Find Academic Supervisors

• Optical Communications
• Coherent Optical Systems
• Signal Processing
• +3 more

Bensu Baran is a doctoral researcher at the Technical University of Munich (TUM), affiliated with the Institute for Communications Engineering under the Professorship of Line Transmission Technology led by Prof. Norbert Hanik. She holds a B.Sc. in Electrical and Electronics Engineering from Koç University (Istanbul, Turkey) and an M.Sc. in Communications Engineering from TUM. Her research focuses on optical communication systems, including topics like carrier and phase recovery in coherent systems and power optimization in hybrid-amplified links. She has contributed to teaching, including courses on Optical Communication Systems and seminars on coding/cryptography in communications. Current research interests emphasize practical challenges in high-speed optical transmission, leveraging her background in signal processing and fiber optics.

• Computer Architecture
• Memory Systems
• Reconfigurable Computing
• +6 more

Ronald Dreslinski is a Professor in the Department of Computer Science and Engineering at the University of Michigan, College of Engineering. His work focuses on computer architecture, memory systems, and reconfigurable computing, with applications in machine learning, wireless communication, and autonomous systems. Research spans hybrid memory systems, fault-tolerant networks, and low-power processors Key technologies include PIM (Processing-in-Memory), systolic arrays, and Galois field accelerators His publications highlight trends in adapting reconfigurable architectures for sparse data, optimizing wireless communication decoders, and integrating neural networks with traditional circuit design. He mentors PhD students through weekly 1-on-1 meetings, project-specific sessions, and group presentations. The department emphasizes broadening participation in computing and student support through community initiatives.

Zeina AbdallahView profile

Research Fellow

• Thermal Engineering
• Materials Science
• Power Electronics
• +3 more

Zeina Abdallah is a Senior Research Associate at the School of Physics, University of Bristol, based in the HH Wills Laboratory. She specializes in advanced materials and thermal management systems, with a focus on high-power electronics and optoelectronic devices. Her research integrates semiconductor physics, thermal characterization techniques, and nanocomposite materials to enhance device performance and reliability. Her work spans thermal interface materials, ultra-wide bandgap semiconductors (e.g., Ga2O3), and diamond-based composites for power electronics. She also explores optical resonators and frequency comb generation for microwave applications. Her methodologies include thermoreflectance techniques, in-situ characterization, and nonlinear modeling of photonic components. Key contributions include optimizing thermal resistance in RF HEMTs, developing diamond-seeded CVD growth techniques, and advancing high-Q resonator technologies for precision signal generation. She collaborates with institutions like the Interface Analysis Centre and works alongside faculty members such as Prof. Martin Kuball and Prof. Paul May. Zeina’s research emphasizes interdisciplinary approaches, bridging materials science, electronics, and photonics to address challenges in next-generation power systems and high-frequency devices.

Joseph E. ShepherdView profile

Professor

• Explosion Dynamics
• Shock Waves
• Hypersonics
• +3 more

Joseph E. Shepherd is the C.L. "Kelly" Johnson Professor of Aeronautics and Mechanical Engineering at Caltech, specializing in explosion dynamics, shock waves, and hypersonic flows. His research examines extreme fluid mechanics phenomena through experiments and modeling, with applications to industrial safety, nuclear power, and aerospace systems. Professor Shepherd leads the Explosion Dynamics Laboratory, studying combustion, detonations, and fluid-structure interactions. His group has investigated high-profile accidents including the TWA Flight 800 crash and Fukushima nuclear disaster to improve safety protocols. Current work focuses on blast wave propagation, hypersonic flow physics, and energy conversion technologies. He currently advises graduate students in explosion dynamics and teaches courses in nonsteady gasdynamics.

Andreas WieserView profile

Professor

• Geospatial Engineering
• Geomatics
• Geodetic Monitoring
• +3 more

Prof. Andreas Wieser is a Full Professor of Geosensorics and Engineering Geodesy at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering, leading the Institute of Geodesy and Photogrammetry. His work focuses on advanced measurement systems for high-precision positioning, navigation, and geodetic monitoring of infrastructure and natural environments. Notable contributions include parameter estimation methods, quality control frameworks, and sensor optimization for applications like avalanche monitoring, railway deformation analysis, and CERN's Futur Circular Collider project. Education: PhD in Surveying from TU Graz (2001), Thesis: 'Robust and fuzzy techniques for parameter estimation and quality assessment in GPS' Habilitation at TU Graz (2007), Thesis: 'GPS based velocity estimation and its application to an odometer' Postdoc at University of Calgary (2003-2004) Research Interests: Development of multi-spectral LiDAR systems for material probing and distance measurement Integration of sensor technologies for environmental monitoring (e.g., snow depth analysis, hydroelectric dam deformation) High-precision geodetic infrastructure for large-scale projects like CERN's FCC Algorithmic advancements in point cloud registration, radiometric calibration, and uncertainty quantification Honors: 2006 Karl-Rinner Award (Austrian Geodetic Commission) 2003 Erwin-Schrödinger Fellowship (Austrian Science Fund) 2002 Josef Krainer Sponsorship (State of Styria) Grants & Labs: Alpine Metrology Lab: Long-range TLS and permanent GNSS for geomonitoring Leadership on CERN FCC Geodesy project Development of Comb-based multispectral LiDAR systems His work bridges geomatics with engineering challenges, emphasizing practical implementations of advanced sensor technologies across civil infrastructure, environmental science, and heritage preservation.

• Cardiovascular Engineering
• Biomedical Imaging
• Mechanobiology
• +5 more

Tzung Hsiai , Professor-in-Residence in the School of Medicine at University of California Los Angeles , is a leading researcher in cardiovascular engineering, biomedical imaging, and environmental health impacts on vascular systems. His work bridges mechanobiology with cutting-edge technologies like light-sheet microscopy, nanoengineered sensors, and machine learning for disease modeling. Key Grants : NIH R01s on shear stress, light-field imaging, and particulate matter effects; T32 training programs. Research Themes : Mechanotransduction in vascular repair, exercise-induced metabolic pathways, SARS-CoV-2 diagnostics, and CAR-NKT cell therapies. Technologies : Wearable impedance sensors for fatty liver detection, graphene oxide antigen-presenting platforms, and wireless cardiac pacemakers. His 2025-2024 publications highlight innovations in deep tissue sound printing, synthetic antigen-presenting cells, and AI-enhanced microscopy. Recent awards include the Maud Cady Guthman Chair in Cardiology (2018-2023). Collaborations span hematology, bioengineering, and nanotechnology. Scientific Awards Maud Cady Guthman Chair in Cardiology (2018-2023) Key Collaborations : Teams with Khademhosseini, Gao, Yang, and Zhou on biofabrication and AI-driven diagnostics.

Chang LiuView profile

Senior Lecturer

• Laser Spectroscopy
• Tomography
• Data-Driven Imaging
• +3 more

Dr. Chang Liu is a Senior Lecturer in Electronic Engineering at the University of Edinburgh's School of Engineering. He received his B.Sc. in Automation from Tianjin University (2010) and Ph.D. in Testing, Measurement Technology and Instrument from Beihang University (2016). Following postdoctoral research at Empa-Swiss Federal Laboratories, he joined the Agile Tomography Group at Edinburgh. His research focuses on laser spectroscopy, laser imaging, and data-driven imaging techniques for applications in reacting flow-field diagnostics and environmental monitoring. Key specialties include design of near/mid-infrared LAS sensing systems, development of high-sensitivity imaging methodologies, spectroscopic modeling, inverse problem solving, and embedded system design. His publications demonstrate a consistent focus on advancing tomographic imaging techniques, with recent work emphasizing machine learning integration, hardware acceleration, and industrial applications in aero-engine monitoring. Research consistently addresses challenges in spatial/temporal resolution enhancement and real-time system implementation. Dr. Liu teaches courses in Digital System Design, Analogue Circuits, and Embedded Systems. He leads multiple research projects including EPSRC-funded initiatives on laser imaging of turbine engine combustion species. His team collaborates with industrial partners to develop cutting-edge laser-based sensing solutions.

• Fluid Dynamics
• Biophysics
• Material Science
• +3 more

Dr. Mazi Jalaal is affiliated with the Faculty of Science at the University of Amsterdam. His research focuses on fluid dynamics, soft matter physics, and biophysics, particularly in the behavior of viscoplastic fluids, microdroplet dynamics, and biological systems like dinoflagellates. His work integrates experimental, computational, and theoretical approaches to study complex fluid phenomena and biological processes. Research interests include: Fluid dynamics in viscoplastic and yield-stress systems Microscale hydrodynamics and droplet behavior Biological fluid-structure interactions in microorganisms Optical and laser-induced fluid deformations Optimization of biological and engineered systems Recent publications highlight trends in droplet microswimmers, light-regulated biological systems, and computational modeling of bubble and filament dynamics. His work bridges fundamental physics with applications in biotechnology and material science. No scientific awards are explicitly mentioned in the provided texts. Collaborative efforts are evident in studies involving microbial systems, additive manufacturing, and rheological fluid behavior.

Omar SkalliView profile

Professor

• Cytoskeleton Dynamics
• Brain Tumor Biology
• Cell Motility
• +2 more

Dr. Omar Skalli is Professor of Biological Sciences at the University of Memphis College of Arts and Sciences and Director of the Integrated Microscopy Center. He holds a PhD in Molecular Biology from the University of Geneva and completed postdoctoral training at Northwestern University. Research investigates cytoskeletal regulation in brain tumor cells, examining how proteins like synemin and α-actinin influence glioblastoma proliferation, motility, and morphology. Additional interdisciplinary collaborations study cellular responses to novel biomaterials and advanced microscopy applications. Recent publications demonstrate advances in super-resolution microscopy techniques, neural scaffold engineering, and molecular mechanisms in neuro-oncology. Research consistently bridges cell biology with materials science and optical engineering.

• Database Information Management
• Big Data Management Systems
• Data Structures
• +3 more

John Tsaknakis is an Associate Professor at the Department of Electrical and Computer Engineering, School of Engineering, University of Peloponnese. He holds a PhD in Computational Geometry and Multidimensional Data Structures from the University of Patras (2004), following a diploma in Computer Engineering and Informatics (1996). His research focuses on Information Management in Databases, Big Data Systems, Data Structures, and Knowledge Mining in Web-based contexts. Since 2004, he has contributed to numerous research and development projects, particularly in software systems and data management. His work spans theoretical advancements and practical applications, including AI-driven labor market analysis, energy demand forecasting, and interoperable social protection frameworks. Research interests include database optimization, computational geometry, and leveraging big data for societal challenges. His publications reflect a blend of technical innovation and real-world problem-solving, with recent work addressing pandemic impacts on employment and AI’s role in reducing gender disparities. He is accessible in Building K on Mondays and Tuesdays, 8:00–9:00 AM, though prior arrangement is recommended. Dr. Tsaknakis collaborates on international projects, such as World Bank initiatives in social protection systems, and maintains active involvement in academic administration and teaching. His contributions to the field are further highlighted through his curriculum vitae and ongoing engagement in the academic community.

Younes Ra’diView profile

Assistant Professor

• Theoretical and Applied Electromagnetics
• RF and Microwave Engineering
• Antennas and Propagation
• +4 more

Younes Ra’di is an Assistant Professor at Syracuse University's College of Engineering and Computer Science, Department of Electrical Engineering. He holds a Sc.D. from Aalto University (2015). His research focuses on engineering electromagnetic wave-matter interactions, including metasurfaces, antennas, and artificial materials. He has pioneered new concepts in RF/microwave materials and wavefront manipulation, with experimental/theoretical work in nanophotonics and plasmonics. His interdisciplinary team secured the 2022 CUNY Interdisciplinary Research Grant. Education: Sc.D. in Electrical Engineering from Aalto University (2015). Research interests emphasize tailoring electromagnetic phenomena through advanced materials and structures. Key areas include broadband absorption systems, nonlinear metasurfaces, and time-domain photonics. His work bridges theoretical electromagnetics with applied engineering, addressing challenges in wireless communications and antenna design. Recent publications highlight breakthroughs in ultrathin absorbers, metasurface cloaking, and photonic time interfaces. Articles span Nature Communications, IEEE journals, and Physical Review series. Grants/Awards: 2022 CUNY Interdisciplinary Research Grant. Active in collaborative research with leading groups in light-matter interaction. He advises students in experimental/theoretical electromagnetics and leads projects on next-generation wireless systems. His lab develops functional metamaterials for applications in antennas, energy harvesting, and sensing.

• Semiconductor Physics
• Materials Science
• Nanotechnology
• +3 more

Thomas Griffiths is a Researcher at King's College London with a Doctor of Philosophy in History. His research focuses on semiconductor materials, nanotechnology, and optoelectronic devices, with a strong emphasis on advanced materials characterization and device optimization. Education: Doctor of Philosophy in History, King's College London. Research interests include the structural and optical properties of semiconductor nanomaterials such as InGaN quantum wells, GaN-based devices, perovskite nanocrystals, and metal-organic frameworks (MOFs). His work bridges materials science and applied physics, addressing challenges in high-speed telecommunications, optoelectronic component design, and nanomaterial synthesis. Articles highlight trends in: Optimization of semiconductor materials for high-performance electronics and photonics Development of advanced fabrication techniques for nanoscale devices Exploration of novel materials for next-generation optoelectronic applications No scientific awards or grants are explicitly mentioned in the provided texts. No formal advisees are listed.

Changyang LinghuView profile

Assistant Professor

• Biomedical Engineering
• Cell Biology
• Developmental Biology
• +5 more

Changyang Linghu, Ph.D., is an Assistant Professor in the Department of Cell and Developmental Biology at the University of Michigan. His research focuses on developing innovative tools for molecular recording, optogenetic control, and advanced imaging techniques to study cellular and neural dynamics. He is affiliated with the Spatial Biodynamics Lab and holds a B.Eng. from Tsinghua University and a Ph.D. from MIT. Education: Ph.D., Massachusetts Institute of Technology, 2019 B.Eng., Tsinghua University, 2013 Research Interests: Dr. Linghu’s work spans synthetic biology, neuroscience, and biomedical engineering. He designs novel fluorescent reporters and optogenetic tools to study intracellular processes, neuronal signaling, and complex biological systems. Key themes include molecular recording systems, spatially resolved imaging, and precision optogenetic control of single cells. Publications: His recent work emphasizes scalable gene regulation monitoring, high-speed microscopy innovations, and optogenetic technologies for neural circuit analysis. The research bridges engineering and biology, with applications in understanding cellular memory, signaling networks, and neural activity. Labs & Teams: The Spatial Biodynamics Lab focuses on developing next-generation tools for dynamic biological systems analysis, integrating molecular engineering, imaging, and computational methods.

Byung KimView profile

Professor

• Biophysics
• Condensed Matter Physics
• Nanotechnology
• +3 more

Byung Kim is a Professor in the Department of Physics at Boise State University, with affiliations in the Graduate Program in Biomolecular Science and the Biomedical Engineering graduate program. His research focuses on biophysics and condensed-matter experiments, particularly investigating self-assembled water chains in biomolecular interactions using cantilever-based optical interfacial force microscopy (COIFM). He develops COIFM biosensors for proteomic screening and explores humidity-dependent structural transitions in nanoscopic systems. Kim holds a Ph.D. in Physics from Seoul National University. His work bridges physics and biology, emphasizing nanoscale phenomena such as interfacial water dynamics, phase transitions, and sensor technology. His recent publications (2022) highlight experimental and theoretical advances in understanding water chain self-assembly, entropy-driven forces, and long-range condensation effects. Kim’s research also involves advanced atomic force microscopy (AFM) techniques, including high-speed imaging, force-feedback systems, and nanomechanical characterization of soft materials. His lab, located in Science Bldg Room 414, focuses on interdisciplinary applications of microscopy to biomolecular and biomedical challenges.

• Computer Vision
• Medical Imaging
• Deep Learning
• +4 more

Zhifeng Wang is a Professor at the National University of Defense Technology's School of Computer Science, specializing in computer vision, medical imaging, and artificial intelligence. His research spans multiple application domains with a recent focus on medical image synthesis, 3D reconstruction, and fluid dynamics simulation. Research interests include developing advanced AI techniques for medical imaging applications, particularly in vascular structure analysis and synthesis. His work bridges computer vision with healthcare applications, focusing on creating anatomically accurate 3D representations without invasive procedures. He has made significant contributions to diffusion models, neural radiance fields (NeRFs), and meta-learning frameworks for cross-domain applications. His publication record shows a clear progression from foundational work in graph algorithms and communications systems to cutting-edge medical AI applications. Recent work demonstrates expertise in combining state space models with diffusion techniques for medical image generation, showing particular strength in maintaining anatomical continuity in 3D vascular structures. While specific awards aren't documented in the provided information, his publications in top venues including CVPR 2025 indicate significant recognition in the computer vision community. His collaborative work spans multiple institutions and research domains, suggesting an active research group with diverse funding sources. His laboratory appears to focus on medical imaging AI, with particular emphasis on non-invasive diagnostic techniques. Current projects involve developing sophisticated diffusion models that can generate high-fidelity angiographic images from non-contrast inputs, potentially reducing patient exposure to harmful contrast agents.