Find Academic Supervisors

• Quantum Technologies
• Imaging
• Sensing
• +6 more

Professor Daniele Faccio is Professor of Quantum Technologies at the University of Glasgow's School of Physics & Astronomy since December 2017. He also serves as adjunct professor at the University of Arizona and was elected Fellow of the Royal Society of Edinburgh in 2017. Previously, he was at Heriot-Watt University (2010-2017) and has held visiting positions at MIT and ICFO, Barcelona. Professor Faccio leads the Extreme Light Group, focusing on quantum technologies applied to imaging and sensing. His research spans quantum-enhanced imaging through complex media, photon transport in biological tissues, and analogue gravity phenomena where intense laser pulses create artificial black holes and 'expanding universes' in laboratory settings. His work bridges fundamental physics with practical applications in biomedical imaging, security, and quantum information processing. Recent publications reveal a strong trend toward quantum-enhanced imaging techniques, machine learning applications in optical sensing, and biomedical applications of advanced optical technologies. His research integrates quantum optics, computational imaging, and photonics to develop novel sensing modalities with applications ranging from non-invasive medical diagnostics to quantum information processing. Professor Faccio has received numerous prestigious awards including the Philip Leverhulme Prize in Physics (2015) and the Royal Society of Edinburgh Senior Public Engagement Medal (2017). He was an ERC fellow from 2012-2017 and a Marie-Curie fellow at ICFO, Barcelona. As principal investigator, Professor Faccio has secured significant research funding supporting his interdisciplinary team. His work on quantum imaging, analogue gravity, and computational optics has attracted substantial grant support from major research councils. He actively mentors postdoctoral researchers and PhD students in the interdisciplinary field spanning physics, engineering, and computational science. The Extreme Light Group maintains state-of-the-art laser laboratories with capabilities in ultrafast optics, quantum optics, and computational imaging. Current projects focus on quantum-enhanced imaging for biomedical applications, non-line-of-sight imaging through scattering media, and exploring fundamental physics through optical analogues of gravitational phenomena.

• Flexible and Stretchable Electronics
• Wearable Biosensors
• Antennas
• +4 more

Dr. Shanmuga Sundar Dhanabalan is an Adjunct Senior Fellow in the School of Engineering at RMIT University, specializing in flexible/stretchable electronics, wearable biosensors, and photonics. His research focuses on smart medical devices like Smart Mattresses for aged care and Smart Eye Patches for chronic eye disease management. He collaborates extensively with industry and holds roles in research supervision and curriculum development. **Affiliations**: Functional Materials and Microsystems Research Group, RMIT University (Melbourne, Australia). **Research Interests**: Wearable sensors, optical communications, photonics, antennas, and sustainable nanomaterials. His work bridges materials science with healthcare technologies, emphasizing practical industry applications. **Awards**: Fondecyt Postdoctoral Fellowship (2018), TEQIP Doctoral Scholarship (2013), and fellowships with the Optical Society of India and Computer Science Teacher Association. **Supervision & Grants**: Active in mentoring postgraduate research projects (e.g., smart sensors, bioelectronic devices). His publications span over 60 peer-reviewed articles in journals like Optical and Quantum Electronics and Renewable and Sustainable Energy Reviews . **Labs/Teams**: Engaged in cross-disciplinary teams developing wearable health monitoring technologies and sustainable materials for electronics.

• Biomedical Engineering
• Nanotechnology
• Microelectronics
• +5 more

Professor Omid Kavehei is a Professor of Intelligent Microsystems in the Faculty of Engineering at the University of Sydney, serving as Deputy Head of the School of Biomedical Engineering. Previously, he held roles as a Research Fellow at the University of Melbourne and Lecturer at RMIT University. His research focuses on biomedical microsystems, nanotechnology, and brain-inspired hardware for healthcare applications, particularly epilepsy monitoring and seizure prediction. Education: PhD (specific institution not explicitly stated) His work bridges nanoelectronics and healthcare, aiming to develop low-power, brain-inspired devices for sensory perception and medical diagnostics. Key interests include neuromorphic engineering, wearable sensors, and AI-driven medical systems. Awards include the Ramaciotti Biomedical Research Award (2021), Microsoft AI for Accessibility Grant (2019), and multiple teaching/research excellence awards from the University of Sydney. His recent work explores neuromorphic cytometry for cell analysis, edge AI for ECG/EEG diagnostics, and closed-loop neurostimulation systems. Collaborations include the Sydney Nano Institute, Brain and Mind Centre, and industry partners like Microsoft. Current research students are advancing topics like bio-inspired algorithms for seizure detection, hardware-friendly machine learning models, and flexible sensor systems for aquatic environments. Grants include funding for neurophysiology platforms, quantum sensors, and semiconductor design. Labs/teams: Involved in the Centre for Drug Discovery Innovation and collaborations across engineering, neuroscience, and clinical domains.

Daniel HellerView profile

Professor

• Cancer Nanotechnology
• Biomedical Engineering
• Drug Delivery
• +3 more

Daniel Heller is a Professor at Cornell University's Graduate School of Medical Sciences and Head of the Cancer Nanotechnology Laboratory at Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College. His interdisciplinary work develops nanotechnologies to revolutionize cancer research, diagnosis, and treatment through engineering innovation. Education: Bachelor of Arts in History, Rice University (2000) PhD in Chemistry, University of Illinois at Urbana-Champaign (2010) Damon Runyon Cancer Research Foundation Postdoctoral Fellowship, MIT Koch Institute (2012) Dr. Heller pioneers cancer nanotechnology with three core research pillars: precision nanomedicines for targeted drug delivery (including blood-brain barrier-penetrating carriers), AI-powered diagnostic sensors for early cancer detection via implantable/wearable platforms, and nanosensors accelerating drug discovery. His lab integrates machine learning with quantum-defect-modified carbon nanotubes to detect multi-analyte cancer fingerprints in serum, enabling real-time biomarker monitoring for high-risk patients and treatment response assessment. Analysis of his recent publications reveals a strategic shift toward clinical translation , with 2021-2023 work focusing on ovarian cancer detection systems and brain metastasis therapies. His Nature Biomedical Engineering (2022) study demonstrates how AI-enhanced nanosensors achieve unprecedented sensitivity in liquid biopsies, while his Nature Materials (2023) paper establishes a mechanistic foundation for nanocarrier-mediated CNS drug delivery—highlighting convergence of nanotechnology, computational biology, and oncology. Scientific Awards: College of Liberal Arts and Sciences Young Alumni Award, University of Illinois (2024) Life Sciences Invention of the Year, UM Ventures (2023) American Institute for Medical and Biological Engineering (AIMBE) Fellow (2021) Pharmacology Teaching and Mentoring Award, Weill Cornell Graduate School (2020) CRS Nanomedicine Junior Faculty Award and American Cancer Society Research Scholar (2018) Pershing Square Sohn Prize (2017) Kavli Fellow, National Academy of Science (2015) Dr. Heller actively mentors graduate students in Pharmacology and Physiology programs, evidenced by his 2020 Teaching Award. His research is funded by competitive grants including the American Cancer Society Research Scholar award and Pershing Square Sohn Prize, supporting high-risk translational projects like implantable sensor clinical validation and next-generation nanocarrier development for treatment-resistant cancers. The Heller Lab operates as a multidisciplinary engine within MSKCC's Sloan Kettering Institute, combining engineers, chemists, and biologists with clinical collaborators. Current initiatives focus on translating ovarian cancer detection platforms to human trials and developing closed-loop therapeutic systems that auto-adjust dosing based on real-time biomarker feedback—positioning nanotechnology at the forefront of precision oncology.

Evert van NieuwenburgView profile

Assistant Professor

• Quantum Physics
• Machine Learning
• Condensed Matter Physics
• +6 more

Dr. Evert van Nieuwenburg is an Assistant Professor at Leiden University, affiliated with both the Leiden Institute of Advanced Computer Science (LIACS) and the Leiden Institute of Physics (LION). His research bridges the fields of Quantum Physics , Machine Learning , and Condensed Matter Physics , with a focus on quantum algorithms, reinforcement learning, and quantum game development (e.g., Quantum TiqTaqToe ). He actively contributes to the Applied Quantum Algorithms (aQa) initiative and leads the QuantumPlayed subgroup for quantum games and education. Research Interests: AI-driven quantum experiment control, quantum machine learning, variational quantum circuits, and quantum games for education and intuition-building. Publications: 15+ peer-reviewed works spanning quantum error correction, phase transitions, reinforcement learning in quantum systems, and quantum dot array simulations. Community Engagement: Developer of educational quantum games, open science advocate, and active participant in interdisciplinary initiatives. Selected Trends: His work demonstrates AI's transformative role in quantum physics, from decoding error-correcting codes with graph neural networks to merging reinforcement learning with quantum control systems. Labs & Initiatives: Affiliated with the Applied Quantum Algorithms (aQa) initiative and co-founder of QuantumPlayed , where quantum mechanics meets game theory to engage diverse audiences.

• Computational Engineering
• Metamaterials
• Quantum Optics
• +12 more

Professor Jensen Tsan Hang Li is a Professor of Computational Engineering and Metamaterials at the University of Exeter, within the Faculty of Environment, Science, and Economy, a role he commenced in July 2024. He previously held professorial and senior academic positions at the Hong Kong University of Science and Technology (HKUST), the University of Birmingham, and City University of Hong Kong. Education: BEng in Electrical and Electronic Engineering, University of Hong Kong (1998) MPhil in Physics, Hong Kong University of Science and Technology (2000) PhD in Physics, Hong Kong University of Science and Technology (2004) His research spans computational engineering, metamaterials, quantum optics, acoustics, and nanophotonics, with strong interdisciplinary links to machine learning and quantum technologies. His work has been featured in numerous news outlets, highlighting breakthroughs in quantum holography, acoustic cloaking, and time-varying orbital angular momentum via metasurfaces. Although no specific publications are listed in the source text, his research output is extensive and centers on quantum control, wave manipulation, and novel material design. His recent work explores virtualized metamaterials, 3D-printed acoustic wormholes, and loss-induced quantum effects. Scientific Awards: Croucher Senior Research Fellowship (2022) Elected Member, The Hong Kong Young Academy of Sciences Professor Li actively supervises postgraduate students (PhD and Masters), engages in consultancy, editorial work, and keynote speaking, and welcomes media and research collaboration opportunities. He has also contributed to sustainable development goals related to quality education, sustainable cities, and industry innovation. He conducted postdoctoral research at UC Berkeley and Imperial College London, supported by the Croucher Foundation, underscoring his international research profile.

Saptarshi DasView profile

Associate Professor

• Two-Dimensional Materials
• Semiconductor Devices
• Field-Effect Transistors
• +5 more

Saptarshi Das is an Associate Professor in the Department of Engineering Science and Mechanics within the College of Engineering at Pennsylvania State University. His research focuses on cutting-edge semiconductor technology, particularly in the realm of two-dimensional materials for next-generation electronic devices. Das maintains an active research program with numerous publications in high-impact journals including Nature, Nature Electronics, and Nature Communications. Dr. Das's research interests center around two-dimensional materials, semiconductor devices, and nanoelectronics with applications in AI hardware and computing systems. His work explores the fundamental properties and applications of materials like transition metal dichalcogenides (MoS 2 , WSe 2 ), graphene, and other 2D materials for creating novel electronic devices that can overcome limitations of traditional silicon-based technology. His research spans from fundamental material science to practical device implementation, with particular emphasis on developing energy-efficient computing solutions. Analysis of Dr. Das's recent publications reveals a strong focus on 2D material-based transistors, 3D integration techniques, and novel computing architectures. His work demonstrates significant advancements in p-type 2D transistors, monolithic 3D integration, and biomimetic sensor systems. The research shows a clear trajectory toward developing non-silicon computing platforms that could revolutionize AI hardware and low-power electronics. Dr. Das leads an active research group with multiple PhD students and collaborators working on semiconductor device fabrication, characterization, and integration. His laboratory likely has strong connections with Penn State's Materials Research Institute and other interdisciplinary research centers focused on advanced materials and semiconductor technology. His research has attracted significant attention, with multiple mentions in university news and science media outlets highlighting breakthroughs in 2D computing and electronic tongue technology.

• Quantum Sensors
• Quantum Gravimetry
• Quantum Magnetometry
• +4 more

Professor John Close is a Professor and Head of the Department of Quantum Science within the Research School of Physics and Engineering at the Australian National University (ANU). He has held this professorship since 2008 and previously served as Deputy Director of the School from 2012 to 2016. His leadership roles include Chair of the ANU Defence Working Group and Deputy Chair of ANU Academic Board (2015-2017), alongside being a Senior Fellow of the Higher Education Academy. His educational background includes: PhD in Physics from the University of California, Berkeley (1991) Postdoctoral Fellowship at the University of Washington, Seattle (1991-1994) Alexander von Humboldt Fellowship and Max Planck Research Fellowship at the Max Planck Institut für Strömungsforschung, Göttingen (1994-1998) Close's research centers on harnessing quantum fields to develop advanced quantum sensors for fundamental physics and interdisciplinary applications. His experimental and theoretical work spans quantum gravimetry, magnetometry, and Bose-Einstein condensate systems, with direct applications in mapping archaeological sites, volcanoes, aquifers, and mineral deposits. He actively explores quantum wavelet representations, higher-dimensional information processing, motion simulation, and biological quantum sensing through extensive collaborations with Earth Science, Biology, and Industry partners. Analysis of his recent publications reveals a dominant focus on compact mobile quantum sensing platforms, atom interferometry innovations, and sensor fusion techniques. His work bridges quantum physics with practical navigation, geophysical surveying, and environmental monitoring solutions, emphasizing real-world deployment of quantum technologies for precision measurements in gravimetry and inertial navigation. His scientific recognition includes: Alexander von Humboldt Fellowship (1994-1998) Queen Elizabeth II Fellowship (2000) National Teaching Award for Research Led Education (2006) As a former member of the Australian Research Council College of Experts (2015-2018), Close has significantly influenced national research funding while securing grants for interdisciplinary quantum projects. His educational leadership as Deputy Director of the Research School of Physics and Engineering (2012-2016) demonstrates commitment to research-led teaching, recognized by his national teaching award. Close leads the Atom Laser Research Group, driving experimental work in quantum sensor development and Bose-Einstein condensate applications. His team focuses on translating quantum phenomena into deployable technologies for defense, resource exploration, and environmental monitoring through industry and international academic partnerships.

David EggerView profile

Associate Professor

• Halide Perovskites
• Electronic Structure Theory
• Molecular Dynamics
• +6 more

Prof. Dr. David Egger is an Associate Professor at the Technical University of Munich (TUM) , leading the Associate Professorship of Theory of Functional Energy Materials under the TUM School of Natural Sciences . He joined TUM in 2019 as a Rudolf Mößbauer Professor and was promoted to Associate Professor in 2023. His work focuses on atomistic theories of energy materials , particularly solar cells , using electronic-structure and molecular-dynamics techniques to study molecules , solid-state materials , and nanoscale interfaces . His research interests span Halide Perovskites , Density Functional Theory , Machine Learning in Materials Science , and Optoelectronic Properties . Recent publications highlight advancements in machine-learning force fields for predicting dielectric properties and ion migration in energy materials, alongside studies on perovskite surface dynamics and phonon effects in solar energy conversion. Scientific Awards : Sofja-Kovalevskaja Award (2017) Best Thesis Award of TU Graz (2015) Koshland Prize (2014) Erwin Schrödinger Fellowship (2014) DOC Fellowship (2010) Teaching and Leadership : Prof. Egger teaches Computational Materials Physics and Advanced Topics in Theory of Functional Energy Materials . He serves as Executive Director of the Atomistic Modeling Center , fostering interdisciplinary research in energy materials.

Sandra Diaz PierView profile

Researcher

• Computational Neuroscience
• High Performance Computing
• Machine Learning
• +3 more

Dr. Sandra Diaz Pier is a Scientific Lead at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre , Germany. Specializing in computational neuroscience , high performance computing (HPC) , and machine learning , she bridges neuroscience and advanced computational methods through her research. Education: B.Sc. in Electronic Systems Engineering, Mexico M.Sc. in Computer Science (focus: machine learning, quantum computing), Mexico Second M.Sc. in Electrical Engineering, Ontario, Canada Ph.D. in Computer Science, Germany (2021) Her research focuses on modeling and simulating brain dynamics and plasticity at multiple scales, leveraging HPC to accelerate large-scale neural network simulations. She actively contributes to EU projects like the Human Brain Project (HBP) , Virtual Brain Cloud , and EBRAINS 2.0 , emphasizing infrastructure development and educational training. Her work includes open-source tools such as the NEST simulator , The Virtual Brain , and L2L , enabling efficient parameter exploration and multiscale co-simulation frameworks. The 15 most recent publications highlight her interdisciplinary approach, spanning topics from quantum computing in biomolecular simulations to neural plasticity algorithms and cloud-based brain modeling . These articles reflect her expertise in integrating machine learning , multi-scale simulation , and HPC infrastructure for neuroscience challenges, including seizure propagation, Parkinson’s disease progression, and swarm intelligence in spiking networks. She leads technical coordination in projects like EBRAINS and serves as a task leader in the HBP infrastructure work package , while also organizing workshops and hackathons for open-source tools. Her role involves supporting domain scientists through methodological research and workflow optimization for brain simulations.

Hideyuki SuzukiView profile

Professor

• Nonlinear Dynamics
• Hybrid Systems
• Many-Body Dynamics
• +5 more

Hideyuki Suzuki is a Professor at the Department of Information and Physical Sciences , Graduate School of Information Science and Technology , Osaka University , where he has been employed since April 2016. His research spans nonlinear dynamics , hybrid systems , and many-body dynamics , with applications to power systems , brain modeling , and epidemic networks . 2001 : Ph.D. in Mathematical Engineering and Information Physics, University of Tokyo 1998 : M.Eng. in Mathematical Engineering and Information Physics, University of Tokyo 1996 : B.Sc. in Mathematics, University of Tokyo His research interests focus on nonlinear dynamical systems , particularly those with discontinuities or large-scale interactions , such as chaotic billiards , hybrid systems , and spatio-temporal chaos . He explores computational applications in machine learning (e.g., chaotic Boltzmann machines ), epidemiology (e.g., vaccine allocation models ), and power grid stability . The 15 most recent articles highlight his work in photonic computing , nonlinear sampling algorithms , and chaotic dynamics in engineering and biology . Key trends include interdisciplinary applications of nonlinear mathematics to renewable energy , neuroscience , and epidemic spread . Scientific awards include: 2022 Osaka University Prize 2018 JSIAM Best Paper Award for Hamiltonian Monte Carlo (2017) He leads the Nonlinear Mathematics Course laboratory, which accepts graduate and undergraduate students. His team investigates hybrid dynamical systems , chaotic computation , and real-world modeling in fields like traffic dynamics and epidemic networks . Research is supported by grants from JST CREST and ALCA-Next programs.

Manuel WimmerView profile

Professor

• Model-Driven Software Engineering
• Digital Twins
• Model-Driven Engineering
• +5 more

Manuel Wimmer is a Full Professor and Head of the Department of Business Informatics – Software Engineering at Johannes Kepler University Linz, Austria. He also serves as the Program Director for the Business Informatics master's program since 2019. His academic leadership extends to representing JKU Linz in the AutomationML society and leading significant research initiatives. Dr. Wimmer received his Ph.D. and Habilitation from TU Wien. His academic journey includes: Research associate at the University of Malaga, Spain Visiting professor at the University of Marburg, Germany Visiting professor at TU Munich, Germany Assistant professor at the Business Informatics Group (BIG), TU Wien, Austria Professor Wimmer's research focuses on Model-Driven Software Engineering and its applications, particularly in the emerging field of Digital Twins . His work bridges theoretical foundations with practical industrial applications, with special emphasis on model transformations, runtime modeling, and the integration of artificial intelligence techniques into model-driven approaches. More recently, he has been exploring the intersection of model-driven engineering with quantum computing, investigating how modeling principles can be applied to quantum software development. His recent publications reveal a strong trend toward Digital Twin engineering, with approximately 40% of his 2023-2025 publications focusing on various aspects of Digital Twin technology. Another significant strand of his work involves the application of AI and machine learning techniques to enhance model-driven engineering processes. The emergence of quantum software engineering as a research direction is also notable in his most recent publications, demonstrating his ability to identify and explore cutting-edge research frontiers. From 2017-2023, Professor Wimmer led the Christian Doppler Laboratory on Model-Integrated Smart Production (CDL-MINT), where he developed engineering approaches for digital twins. He is also the co-author of the influential book "Model-driven Software Engineering in Practice" (2nd edition, 2017). Professor Wimmer is actively involved in the organization of major scientific events including the IEEE International Conference on Quantum Software (QSW) and the International Conference on Engineering Digital Twins (EDTconf), demonstrating his leadership in these emerging research communities. His research has practical applications across various domains including smart cities, industrial automation, tunneling/construction, and quantum computing. The MATISSE project represents a significant multi-partner effort to develop a framework for federated digital twins of industrial systems.

• Process Mining
• Anomaly Detection
• Blockchain
• +3 more

Ko, Jonghyeon is a researcher affiliated with the Ulsan National Institute of Science and Technology (UNIST) , specifically the Department of Materials Science and Engineering within the College of Natural Science and Engineering. His work spans multiple disciplines including process mining, anomaly detection, blockchain technology, AI computing, and environmental engineering. His research interests include: Anomaly detection in business process event logs Blockchain-based systems for nuclear/radioactive waste management AI computing using neuromorphic devices Statistical leverage and information-theoretic approaches to process mining Optimization of autonomous vehicle safety systems Recent publications demonstrate expertise in developing formal languages for data quality simulation, probabilistic trace alignment methods, and practical tools for anomaly detection like AIR-BAGEL. While no explicit scientific awards are mentioned in the text, his work has been published in venues such as Information Systems , npj Unconventional Computing , and Expert Systems with Applications .

Michelle Yvonne SimmonsView profile

Professor

• Quantum Computing
• Semiconductor Physics
• Nanotechnology
• +4 more

Professor Michelle Simmons is the Director of the ARC Centre of Excellence in Quantum Computation and Communication Technology at the University of New South Wales (UNSW Sydney). Her work focuses on advancing silicon-based quantum computing through atomic precision engineering, including projects on 2-qubit gates and logical qubit architectures. Involves cryogenic measurement and microwave spin control Collaborates with Silicon Quantum Computing Pty. Ltd. Her research spans fundamental quantum mechanics, device fabrication in CMOS cleanrooms, and error correction for scalable quantum systems. Recent publications highlight trends in quantum dot arrays, spin readout sensitivity, and interdisciplinary applications of quantum technologies. Professor Simmons received the Esther Hoffman Beller Lectureship (2022) for her contributions to qubit manufacturing. She leads a dedicated team at UNSW, working toward the development of high-fidelity quantum processors and exploring the intersection of quantum materials and computational innovation.

• Parallel File and Storage Systems
• Modular Supercomputing
• Resource Disaggregation and Virtualization
• +6 more

Sarah Neuwirth is a tenured Professor for Computer Science at Johannes Gutenberg University Mainz (JGU) and a Visiting Researcher at the Jülich Supercomputing Centre. She manages JGU's High Performance Computing (HPC) division, coordinates regional/national HPC activities, and represents JGU in NHR, Gauss-Allianz, and HPC committees. Education : PhD (Dr. rer. nat.) in Computer Science (2018), Heidelberg University Diplom in Computer Science (2012), University of Mannheim Bachelor of Science in Computer Science (2010), University of Mannheim Research Interests : Parallel File and Storage Systems Modular Supercomputing (resource disaggregation/virtualization) Performance Engineering High Performance Computing Networking Reproducible Benchmarking Parallel I/O Publications Trends : Her work focuses on HPC performance modeling, parallel I/O optimization, modular supercomputing, network characterization, and reproducible benchmarks. Key themes include resource disaggregation, automated workflows, and data-intensive distributed applications. Scientific Awards : 2023 PRACE Ada Lovelace Award for HPC ZONTA Science Award 2019 Grants & Leadership : She leads the High Performance Computing division at JGU, participated in European DEEP projects, and serves on SC conference committees.