamical Systems Group Mehta has supervised students like Jin Kim (IEEE CDC Best Student Paper, 2019) and co-founded the startup Rithmio , acquired by Bosch Sensortec . His laboratory develops gesture-detection filters for applications in soft robotics and human-machine interfaces .
Dr. Gary Scavone is a Professor and Department Chair in the Music department at McGill University's Schulich School of Music. He holds a PhD in Computer-Based Music Theory & Acoustics and MS in Electrical Engineering from Stanford University, alongside degrees from Syracuse University in Music and Electrical Engineering. His research focuses on music technology, including acoustic modeling, sound synthesis, and instrument design. He directs the Computational Acoustic Modeling Laboratory (CAML), which explores advanced techniques for simulating musical instruments and developing software tools. As a saxophonist, he specializes in contemporary concert music performance. Research interests include physically-based sound synthesis, wind instrument acoustics, and digital waveguide modeling. He has contributed to studies on brass and woodwind impedance measurements, violin soundpost dynamics, and free-reed instrument modeling. His work bridges engineering and artistry, with applications in music pedagogy, instrument design optimization, and virtual acoustic replication. Key contributions include open-source projects for wind instrument modeling and the development of tools for automated timbre assessment. His research often combines experimental methods with computational simulations, addressing challenges in both theoretical and applied music acoustics. Current projects focus on deep learning for friction modeling, impedance measurement systems, and cross-cultural instrument analysis.
Dr. Chenming Zhang is an Advanced Queensland Industry Research Fellow at the School of Civil Engineering, The University of Queensland. His research focuses on hydrological processes in coastal and terrestrial groundwater systems, with particular emphasis on evaporation-driven mass and heat transport in soils and tailings, and hydrogeochemical dynamics in aquifers and mine waste systems. Specializes in IoT-based environmental monitoring Develops numerical models for coastal aquifer dynamics Conducts field and laboratory experiments on tailings behavior Research interests span coastal hydrology, groundwater modeling, mine waste management, and environmental monitoring. He works on contamination transport, aquifer protection, and climate impacts on water systems. Recent publications analyze: Iron curtain formation in subterranean estuaries Sea water intrusion mechanisms Salinity dynamics in tidal wetlands Smart sewer monitoring systems Scientific awards include the prestigious Advanced Queensland Industry Research Fellowship. He supervises multiple PhD projects on mine waste hydrology and coastal aquifer management, with notable collaboration on: Evolution Mining's gold tailings projects ARC Discovery Projects on coastal processes Grange Resources' PAF cell instrumentation His work combines field measurements, laboratory testing, and computational modeling to address critical environmental challenges in mining and coastal zones.
Olivier Pfister is a Professor in the Department of Physics at the University of Virginia , with courtesy appointments in Electrical and Computer Engineering (2022–). His research focuses on experimental quantum optics and quantum information , particularly leveraging optical frequency combs to develop scalable quantum computing platforms. The Quantum Fields and Quantum Information (QFQI) group , which he leads, has pioneered techniques for generating multipartite entanglement in continuous-variable systems, achieving cluster-state entanglement in 60+ qumodes (with potential scaling to thousands). Collaborations span institutions like NIST, University of Sydney, CUNY, and Jefferson Laboratory, with applications in quantum simulation , non-Gaussian state characterization , and hybrid quantum technologies . Key contributions include the 2013 APS Fellowship for groundbreaking work on quantum frequency combs, NSF Distinguished Research Awards , and patents in quantum photonic devices. His group’s NSF-funded research (e.g., QLCI Preliminary Proposal, $3.2M; RAISE-EquIP, $750K) explores fault-tolerant quantum computing, machine learning integration, and microresonator-based entanglement. Pfister’s scientific awards include the 2013 UVA Distinguished Research Career Award and the 1996 JILA Clever Idea Contest Second Prize . His students and postdocs (e.g., Amr Hossameldin , Miller Eaton , Rajveer Nehra ) have published extensively on quantum tomography, cluster states, and photonic detector design. Pfister also serves on advisory and planning committees at UVA, emphasizing interdisciplinary collaboration across physics , engineering , and quantum information .
