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Andrey SukhorukovView profile

Professor

• Photonics
• Metasurfaces
• Quantum Imaging
• +5 more

Professor Andrey Sukhorukov is affiliated with the Australian National University (ANU) , working in the Department of Electronic Materials Engineering . His research focuses on photonics , metasurfaces , and nonlinear optics , with applications in quantum imaging and flat optics . He contributes to cutting-edge projects like the ARC Centre of Excellence for Transformative Meta-Optical Systems and collaborates globally on nanophotonic devices and quantum information processing . Academic Rank: Professor Department: Electronic Materials Engineering University: Australian National University Research Interests: Sukhorukov specializes in metasurface engineering , dielectric nanophotonics , and quantum optical systems . His work bridges fundamental physics and applied engineering , particularly in light manipulation at the nanoscale and quantum imaging technologies . Article Trends: Recent publications emphasize quantum imaging , metamaterial design , and integrated photonic systems . Topics include nonlinear metasurfaces , dielectric waveguide engineering , and two-photon interference in chip-based platforms. Supervision: Registered to supervise research students, Sukhorukov contributes to advancing next-generation optical technologies through mentorship and collaborative projects. Labs & Collaborations: He collaborates with institutions like Optica Publishing Group and IEEE, and is involved in multi-institutional initiatives, including the ARC Centre of Excellence for Transformative Meta-Optical Systems .

• Data Mining
• Machine Learning
• Product Recommendation
• +5 more

Christian Desrosiers is a Research Professor at the Department of Software Engineering and IT, École de technologie supérieure (ÉTS), with a Ph.D. from Polytechnique Montréal. His research focuses on data mining, machine learning, and computer vision, particularly in medical imaging and optical network analysis. Research Units: Zebra Research Chair in Computer Vision for Industrial Applications, LIVE – Interventional Imaging Laboratory, LIVIA – Imaging, Vision and Artificial Intelligence Laboratory Research Axes: Intelligent and autonomous systems, Health technologies His expertise spans medical image analysis, domain adaptation, and computer vision. Recent publications highlight advancements in 3D point cloud learning, MRI harmonization, domain generalization, and real-time segmentation networks. Scientific awards include the prestigious Zebra Research Chair. He has co-supervised over 30 graduate students in topics ranging from optical network diagnostics to brain imaging and machine learning applications.

Patrick DesrosiersView profile

Adjunct Professor

• Dimensionality Reduction
• Dynamical Systems
• Mathematical and Computational Neuroscience
• +8 more

Patrick Desrosiers serves as an Adjunct Professor in the Department of Physics, Physical Engineering and Optics within Université Laval's Faculty of Science and Engineering, while conducting neuroscience research at the CERVO Brain Research Center. He co-directs Dynamica, a multidisciplinary complex systems research group, and participates in UNIQUE (neuroscience-AI integration) and CIMMUL (mathematical modeling applications). His academic training spans physics and mathematics at Université Laval, the University of Melbourne, and CEA-Saclay. Dr. Desrosiers' research centers on mathematical and computational neuroscience , with signature contributions in dimensionality reduction and network resilience analysis . His work bridges biological and artificial neural networks , zebrafish brain mapping , and neurovascular coupling using advanced techniques from spectral graph theory , random matrix theory , and dynamical systems . Current investigations focus on neural decoding under chronic stress and structural-functional relationships in brain networks. Analysis of his 2023-2025 publications reveals three dominant trajectories: (1) Low-dimensional representations for predicting cognitive decline and neural dynamics, (2) Network reconstruction methodologies applied to neuroscience and biodiversity, and (3) Development of computational tools like NeuroTorch for neural data analysis. His work consistently integrates mathematical rigor with biological relevance across species and scales. His recognition includes: Professeur étoile prize for exceptional teaching (Faculty of Science and Engineering, Université Laval, 2018) As Dynamica co-director, he mentors a research team comprising Antoine Légaré, Arthur Légaré, Benjamin Claveau, Jordan Charest, Marziyeh Pourmousavi, Pierre-Luc Larouche, Vincent Savard, Vincent Thibeault, and Zahra Yazdani. His collaborative framework connects physics, mathematics, and neuroscience to address fundamental questions in neural network organization, with funding evident through sustained publication output and lab operations. Dynamica Lab ( https://dynamicalab.github.io/ ) serves as the operational hub for his interdisciplinary research, maintaining active collaboration with CERVO Brain Research Center and international institutions.

Dharanidhar DangView profile

Assistant Professor

• Photonic Computing
• AI Hardware Acceleration
• Memristor-based Computing
• +3 more

Dharanidhar Dang serves as Assistant Professor in the Department of Computer Engineering at the College of AI, Cyber and Computing, The University of Texas at San Antonio (UTSA), where he advances hardware-centric artificial intelligence solutions through photonic and memristor technologies. Education Ph.D., Texas A&M University His research program bridges hardware innovation and biomedical applications, with primary focus on photonic computing architectures for real-time AI acceleration and memristor-based neuromorphic systems. He investigates critical challenges in hardware reliability (particularly degradation in memristor crossbars), energy efficiency in photonic accelerators, and co-design methodologies that optimize both algorithms and physical implementations. His biomedical work applies machine learning to macrophage biology, identifying predictive signatures for inflammatory diseases through computational immunology approaches. Analysis of his 2020-2025 publications reveals three dominant research trajectories: 1) Silicon photonic accelerators (P-ReTI, P-ReTiNA, SOFTONIC) targeting real-time and energy-efficient AI, 2) Memristor reliability frameworks addressing aging effects in deep learning hardware, and 3) Translational biomedical applications where machine learning deciphers macrophage behavior in inflammatory bowel disease and preterm infant lung conditions. This tripartite focus demonstrates exceptional versatility across hardware engineering and life sciences.

Andrea Di FalcoView profile

Professor

• Nano-photonics
• Metamaterials
• Plasmonics
• +6 more

Andrea Di Falco serves as Professor and Director of Impact at the School of Physics and Astronomy, University of St Andrews. He leads the Centre for Biophotonics and maintains an active research group focused on cutting-edge photonics research. His institutional affiliations include editorial work for Photonics and Nanostructures: Fundamentals and Applications journal since 2013. University of St Andrews - School of Physics and Astronomy (Current) Centre for Biophotonics (Current) Photonics and Nanostructures: Fundamentals and Applications (Editor since 2013) Professor Di Falco's research spans multiple photonics domains with particular expertise in nano-photonics, metamaterials, plasmonics, and biophotonics. His work bridges fundamental optical physics with practical applications, especially in metasurface technology and flexible photonics. The research demonstrates strong interdisciplinary connections between physics, materials science, and biomedical applications, contributing to multiple UN Sustainable Development Goals. His recent publication portfolio shows a clear trend toward increasingly sophisticated metasurface applications, with growing integration of machine learning techniques for photonic design. The research spans fundamental optical physics, novel material development, and practical biomedical applications, demonstrating remarkable breadth while maintaining technical depth in photonics. EPSRC Fellowship (2010) for flexible metamaterials and plasmonics research ERC Consolidator Grant (2019) for biophotonic applications of optically trapped photonic membranes Professor Di Falco actively supervises postgraduate research students and has led numerous significant research projects, including the current Holographic Integrated Photonic Platform project (2024-2025). His research program has secured substantial funding from EPSRC, European Research Council, and Medical Research Council, demonstrating strong recognition of his work's significance and potential impact. His group maintains the SynthOpt research website as a hub for their collaborative work. The SynthOpt research group operates within the School of Physics and Astronomy at St Andrews, maintaining strong connections with both theoretical and experimental photonics researchers. The team focuses on developing novel photonic structures with applications ranging from fundamental optics to biomedical sensing and human-computer interaction technologies.

John D CresslerView profile

Professor

• Silicon-Germanium Microelectronics
• RF/Microwave Circuits
• Semiconductor Devices
• +3 more

John D. Cressler is a Regents Professor and Schlumberger Chair in Electronics at the Georgia Institute of Technology's School of Electrical and Computer Engineering. He earned his B.S. in Physics from Georgia Tech (1984) and Ph.D. in Applied Physics from Columbia University (1990). After pioneering SiGe research at IBM (1984-1992), he joined academia at Auburn University before moving to Georgia Tech in 2002. His research specializes in silicon-germanium heterojunction technology, with focuses on: RF/microwave/mm-wave circuits Radiation effects in electronics Cryogenic semiconductor behavior Device reliability physics Compact modeling for SiGe devices His 700+ publications demonstrate consistent innovation in SiGe HBT design, radiation-hardened circuits, and millimeter-wave systems. Recent work emphasizes radiation tolerance for space applications, high-frequency circuit optimization, and novel fabrication techniques. Major Awards: IEEE Fellow (2001) IEEE Leon K. Kirchmayer Graduate Teaching Award (2011) ONR Young Investigator Award (1994) IEEE Third Millennium Medal (2000) He leads Georgia Tech's SiGe research group with extensive industry collaborations and teaches courses including ECE 3040 (Microelectronic Circuits), ECE 6444 (SiGe Devices), and interdisciplinary courses on science/religion dialogue.

• Integrated Circuits
• Signal Processing
• Data Analytics
• +4 more

Xin Li is a Professor in the Department of Electrical and Computer Engineering at Duke University and serves as the Associate Vice Chancellor at Duke Kunshan University. He holds a Ph.D. from Carnegie Mellon University (2005) and has held leadership roles in research consortia like the FCRP Focus Research Center and the Center for Silicon System Implementation (CSSI). His research bridges integrated circuits , machine learning , and cyber-physical systems , with applications in autonomous driving, battery lifetime prediction, and smart buildings. Education : Ph.D., Carnegie Mellon University (2005); M.S., Fudan University (2001); B.S., Fudan University (1998) His work emphasizes robust design methodologies for analog/RF circuits, data-driven predictive modeling , and Bayesian inference for high-dimensional variation spaces. Recent publications focus on generative adversarial networks for circuit design, multi-view imputation for incomplete data, and knowledge-driven autonomous systems . He has received numerous accolades, including the NSF CAREER Award (2012) , IEEE Donald O. Pederson Best Paper Awards (2013, 2016) , and IEEE Fellow (2017) . He has served as Editor for journals like IEEE Transactions on Biomedical Engineering and as Chair for conferences including ISVLSI and CAD/Graphics.

• Computer Architecture
• Machine Learning Systems
• Parallel Computing
• +3 more

Brian Towles is an Adjunct Assistant Professor in the Department of Electrical and Computer Engineering at Duke University. He earned his D.Phil. from Stanford University in 2005 and has contributed extensively to computer architecture and machine learning systems through research and publications. His work focuses on specialized hardware for molecular dynamics simulations and network-on-chip design. Research Interests: Dr. Towles specializes in computer architecture, particularly in network-on-chip design, event-driven computation, and low-latency interconnects for scientific computing. His research enables high-performance simulations in molecular dynamics and machine learning, with notable collaborations on Anton/TPU series supercomputers. Publication Trends: His publications span from 2001 to 2024, emphasizing Custom ASICs for scientific computing (Anton 2/3, TPUv4) Optimized interconnects and routing algorithms Event-driven and cycle-accurate simulation frameworks Resilient systems for large-scale machine learning

Diego ContrerasView profile

Professor

• Thalamocortical Networks
• Epilepsy
• Visual System
• +3 more

Diego Contreras, MD, PhD, is a Professor of Neuroscience at the Perelman School of Medicine, University of Pennsylvania, with dual affiliations in the Neuroscience and Bioengineering Graduate Groups. Education: M.D., University Autonoma of Madrid, Spain (1988) Ph.D., Laval University, Quebec, Canada (1996) His research centers on thalamocortical networks and epilepsy mechanisms , investigating inhibitory circuits in thalamus and visual cortex, thalamocortical synapse dynamics, and intrinsic electrophysiological properties using in vivo intracellular and optical recordings. His lab studies seizure initiation/propagation in neocortex and thalamocortical systems, bridging cellular mechanisms with network-level phenomena in sensory processing and epileptic disorders. Recent publications (2016-2018) demonstrate expertise in neural coding during gamma oscillations, spatiotemporal evolution of epileptiform activity, and thalamocortical communication. His work employs voltage-sensitive dye imaging and laminar recordings across rodent/cat models to address fundamental questions in visual processing and seizure dynamics, with significant contributions to understanding OFF-subregion inhibition and millisecond-precision temporal encoding. Dr. Contreras leads a laboratory focused on thalamocortical physiology, utilizing advanced electrophysiological techniques and collaborating with neuroengineers to translate basic findings into clinical epilepsy applications.

Stefano BonettiView profile

Associate Professor

• Ultrafast magnetism
• Spin dynamics in condensed matter
• Terahertz physics
• +3 more

Stefano Bonetti is an Associate Professor in the Department of Physics at Stockholm University , leading the Ultrafast Condensed Matter Dynamics Group . His research focuses on manipulating quantum materials using terahertz (THz) and near-infrared laser fields to study spin dynamics and ultrafast phenomena at nanoscale and femtosecond timescales. PhD in Materials Physics (KTH Royal Institute of Technology, Sweden) MSc in Engineering Physics (KTH) BSc in Technical Physics (Politecnico di Milano, Italy) Recent research efforts involve time-resolved X-ray microscopy to visualize spin currents and magnetization dynamics, leveraging facilities like free-electron lasers. His work bridges experimental physics and applied materials science, aiming to enhance energy efficiency in data storage technologies by understanding ultrafast spin-lattice interactions . Key scientific awards and grants: ERC Starting Grant (2017-2021) Wallenberg Academy Fellow (2018-2023) VR's free grant (2019-2023) International Career Grant (COFUND) (2015-2019) He has contributed to developing THz-based techniques for magnetic control and authored foundational work on spin-wave solitons and nonlinear magnetoelastic coupling . His group collaborates internationally, utilizing advanced synchrotron and free-electron laser facilities.

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +7 more

Luka Radic is a Researcher in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His work bridges theoretical and applied research in machine learning, with a focus on quantum machine learning , large language models , and fairness in AI systems.

Ryo IkeshiroView profile

Assistant Professor

• Sound Art
• Sonification
• Computational Creativity
• +3 more

Ryo Ikeshiro is an Assistant Professor at the School of Creative Media, City University of Hong Kong, and co-director of the spatial audio art/research unit SoundLab. His work bridges sound art, computational creativity, and cultural studies through immersive installations, algorithmic audio-visual systems, and sonification techniques. PhD in Creative Practice (Goldsmiths, University of London) MPhil in Music (University of Cambridge) BMus (King's College London) Ikeshiro's research interrogates the materiality of sound through: Multichannel Ambisonics and directional audio Neural network-driven temporal dislocation Sonification of climate data and historical soundscapes Machine learning for artistic interpretation Interplay of identity and technology East Asian ideophonic traditions His 2010-2024 publications and installations reveal cross-disciplinary engagement with: Fractal mathematics in audiovisual art Algorithmic composition systems Interactive installation technologies Sonic cartography Historical memory in sound Collaborative research frameworks SoundLab, which he co-directs, develops spatial audio research at the intersection of: Technical innovation Cultural representation Experimental pedagogy Public engagement International artistic exchange Practice-based research

Raymond H. CuijpersView profile

Associate Professor

• Cognitive Robotics
• Human-Robot Interaction
• Socially Assistive Robotics
• +5 more

Raymond H. Cuijpers is an Associate Professor at Eindhoven University of Technology in the Human Technology Interaction group. His research focuses on Cognitive Robotics , Human-Robot Interaction , and Artificial Intelligence for cognitive agents, with applications in healthcare robotics and aging population support. PhD in Physics of Man from Utrecht University (2000) Postdoctoral research at Erasmus MC Rotterdam and Radboud University Nijmegen Key research areas include: Developing socially intelligent robots with proper social cue interpretation Hybrid AI approaches for real-world complexity handling Visual-haptic perception integration in human motor control Service robots for COPD patient assistance (KSERA project) Rescue robotics and tele-operation applications Recent research output (2025) includes studies on: Personalization in human-robot communication Optimal lighting for elderly visual perception Human-robot bonding mechanisms Interactive sensorized platforms for homecare (GUARDIAN) Audiovisual temporal integration in virtual environments He coordinates large-scale European projects like GUARDIAN and previously KSERA, contributes to sustainable development goals through healthcare robotics, and serves on editorial boards of leading journals including International Journal of Social Robotics . His work spans both technical robotics development and human-centric interaction studies.

Huib ZuidervaartView profile

Researcher

• History of Scientific Instruments
• History of Academic Institutions
• Early Modern Science
• +3 more

Huib Zuidervaart is a Guest Researcher at the Royal Netherlands Academy of Arts and Sciences (KNAW), affiliated with the Huygens Institute for the History of the Netherlands. His career spans roles at institutions including Huygens ING, Utrecht University, and Leiden University, with expertise in the history of scientific instruments and academic institutions. Educated at VU University Amsterdam and Utrecht University, he holds a Ph.D. on Dutch astronomy in the Eighteenth Century. His research focuses on Early Modern Science, particularly the role of instruments, academic communities, and collections. Notable projects include co-editing the Collected Letters of Antoni van Leeuwenhoek and analyzing Dutch contributions to optical and astronomical innovations. His work bridges technical craftsmanship, institutional history, and cultural contexts of scientific advancement. Publications emphasize interdisciplinary connections between science, art, and society, such as exploring Vermeer’s Delft paintings through a scientific lens. His articles frequently address knowledge circulation in Dutch cities like Middelburg and Delft, highlighting regional networks of scholars, artisans, and collectors. Collaborations include international projects on instrument history and editorial roles in journals like ISIS . His writings span technical analyses, historical biographies, and critical reviews, reflecting a commitment to preserving and interpreting the material and intellectual heritage of early modern science.

Minoru KoyamaView profile

Assistant Professor

• Neurobiology
• Developmental Biology
• Animal Biology
• +4 more

Minoru Koyama is an Assistant Professor in the Department of Cell & Systems Biology at the University of Toronto Scarborough (UTSC). His research focuses on understanding the neural circuit mechanisms underlying behavioral development, particularly in zebrafish models. He employs advanced techniques such as optogenetics, voltage imaging, and CRISPR-based methods to study circuit maturation in the hindbrain and spinal cord. Education: Koyama holds a Ph.D. (2006), M.Sc. (2002), and B.Sc. (2000) in Biological Sciences from the University of Tokyo. Research Interests: His work investigates how neural circuits mature post-birth and contribute to complex behaviors, with applications to developmental brain disorders. His lab uses zebrafish as a model system, combining optics, genetics, and machine learning for behavioral analysis. Key projects include studying motor coordination development and refining imaging techniques like multi-plane microscopy and voltage indicators. Publications Highlight: Koyama’s recent work includes innovations in microscopy (e.g., HiLo speckle illumination) and genetic tools (e.g., TEMPO lineage tracing). These advancements enable precise observation of neural circuits and cellular dynamics. Lab & Recruitment: The Koyama Lab actively recruits graduate students and postdoctoral researchers. No specific grants are detailed, but his work reflects broad interdisciplinary collaborations in neuroscience and biotechnology. Labs/Teams: His lab focuses on developmental neurobiology, leveraging cutting-edge imaging and genetic engineering to explore neural circuit function across vertebrate development.