Find Academic Supervisors

• Biomedical Instrumentation
• Medical Technology
• Clinical Engineering
• +3 more

Jan Olav Høgetveit is an Associate Professor in the Department of Physics at the University of Oslo (UiO), within the Faculty of Mathematics and Natural Sciences. He also serves as Head of Research & Development in the Department of Biomedical and Clinical Engineering at Rikshospitalet, Norway’s national hospital. His work bridges physics and clinical practice, focusing on medical instrumentation. Education: Bachelor of Electronic Engineering (Technical Cybernetics), Oslo University College, 1993 Master of Electronics, University of Oslo (Department of Physics), 1997 Ph.D. in Physics (Technology Applications for Medical Devices), University of Oslo, 2008 Research Interests: Høgetveit specializes in biomedical instrumentation and clinical engineering, particularly in surgical technology and wireless communication impacts on medical devices. His work addresses challenges like real-time physiological monitoring during heart-lung machine use, non-invasive blood glucose detection, and bioimpedance-based viability assessment of organs. He emphasizes interdisciplinary collaboration between engineering and medicine to enhance patient safety and surgical outcomes. Scientific Contributions: His research trends span bioimpedance applications in ischemia/reperfusion injury, machine learning for surgical decision support, and electrosurgery safety. He has explored ventilator optimization during pandemics and implant-related thermal risks. Contributions highlight both hardware development (e.g., optically isolated current sources) and software innovations (e.g., neural networks for viability prediction). Awards: No scientific awards explicitly mentioned in the text. Advising & Grants: Høgetveit received a 1998–2001 research council scholarship. As Head of R&D since 2001, he oversees translational projects. No formal advisees/students listed, though he collaborates extensively with teams on device development and clinical trials. Labs & Teams: Affiliated with UiO’s Department of Physics and Rikshospitalet’s Biomedical and Clinical Engineering department. Active in the Electronics research group at UiO. Engages with multidisciplinary teams addressing surgical instrumentation and physiological monitoring challenges.

Francesco FedeleView profile

Associate Professor

• Nonlinear Wave Phenomena
• Coastal and Ocean Engineering
• Fluid Mechanics
• +11 more

Francesco Fedele is an Associate Professor at Georgia Tech, concurrently affiliated with the School of Civil and Environmental Engineering and the School of Electrical and Computer Engineering. He holds a Ph.D. in Civil Engineering from the University of Vermont (2004) and a Laurea (magna cum laude) from the University Mediterranea, Italy (1998). His research spans nonlinear wave phenomena, coastal engineering, fluid mechanics, and sustainable ocean energy, with a focus on rogue waves, stereo imaging, and computational methods. His work has been published in high-impact journals like Physical Review Letters and IEEE Transactions series. Research Interests include wave turbulence, signal processing for biomedical and radar applications, and mathematical modeling of tidal energy systems. Notable contributions involve analyzing extreme waves in the Mediterranean and North Sea, contributing to maritime safety and hurricane impact studies. Publications reflect expertise in fluid dynamics, oceanography, and computational methods. Recent work addresses the geometrical phases of nonlinear systems and interval-based finite element analysis under uncertainty. His research has been featured in Georgia Tech news for applications in rogue wave prediction and structural engineering. Dr. Fedele’s academic positions and collaborations include postdoctoral research at NASA Goddard Space Flight Center (pre-Georgia Tech tenure). No specific awards are explicitly listed in the provided text, though his work has garnered media attention for its societal impact.

Marcus BotacinView profile

Assistant Professor

• Malware Analysis
• Hardware-Assisted Security
• Antivirus Technology
• +4 more

Marcus Botacin is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University (TAMU), USA. Previously, he held positions as Visiting Assistant Professor (2022-2024) and Lecturer at the Federal University of Paraná (Brazil). His research focuses on malware analysis, hardware-assisted security, and antivirus technology. He earned his Ph.D. in Computer Science from UFPR (2021), M.Sc. from UNICAMP (2017), and B.Sc. in Computer Engineering from UNICAMP (2015). Education: Ph.D., Computer Science, Federal University of Paraná, Brazil (2021) M.Sc., Computer Science, University of Campinas, Brazil (2017) B.Sc., Computer Engineering, University of Campinas, Brazil (2015) Research Interests: Botacin's work addresses challenges in malware detection (static/dynamic methods, sandboxing), hardware-enhanced security mechanisms (e.g., branch monitoring), and antivirus internals. He emphasizes practical solutions and ethical considerations in cybersecurity, advocating for culturally aware threat models (e.g., Brazilian financial malware studies). Publications & Trends: His recent work explores adversarial ML attacks on malware detectors, HPC-based detection frameworks, and automated malware generation risks. He frequently publishes in top venues like ACM CCS, USENIX Security, and IEEE TDSC. Awards: Top-3 Best Ph.D. Thesis in Computer Security (Brazilian Computer Society, 2022) Best PhD Thesis Award from UFPR (2022) MLSec Evasion Challenge 1st place (2021/2020) Advising & Grants: Supervises 15+ students at TAMU and leads NSF-funded projects (e.g., $523K grant for HPC malware detection frameworks). Serves on 21+ conference program committees and reviews for over 50 journals. Lab & Projects: Develops Corvus (public malware analysis sandbox) and explores hardware-accelerated AV solutions like Terminator and HEAVEN.

Peter ChinView profile

Professor

• Machine Learning
• Artificial Intelligence
• Differential Geometry
• +8 more

Professor Peter Chin is a Professor of Engineering at Dartmouth College and Director of the Learning, Intelligence + Signal Processing (LISP) Lab. He holds affiliations with the Thayer School of Engineering and serves as Associate Editor of IEEE Transactions on Computational Social Systems. His research bridges signal processing, machine learning, game theory, and differential geometry, with applications in cybersecurity, healthcare, and network analysis. Education: Bachelor of Science in Electrical Engineering, Computer Science, and Mathematics from Duke University (1993) Doctor of Philosophy in Mathematics from MIT (1998) Research Interests: Chin’s work focuses on fundamental questions at the intersection of machine learning, game theory, and signal processing. His lab explores topics like adversarial defense mechanisms, topological machine learning, and computational neuroscience. Recent projects include cybersecurity resilience modeling, medical imaging enhancements via GANs, and multi-agent reinforcement learning frameworks. Publications Trends: His most recent articles address cutting-edge challenges in cybersecurity (e.g., autonomous defense systems), medical AI (e.g., Alzheimer’s classification), and adversarial robustness. A notable 2025 focus is on quantitative resilience modeling for cyber defense, reflecting growing demand for AI-driven security solutions. Awards: Faculty Scholar Award, Duke University George Sherred III Award, Duke University Julia Dale Memorial Award, Duke University Grants & Leadership: Recipient of DARPA cybersecurity research grants Co-chair for SPIE/DSS Cyber Sensing Conference (2013–2020) Developed novel compressive sensing microscope for biological imaging LISP Lab: This interdisciplinary lab pioneers projects like nFlip (multiplayer security game models) and topological machine learning frameworks, emphasizing practical applications of theoretical advancements.

Peter BishopView profile

Professor

• Software Reliability
• Software Fault Tolerance
• Design Diversity
• +10 more

Peter Bishop is a Professor at the Centre for Software Reliability, City St George's, University of London, where he holds a joint chair in Systems and Software Dependability with Robin Bloomfield. He is also Chief Scientist at Adelard, part of NCC Group, providing consultancy and research in computer safety and dependability. He holds BSc and MSc degrees in Physics and is a Chartered Engineer and Member of the IET. University: City St George's, University of London School: College of Engineering, Design and Physical Sciences Department: Centre for Software Reliability Academic Rank: Professor Email: p.bishop@citystgeorges.ac.uk Research Interests: Peter Bishop's research spans software fault tolerance, design diversity, software reliability prediction, statistical testing, system safety and security, assurance case methodologies, and their application in industrial contexts including autonomous vehicles and nuclear systems. He has led research for the UK nuclear industry on smart device assessment and participated in European projects on critical control system safety. Publication Trends: His recent publications focus on conservative confidence bounds for software reliability, safety assurance under uncertainty, integration of testing and formal proof, and security-informed safety. A recurring theme is the development of rigorous, evidence-based methods to justify software dependability in safety-critical domains, particularly where operational and test profiles differ or failure data is scarce. Scientific Awards and Recognition: While specific awards are not listed, his long-standing contributions are evident through his professorship, leadership at Adelard, and active role in safety-critical research. He is a Chartered Engineer and Member of the IET. Advising and Grants: Although specific students are not named, his leadership in major research projects such as DISPO and DIRC (2000–2006) indicates significant supervisory and mentoring roles. He has secured funding from sources including the Leverhulme Trust (UnCoDe project) and a consortium of nuclear industry stakeholders (EDF Energy, NDA, AWE, etc.) under the CINIF Nuclear Research Programme. Labs and Research Teams: He is a key member of the Centre for Software Reliability at City St George's and leads research activities at Adelard. He collaborates extensively with Robin Bloomfield, Lorenzo Strigini, Bev Littlewood, and others on software dependability and safety assurance research.

• Optics
• Visual Sciences
• Medical Optics
• +3 more

Sergio Barbero is an Associate Researcher at the Visual Optics laboratory of the Instituto de Óptica (CSIC), Spain, under the supervision of Prof. Susana Marcos. He holds a BSc in Physics from the University of Zaragoza (1999) and a PhD in Visual Sciences from the University of Valladolid (2004), which earned him the Doctoral Thesis Extraordinary Award (2005). His research focuses on optical aberrations, intraocular lens design, wavefront measurement techniques, and gradient-index modeling of ocular structures. Barbero has collaborated with international groups at Indiana University (USA), University of Houston (USA), and Australian institutions. His work includes pioneering studies on crystalline lens tomography, corneal ablation algorithms, and novel wavefront sensing methods. He has authored 16 peer-reviewed publications and contributed to a US patent on wavefront reconstruction techniques. His research spans three core areas: (1) intraocular lens design using analytical tools, (2) gradient-index modeling of the human eye, and (3) in vivo measurement of crystalline lens aberrations. He has secured grants from the Spanish government (I3P-CSIC), NIH (USA), and Fulbright fellowships. Barbero has presented 33 scientific talks/posters, including invited lectures, and maintains an h-index of 9. His work bridges fundamental optics with clinical applications in ophthalmology.

Johannes ZeiherView profile

Professor

• Quantum Computing
• Atomic Physics
• Quantum Matter Interfaces
• +3 more

Prof. Johannes Zeiher is a Professor at Ludwig Maximilian University (LMU) and leads the independent research group Quantum Matter Interfaces . His work focuses on studying quantum systems of laser-cooled atoms coupled to optical resonators, aiming to advance quantum error correction and quantum many-body physics. He secured €3.3 million from Germany's BMBF for the SNAQC project on scalable neutral atom quantum computing. Research interests include quantum interfaces between atoms and photons, Rydberg arrays in optical tweezers, and hybrid architectures for quantum technologies. His group explores non-destructive measurements, feedback mechanisms, and entanglement generation in quantum systems. Key experimental tools include high-resolution microscopy and resonator-coupled systems. Prof. Zeiher's lab is located at the Max Planck Institute of Quantum Optics, collaborating on cutting-edge quantum technologies. He holds dual affiliations with LMU and the MPQ, advancing both theoretical and experimental frontiers in quantum computing and quantum simulation. His work bridges atomic physics, quantum optics, and condensed matter systems to realize practical quantum devices.

• Carbon Nanotubes
• Graphene
• Nanomaterials
• +3 more

Paola Ayala is a Professor at the Faculty of Physics of the University of Vienna, specializing in the Electronic Properties of Materials . Her research focuses on nanomaterials, particularly carbon nanotubes, graphene, and carbyne, exploring their electronic, magnetic, and optical properties. She leads the Doctoral College Advanced Functional Materials (DCAFM) (2020–2025), fostering interdisciplinary training in nanotechnology. Key research areas include nitrogen doping of carbon nanotubes, magnetic coupling in nanoclusters, and sensor applications of nanocomposites. She has pioneered studies on confined carbyne synthesis and the environmental stability of 1D nanocarbons. Ayala’s work bridges theoretical modeling (e.g., DFT simulations) and experimental techniques like Raman spectroscopy and XPS analysis. Her 2017 Matilde Hidalgo Prize recognizes contributions to nanomaterials science. She actively promotes STEM equity, co-authoring reports on women in physics in Austria and Ecuador. Ayala has supervised over 97 publications since 2007, with recent emphasis on functional nanomaterials for energy, sensing, and biomedical applications. Notable projects include developing flexible formaldehyde sensors and investigating magnetic properties of iron nanoclusters. She collaborates globally, presenting at conferences like the 2024 UNIVIE NanoteC Symposium and the 2023 International Nanotechnology Congress.

• Information visualization
• Visual analytics
• Eye tracking
• +10 more

Tanja Blascheck is a PostDoc Researcher and Margarete von Wrangell Fellow at the Institute for Visualization and Interactive Systems (VIS) at the University of Stuttgart. Her work focuses on visual analytics , eye tracking , and microvisualizations for smartwatches and other wearable devices.

Joseph TalghaderView profile

Professor

• Optics
• Microelectromechanical Systems
• Nanoelectromechanical Systems
• +7 more

Joseph Talghader is the Cymer Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, where he has been a faculty member since 1997, progressing from Assistant to Full Professor. He leads the Optical Micro+Nanosystems Group and holds appointments in the College of Engineering. Dr. Talghader's educational background includes a B.S. in Electrical Engineering from Rice University, followed by an M.S. (1993) and Ph.D. (1995) from UC Berkeley, where he was awarded an NSF Graduate Fellowship. Prior to joining academia, he worked at Texas Instruments and Waferscale Integration in process development and memory design. His research spans optics and micro/nano-mechanical systems with particular focus on infrared detectors, optical coatings, heat transfer mechanisms, and microsensors. His group has developed groundbreaking technologies including the highest sensitivity uncooled thermal detectors and the first tunable multispectral thermal detectors. Recent work has expanded into applications for glacial ice analysis and high-power laser systems. His research integrates theoretical modeling with advanced fabrication techniques, particularly atomic layer deposition. Analysis of his 15 most recent publications reveals a consistent focus on infrared technologies, optical coatings, and thermal phenomena. His work demonstrates strong interdisciplinary connections between electrical engineering, materials science, and optical physics, with increasing emphasis on practical applications in environmental sensing and high-power laser systems. Among his notable recognitions are three 3M Faculty Awards and being a Finalist for the Minnesota Cup for entrepreneurs. He has served on various program committees including the Army Research Office Electronics Division strategic planning panel and has chaired multiple IEEE conferences. Dr. Talghader actively mentors students and postdocs, with numerous publications listing junior researchers as lead authors. His group has secured significant research funding, though specific grant details aren't provided in the source material. He currently serves as an Editor for the NPG journal Light: Science and Applications, demonstrating his standing in the optics research community. The Optical Micro+Nanosystems Group maintains strong industry and interdisciplinary collaborations, with research spanning from fundamental materials properties to practical device implementation. Current projects focus on improving infrared detection technologies, developing advanced optical coatings for high-power applications, and exploring novel sensing mechanisms for extreme environments.

• Optical fiber technology
• Photonics
• Biosensors
• +5 more

Dr. Stephen Warren-Smith is a Senior Research Fellow at the Future Industries Institute, University of South Australia (UniSA), where he conducts cutting-edge research in optical fiber technology and photonics. He is affiliated with the Laser Physics and Photonic Devices Laboratories within UniSA STEM (Science, Technology, Engineering and Mathematics), and serves as a Research Degree Supervisor for graduate students. Dr. Warren-Smith's primary research interests span optical fiber technology, photonics, and biosensors, with a particular focus on developing novel fiber optic sensing platforms for biomedical and environmental applications. His work encompasses microstructured optical fibers, fluorescence sensing, and the integration of machine learning techniques for enhanced sensor performance. He has made significant contributions to the fields of harmonic generation in optical fibers, NV center-based quantum sensing, and multimode fiber applications. Analysis of Dr. Warren-Smith's recent publications reveals a strong trend toward developing sophisticated fiber optic sensing platforms with diverse applications. His work demonstrates increasing integration of advanced materials (like diamond with NV centers) and computational methods (particularly deep learning) to overcome traditional limitations in optical sensing. The research spans fundamental physics of light-matter interactions in fibers to practical applications in medical diagnostics, environmental monitoring, and industrial process control. A notable pattern is the development of multi-parameter sensing capabilities within single fiber platforms, enabling simultaneous measurement of various physical and chemical properties. Dr. Warren-Smith has secured significant research funding including ARC Future Fellowships (FT200100154), ARC Discovery Projects (DP190102896), and support from the Australian National Fabrication Facility (Optofab Node) utilizing Commonwealth and South Australian State Government resources. His research has received substantial citation counts, with several papers cited multiple times in Web of Science and Scopus. Dr. Warren-Smith leads research activities within the Laser Physics and Photonic Devices Laboratories at UniSA STEM. His team specializes in the design, fabrication, and characterization of advanced optical fiber devices, with particular expertise in microstructured optical fibers, suspended core fibers, and integrated photonic sensing platforms. The laboratory maintains strong connections with the Australian National Fabrication Facility (Optofab Node) for advanced device fabrication capabilities and collaborates extensively with institutions including RMIT University, University of Melbourne, University of Adelaide, and international partners in China.

• Continuum Mechanics
• Material Modelling (Composites and metamaterials)
• Computational Modelling
• +6 more

Zia Javanbakht is a Senior Lecturer at the School of Engineering and Built Environment , Griffith University , specializing in Mechanical Engineering and Industrial Design . As a chartered engineer with a PhD in Mechanical Engineering, he contributes to research in Continuum Mechanics , Material Modelling (composites and metamaterials), and Computational Modelling . He is affiliated with the Australian Centre for Precision Health and Technology (PRECISE) and has been involved in projects related to additive manufacturing, auxetic materials, and composite structures. Research Interests include the development of advanced computational models for material behavior, with a focus on auxetic structures , triply periodic minimal surfaces (TPMS) , and additively manufactured composites . His work addresses challenges in residual stress analysis , multiscale modelling , and machine learning applications in material deformation mechanisms. Scientific Awards Fellow (FHEA) of Higher Education Authority, Dublin, Ireland (since 2021) Key Funded Projects span collaborations with Gilmour Space Technologies (CRC-P grant for rocket fuel tanks), Bond University (concrete sensor testing), and internal Griffith University grants for equipment like the Transient Plane Source Thermal Conductivity Analyser . He actively supervises PhD and Master’s students in topics such as polymer-matrix composites , auxetic timber structures , and additive manufacturing failure models . Collaboration Networks include the AuxeticsLab and partnerships with industry leaders like Stoddart Group Pty Ltd and ATL Composites . His teaching portfolio covers Constitutive Material Modelling (7015ENG) and Computational Statics and Dynamics (7252ENG), reflecting his expertise in computational techniques and structural analysis.

• Semiconductor Optoelectronics
• Nanotechnology
• Quantum Structures
• +3 more

Dr. Michael Fraser is a researcher affiliated with the Department of Electronic Materials Engineering at the Research School of Physics and Engineering, Australian National University. His work focuses on semiconductor optoelectronics and nanotechnology, particularly in quantum structures and terahertz technology. He collaborates with prominent researchers like Professor Chennupati Jagadish and Professor Hoe Tan. University: Australian National University Department: Electronic Materials Engineering Email: michael.fraser@riken.jp Dr. Fraser's research spans quantum structures , carrier dynamics , and terahertz emission . His publications highlight excitons , trions , quantum wires , and defect analysis in semiconductors . Techniques like micro-photoluminescence , X-ray absorption spectroscopy , and ion implantation are central to his studies. Key areas: Semiconductor optoelectronics, nanotechnology, quantum physics, material science, and terahertz technology. Recent trends: Carrier confinement in quantum wells, defect characterization in indium nitride, and polarization-sensitive terahertz detection.

Hongsheng HuView profile

Lecturer

• Data Privacy
• Machine Unlearning
• Trustworthy Machine Learning
• +5 more

Dr. Hongsheng Hu is currently a Lecturer in the School of Information and Physical Sciences at the University of Newcastle, Australia, specializing in the Data Science and Statistics focus area. Prior to this position, he served as a Postdoc Research Fellow at CSIRO's Data61 from October 2022 to August 2024. His academic journey includes a Doctor of Philosophy in Computer Systems Engineering from the University of Auckland in New Zealand, establishing his foundation in advanced computing systems. Dr. Hu's research centers on enhancing the trustworthiness of machine learning systems, with particular emphasis on identifying critical privacy vulnerabilities within machine learning models and developing robust defensive strategies. His work spans several key domains including adversarial machine learning (30% focus), statistical data science (30% focus), and data and information privacy (40% focus). He investigates membership inference attacks, machine unlearning techniques, and privacy-preserving mechanisms in federated learning environments. His research addresses fundamental challenges in AI security, exploring how machine learning models can be compromised through sophisticated privacy attacks and developing methods to mitigate these vulnerabilities while maintaining model utility. Analysis of Dr. Hu's publication record reveals a strong research trajectory focused on machine learning security and privacy. His work consistently addresses vulnerabilities in machine learning systems, particularly examining membership inference attacks, machine unlearning mechanisms, and privacy-preserving techniques in federated learning. The research spans top-tier venues including IEEE Security & Privacy, USENIX Security, NDSS, NeurIPS, IJCAI, AAAI, and WWW, demonstrating both technical depth and recognition by the research community. His publications show an evolving focus from foundational privacy attacks to developing more sophisticated unlearning techniques and robust defense mechanisms, with increasing citation counts indicating growing impact in the field. Active Program Committee member for USENIX Security, NDSS, ICLR, IJCAI, WWW, ICDM, ECML, and PKDD Invited reviewer for IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Dependable and Secure Computing (TDSC), IEEE Transactions on Pattern Analysis and Machine Intelligence (IPAMI), and ACM Computing Surveys (CSUR) Dr. Hu currently serves as Course Coordinator for STAT6020 and STAT2020 Predictive Analytics at the University of Newcastle. As an academic supervisor, he co-supervises one PhD student working on 'Identifying and Mitigating Vulnerability in Recommender Systems' at Macquarie University. His research collaborations span multiple countries, with significant publication counts in Australia (18), China (12), New Zealand (10), and the United States (7), reflecting an active international research network focused on AI security challenges.

Kexin LiView profile

Assistant Professor

• Semiconductor Device Physics
• GaN Device Modeling
• Nanoscale Electronic Materials
• +3 more

Kexin Li is an Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University since August 2023. She earned her Ph.D. in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign in 2022, followed by a postdoctoral position at Columbia University. Education: Ph.D., Electrical and Computer Engineering, University of Illinois Urbana-Champaign (2022) M.Eng., Computer Engineering, New York University (2019) MSc., Analog and Digital IC Design, Imperial College London (2014) B.Eng., Electronic Science and Technology, Southeast University (2012) Her research focuses on semiconductor device physics and modeling for high-power, high-frequency applications, with particular expertise in wide bandgap materials like GaN. She develops frameworks for technology-circuit co-design that bridge nanoelectronics, device physics, and circuit implementation. Current work emphasizes cryogenic device modeling for quantum computing interfaces and ultra-wideband RF systems. Analysis of her recent publications reveals a strong focus on GaN HEMT characterization, device-circuit co-design methodologies, and cryogenic operation for quantum applications. Her work spans fundamental semiconductor physics, advanced TCAD simulation, and practical circuit implementation for next-generation communication systems. Scientific Recognition: Selected as 2022 EECS Rising Star Editor's Pick in Journal of Applied Physics (2022) for GaN HEMT modeling work Professor Li actively mentors graduate and undergraduate researchers, currently advising five Ph.D. students and four MS/UG students. Her research group collaborates with institutions including AFRL and focuses on creating a collaborative, diverse environment for developing new electronic materials and systems. She teaches courses including Analog and Digital Circuits (EEE 335) and Fundamentals of Solid-State Devices (EEE 436).