Find Academic Supervisors

Adeline De MontlaurView profile

Associate Professor

• Computational Fluid Dynamics (CFD)
• Wind Energy
• Air Traffic Management
• +5 more

Adeline De Montlaur is an Associate Professor at the Universitat Politècnica de Catalunya (UPC) within the School of Telecommunications and Aerospace Engineering of Castelldefels (EETAC), affiliated with the Department of Physics. She leads research in numerical methods for fluid dynamics and their applications in renewable energy systems and air traffic management. Her academic career includes a PhD in Aerospace Science and Technology (UPC, 2009), an M.S. in Mechanical and Aerospace Engineering (SUNY Buffalo, 2003), and an Engineering degree from ENSICA (France, 2002). Roles: Academic Staff, Researcher at LACÀN Center for Numerical Methods. Research Interests: High-order CFD methods, wind energy optimization, multiphase flows, air traffic flow management, and planetary atmospheric dynamics. Her work bridges computational methodologies with practical applications, such as optimizing wind turbine efficiency using flow control techniques and analyzing thermally-driven winds on Mars. She has contributed to over 50 publications and projects like the European-funded WOW-CONTROL initiative for turbine optimization. Awards include the 2023 Best Paper Award in Atmospheric Sciences. Key projects include wind resource assessment near hydroelectric dams, delay management strategies in air traffic control, and analytical models for aviation emissions. Adeline collaborates with global institutions and industry partners to advance sustainable energy and transport systems.

• complex-valued neural networks
• classification
• pattern recognition
• +2 more

Igor Aizenberg is a Professor and Chair of the Department of Computer Science at Manhattan College (Riverdale, NY) since 2016. He holds a Ph.D. in Computer Science (1986) and M.S. in Mathematics (1982) from Dorodnicyn Computing Center (Moscow) and Uzhhorod National University (Ukraine), respectively. Ph.D. in Computer Science, Dorodnicyn Computing Center, USSR (1986) M.S. in Mathematics, Uzhhorod National University (1982) His research focuses on complex-valued neural networks (CVNNs) with multi-valued neurons (MVN), emphasizing classification , pattern recognition , intelligent image processing , and spectral techniques . He pioneered the MLMVN (Multilayer Neural Network with Multi-Valued Neurons), which excels in learning speed and generalization for nonlinear separability problems like XOR. His recent publications (2025-2016) highlight advancements in CVNNs for frequency domain image filtering , power system fault diagnosis , DC-DC converter monitoring , and CNNMVN (Convolutional Neural Networks with Multi-Valued Neurons). Key trends include edge detection , impulse noise filtering , and financial time series prediction . $300,000 NSF grant (2009-2012) Fulbright Specialist Awards (2014, 2015) Senior Member, IEEE Aizenberg has developed MATLAB simulators and executable tools for MLMVN and CNNMVN, freely available for non-commercial research. These tools address classification , regression , and multi-class problems . He has also contributed to books and tutorials on CVNNs, including the 2011 Springer monograph Complex-Valued Neural Networks with Multi-Valued Neurons .

Weigang WangView profile

Professor

• Condensed Matter Physics
• Spintronics
• Nanomagnetism
• +3 more

Weigang Wang is a Professor of Physics and Electrical and Computer Engineering at the University of Arizona, serving as Director of Graduate Studies. His research focuses on nanoscale spin and charge transport phenomena with direct applications in next-generation magnetic memory and logic technologies. His educational background includes a Ph.D. in Physics from the University of Delaware (2008). His research group specializes in voltage-controlled magnetism, spin-orbit torque effects, and magnetic tunnel junction engineering for ultra-low-power spintronic devices. Wang's experimental work bridges fundamental condensed matter physics and practical device engineering, emphasizing energy-efficient switching mechanisms through novel materials and nanostructure fabrication techniques including electron-beam lithography and self-assembly processes. His publications demonstrate consistent innovation in reducing switching energy barriers for nanomagnetic systems. His research trajectory shows increasing focus on antiferromagnetic spintronics, topological materials interfaces, and cryogenic-compatible magnetic memory since 2020, with significant contributions to voltage-controlled magnetic anisotropy and spin-transfer torque efficiency. Notable honors include: CSM Fellow (2024) University of Arizona Distinguished Scholar Award (2022) Department of Physics Outstanding Undergraduate Teaching Award (2018) NSF CAREER Award (2016) As Director of Graduate Studies, Wang oversees advanced degree programs while leading an experimental lab focused on magnetic device characterization and nanofabrication. His NSF-funded research explores voltage-mediated control of magnetic states, with implications for non-volatile memory and neuromorphic computing architectures. The lab maintains collaborations with national facilities for advanced characterization of spintronic materials.

Gil BubView profile

Associate Professor

• Cardiovascular Research
• Cardiac Dynamics
• Imaging Techniques
• +3 more

Gil Bub is an Associate Professor in the Department of Physiology at McGill University, focusing on cardiovascular research and cardiac dynamics. His lab develops advanced imaging and computational methods for studying excitable cell networks in heart and brain tissues. Current research involves high-speed microscopy technologies (Temporal Pixel Multiplexing, RAP imaging, remote focusing) and optogenetic techniques to control and image cardiac excitation patterns. Teaching includes the course Mathematical Models in Biology (BIOL 309) , with supplementary tools like cellular automata and logistic map iterators. Research themes explore excitable media, spiral wave dynamics, and real-time optical control of cardiac tissue. The lab combines bioengineered myocyte sheets, co-cultures, and whole-heart models with novel microscopy and simulation programs. Instrumentation projects include ultra-fast sensors, three-photon microscope prototypes, and parallel imaging systems for high-throughput screening. Optogenetics work collaborates with Emilia Entcheva's COOL lab to sensitize tissues to light control, enabling precise manipulation of wave patterns and rhythms. Lab members include postdocs, PhD/MSc students, and undergraduate trainees. Prior students have pursued careers in academia, medicine, and industry. Collaborators span institutions including Oxford, UBC, and industry partners like Cordin Scientific Imaging.

• Quality of Experience (QoE) of Internet applications
• Artificial intelligence and machine learning for communication networks
• Measurement and analytics of encrypted network traffic
• +5 more

Prof. Dr. Michael Seufert is a Full Professor and Chairholder at the University of Augsburg since October 2023, leading the Chair of Networked Systems and Communication Networks within the Faculty of Applied Computer Science. Previously, he served as a Private Lecturer at the University of Würzburg and completed his Habilitation in Computer Science there in 2023. His academic journey includes a PhD in Computer Science from the University of Würzburg (2017) with a thesis on Quality of Experience and Access Network Traffic Management of HTTP Adaptive Video Streaming, which earned him two prestigious Best Dissertation Awards. His research focuses on Quality of Experience (QoE) of Internet applications, artificial intelligence and machine learning for communication networks, measurement and analytics of encrypted network traffic, and data-driven proactive user-centric network management solutions. His work bridges theoretical foundations with practical applications in network monitoring, security, and performance optimization. Recent research has increasingly incorporated machine learning techniques to address challenges in network management, traffic analysis, and user experience assessment. Prof. Seufert's publication record shows a clear evolution from foundational work on QoE modeling and HTTP adaptive streaming toward more sophisticated applications of machine learning in network operations. His recent publications (2023-2025) demonstrate a strong emphasis on practical ML applications for network monitoring, security, and optimization, with particular attention to real-world constraints and performance requirements. The research spans multiple subfields including encrypted traffic analysis, explainable AI for network management, edge computing, and quality assessment for emerging applications. CNOM Young Professional Award of the IEEE Communications Society (ComSoc) Technical Committee on Network Operations & Management (CNOM) (2024) Best Dissertation Award 2018 of KuVS (Communication and Distributed Systems) special interest group Best Dissertation Award of the IEEE Communications Society (ComSoc) Technical Committee on Network Operations & Management (CNOM) Prof. Seufert actively supervises research projects and advises students through thesis projects and practical modules. His teaching portfolio includes Communication Systems, Management of Communication Networks, Practical Introduction to Internet-Technologies, and seminars on Networked Systems. He leads a research group focused on networked systems and communication networks, with current projects exploring machine learning applications in networking, as evidenced by the organization of the 3rd International Workshop on Machine Learning in Networking (MaLeNe 2025).

Scott HowardView profile

Assistant Professor

• Biomedical Photonics
• Fluorescence Microscopy
• Super-resolution Microscopy
• +5 more

Scott Howard is an Assistant Professor in the Department of Electrical Engineering at the University of Notre Dame’s College of Engineering. His research bridges biomedical optics, microscopy, and computational imaging, with a focus on developing advanced optical tools for diagnostic and biological research. Education PhD in Electrical Engineering from Princeton University (2008) Postdoctoral studies in Applied and Engineering Physics at Cornell University (2008–2011) BSEE from the University of Notre Dame (2003) Research interests span biomedical photonics , including: Super-resolution fluorescence microscopy techniques like Stepwise Optical Saturation (SOS) and Generalized SOS (GSOS). Adaptive optics and deep learning for enhancing microscope functionality. Multiphoton microscopy (MPM) and fluorescence lifetime imaging microscopy (FLIM) for 3D in vivo imaging. Mid-infrared spectroscopy for trace explosive detection. Diffuse optical imaging for non-invasive cancer diagnostics. His work has led to open-source software tools for low-noise microscopy and collaborations with biologists on applications ranging from neuroscience to plant toxicity studies . Students under his mentorship have received fellowships and awards, including the JenLab Young Investigator Award and Berry Family Foundation Graduate Fellowship. Recent publications highlight trends in zero-shot FLIM denoising , real-time diffuse optical tomography , and machine learning for high-speed biomedical imaging . These articles emphasize advancements in in vivo 3D imaging , mechano-metabolic cellular analysis , and optical property estimation in multi-layered tissues .

• Hydraulic Fluid Power
• Fluid Mechanics
• Positive Displacement Pumps
• +5 more

Massimo Rundo is an Associate Professor at the Polytechnic of Turin 's Department of Energy (DENERG) and coordinator of the Fluid Power Research Laboratory (FPRL) . With over 70 Scopus-indexed publications, his work focuses on modeling, simulation, and experimental validation of fluid power systems. Research Interests: Positive displacement pumps (gerotor, gear, vane, piston) Hydraulic valves (flow forces, pressure control) Mobile hydraulics (excavators, telehandlers) CFD and lumped parameter modeling Incomplete filling phenomena at high speeds Recent Publications analyze flow dynamics in pumps, vibration-based fault detection, and energy-efficient hydraulic architectures through 1D/3D simulations. He has coordinated industry-funded projects with companies like Casappa and Pierburg Pump Technology. Honors: MDPI Energies Editor's Choice (2018) SAE Excellence in Oral Presentation (2004) SAE Certificate of Appreciation (2000) Rundo teaches graduate courses in Mobile and Industrial Fluid Power and advises master's theses, while serving as Associate Editor for the International Journal of Fluid Power and committee member for major conferences including ASME/BATH Symposium and International Maha Fluid Power Conference.

Alexandros KapsalisView profile

Researcher

• Photonic Design
• Novel Optical Devices
• Silicon Photonics
• +5 more

Dr. Alexandros Kapsalis is a post-doc researcher at the Optical Communications Laboratory of the National and Kapodistrian University of Athens (NKUA), affiliated with the Department of Informatics and Telecommunications. He holds a PhD in Optical Communication Devices from the University of Athens (2010) alongside a B.S. (2002) and M.Sc. (2004) in Telecommunications. Research Interests: Photonic design, novel optical devices, silicon photonics, all-optical signal processing, semiconductor lasers, optomechanical systems, and system automation. Article Trends: Focuses on silicon/silicon germanium waveguides, quantum dot lasers, four-wave mixing, phase regeneration, and mid-infrared conversion. Keywords span Photonics , Telecommunications , and Nonlinear Optics . Service: Serves as a reviewer for IEEE and Elsevier journals, with 20+ publications in national and EU projects.

Michael JohnstonView profile

Professor

• Semiconductor Physics
• Solar Cells
• Ultrafast Optics
• +4 more

Michael Johnston is Professor of Physics at the University of Oxford's Department of Physics and a Fellow of Corpus Christi College since 2002. He leads a research group focused on high-frequency semiconductor devices, semiconductor charge dynamics, and spectroscopy, bridging fundamental physics with real-world applications in terahertz technology, semiconductor nanostructures, and perovskite optoelectronics. His educational background includes a PhD in Physics from the University of New South Wales (Sydney, Australia), where he researched electron behavior in quantum-confined systems. Prior to Oxford, he established a terahertz spectroscopy research program at the Cavendish Laboratory, University of Cambridge (1999-2002). Professor Johnston's research centers on charge dynamics in semiconductors and light-matter interactions , with three core thrusts: Terahertz Science : Developing instrumentation and theories for terahertz spectroscopy, radiation emission, and ultrafast modulation using semiconductor nanostructures Semiconductor Nanostructures : Investigating electron dynamics to create novel photonic devices like single nanowire terahertz detectors with picosecond switching Perovskite Optoelectronics : Pioneering vapor deposition methods for metal halide perovskites enabling efficient planar heterojunction solar cells His publication record (2002-2020) demonstrates consistent innovation in terahertz device engineering and perovskite solar cell technology, with high-impact contributions across fundamental charge-carrier dynamics, nanoscale device fabrication, and industrial-scale material processing for clean energy applications. His scientific excellence is recognized through: Harrie Massey Medal Friedrich Wilhelm Bessel Research Award IUMRS Somiya Award Clarivate Highly Cited Researcher status Professor Johnston actively mentors students through undergraduate physics tutoring at Corpus Christi College (covering Electromagnetism, Quantum Mechanics, and Condensed Matter Physics) while leading his research group. His key contributions include inventing single-nanowire terahertz detectors, ultrafast terahertz modulators, and vapor deposition techniques critical for industrial perovskite solar cell production. He directs Oxford's Terahertz Physics research group (www-thz.physics.ox.ac.uk), which integrates experimental and theoretical approaches to semiconductor charge dynamics, with strong industry connections for translating fundamental discoveries into photonic devices and solar energy solutions.

Carlos Portera-CailliauView profile

Professor

• Neuroscience
• Neurology
• Autism Research
• +3 more

Carlos Portera-Cailliau is a Professor at the David Geffen School of Medicine at University of California, Los Angeles (UCLA) , with joint appointments in the Departments of Neurology and Neurobiology . He co-directs the UCLA-Caltech Medical Scientist Training Program and is affiliated with UCLA’s Brain Research Institute , Integrated Center for Learning & Memory , and Neuroscience Theme . Dr. Portera-Cailliau earned a B.A. in Biochemistry & Cell Biology from UC San Diego (1990), followed by an MD-PhD from Johns Hopkins School of Medicine (1997). After neurology residency at Massachusetts General Hospital and Brigham & Women’s Hospital (2001), he conducted postdoctoral research at Columbia University and Cold Spring Harbor Laboratory. The Portera-Cailliau laboratory employs a symptom-to-circuit approach to study neurodevelopmental disorders like autism and Fragile X syndrome. Key research areas include sensory hypersensitivity , neuronal connectivity , and synaptic plasticity , using in vivo two-photon calcium imaging , patch-clamp electrophysiology , and head-fixed behavioral assays . Recent work explores GABAA receptor roles in cortical development and EPAC2 as a therapeutic target in Fragile X mice. Publications highlight neurodevelopmental circuit defects , excitation-inhibition imbalance , and interventions to restore plasticity in autism and Fragile X models. His lab also develops open-source tools like EZcalcium for calcium imaging analysis. Dr. Portera-Cailliau’s affiliations include UCLA’s Brain Research Institute , Integrated Center for Learning & Memory , and Neuroscience Theme . His research integrates behavioral assays , optogenetics , and chemogenetics to identify therapies for neuropsychiatric conditions.

• Optical Communication
• Fiber Optics
• Photonics
• +4 more

Magnus Karlsson is a Professor of Photonics at Chalmers University of Technology and serves as Deputy Dean of the Department of Microtechnology and Nanoscience (MC2), responsible for research and graduate education. He co-leads the fiber optics research group with Prof. Peter Andrekson and co-founded the Chalmers Center for Optical Communication (FORCE) in 2010 alongside Prof. Erik Agrell. Karlsson teaches courses in Wireless and Photonics System Engineering and Photonics and Lasers, and holds editorial leadership as Editor-in-Chief of the IEEE/Optica Journal of Lightwave Technology. His research centers on optical fiber communication systems with expertise in light propagation, polarization dynamics, and nonlinear optical effects. Current investigations focus on capacity-enhancing techniques including Voronoi constellation geometric shaping, silicon nitride integrated photonics for microwave applications, and machine learning-driven polarization sensing. His work bridges theoretical modeling of phase-noise channels with experimental validation of novel receiver architectures for deep-space communication through atmospheric turbulence. Recent publications reveal strong trends in overcoming nonlinear transmission limits through multidimensional modulation and MIMO processing for coupled-core fibers. His group pioneers integrated photonic solutions for high-frequency signal generation while advancing real-time network monitoring capabilities in operational fiber infrastructure. Key themes include power-efficient signaling, distributed sensing, and computational methods for channel compensation. Karlsson's leadership in the fiber optics group and FORCE drives collaborative research in next-generation optical networks. His editorial role and ECOC program committee membership position him as a key influencer in shaping global optical communication standards and disseminating cutting-edge research advancements.

Fabian IhleView profile

Researcher

• Software-Defined Networking (SDN)
• P4 Programming Language
• Time-Sensitive Networking (TSN)
• +3 more

Fabian Ihle is a Researcher & PhD Student at the Chair of Communication Networks , Department of Computer Science , University of Tübingen . He works on Software-Defined Networking (SDN) , P4 Programming Language , and MPLS Network Actions , focusing on Time-Sensitive Networking and Network Resilience . His research includes data plane programming , network protocol development , and high-speed switching using hardware like Intel Tofino. He has contributed to IETF Internet Drafts and presented at workshops including ReNeSys 2025 and IETF MPLS WG meetings. Academic Background : B.Sc. and M.Sc. in Computer Science from University of Tübingen (2021-2023) His publications address MPLS extensions , BIER-TE , and P4-based tools for traffic generation and runtime control. He actively participates in KuVS workshops and serves as a reviewer for journals like IEEE Transactions on Cognitive Communications .

• Space Physics
• Plasma Physics
• Geophysics
• +3 more

Ahmad Lalti serves as a Research Fellow at Northumbria University within the School of Engineering Physics and Mathematics, focusing on experimental space plasma physics and collisionless shock phenomena. His work bridges theoretical models with multi-spacecraft observational data to unravel fundamental processes in near-Earth space environments. His educational background includes a PhD awarded on May 31, 2024, with ongoing status indicated by an end date of December 31, 2099. Dr. Lalti's research spans Space Physics, Plasma Physics, and Geophysics with concentrated expertise in shock wave dynamics, particle acceleration mechanisms, and wave-particle interactions. His investigations particularly target Earth's bow shock structures, quasi-perpendicular collisionless shocks, and transient plasma phenomena using data from major space missions like Cluster, MMS, and THEMIS. This work has significant implications for space weather prediction and fundamental plasma theory. Analysis of his 2025 publications reveals a cohesive research trajectory examining non-stationary shock behavior, electron/ion acceleration through Fermi mechanisms, and wave instabilities in space plasmas. His studies consistently employ multimission datasets to correlate transient events like high-speed jets with relativistic electron acceleration, demonstrating sophisticated cross-mission data fusion techniques. No scientific awards were documented in the provided materials. Dr. Lalti maintains an extensive international collaboration network evidenced by co-authorship with researchers from Swedish Institute of Space Physics, University of Colorado, and multiple European institutions. His work appears in premier journals including Journal of Geophysical Research and Geophysical Research Letters, though no specific grant funding or student supervision details are disclosed. He operates within global space physics consortia analyzing data from NASA and ESA missions, contributing to shock physics working groups that coordinate multi-spacecraft observational campaigns across international agencies.

• Digital signal processing
• Wireless communications
• Signal processing
• +3 more

Xiaodan Pang is a Tenure Professor at Riga Technical University (RTU) specializing in cutting-edge photonics and communications research. Her work focuses on developing next-generation optical and wireless technologies for high-speed data transmission systems, with significant contributions to silicon photonics, terahertz communications, and integrated sensing and communication architectures. Her primary research interests include: Digital signal processing Wireless communications Signal processing Fiber optics Optoelectronics Photonics Professor Pang's recent publications demonstrate leadership in overcoming fundamental challenges in high-speed communications. Her 2025 work spans silicon photonics ring-resonator modulators for optical-amplification-free links, photonic terahertz chaos systems for secure ranging, and analog fronthaul solutions for 6G networks. Key themes include neural network equalization for ultra-high baudrate transmission, energy-efficient unamplified optical links, and integrated sensing-communication systems leveraging terahertz frequencies. This research directly addresses critical bottlenecks in data center interconnects, 6G mobile infrastructure, and secure high-precision wireless applications. Her technical profile is documented through ORCID (0000-0003-4906-1704), Scopus (54407301300), and Web of Science (D-5032-2015) identifiers, with active professional engagement via LinkedIn.

• Synaptic transmission
• Optical Microscopy
• Computational neuroscience
• +5 more

Robin Angus Silver is Professor of Neuroscience at University College London (UCL), a Wellcome Trust Principal Research Fellow, and Fellow of the Royal Society. He has held leadership roles since 2011 and is renowned for groundbreaking work in synaptic transmission, neural computation, and neuroinformatics. Education: B.Sc. in Physical Sciences (1st Class Hons), Coventry Polytechnic (1986) Ph.D. in Physiology, UCL (1990) Dr. Silver's research focuses on information processing in cerebellar and neocortical circuits. He discovered fundamental properties of central excitatory synapses, elucidated how neurons perform arithmetic operations, and pioneered tools like NeuroConstruct and NeuroML for 3D neuronal modeling. His development of high-speed two-photon microscopy with acousto-optic lenses revolutionized in vivo imaging. His work spans synaptic physiology, computational modeling, and neuroinformatics infrastructure. He has contributed to open-source platforms like OpenSourceBrain, enabling browser-based visualization and simulation of neural models. Awards include Royal Society Fellowship (2017), Wellcome Trust Principal Research Fellowships (2011, 2016), and ERC Advanced Investigator Award (2011). Scientific Awards Fellow of the Royal Society (2017) Wellcome Trust Principal Research Fellowship (2011, 2016 renewal) European Research Council Advanced Investigator Award (2011) Hungarian Academy of Sciences Distinguished Guest Scientist Fellowship (2012) Multiple Wellcome Trust Senior/Principal Research Fellowships Wellcome Trust Research Career Development Fellowship (1996) Dr. Silver has organized international workshops including OpenSourceBrain meetings and INCF Congress events. He serves on steering committees for neuroinformatics initiatives and evaluation panels for funding bodies like the Wellcome Trust and US BRAIN Initiative.