Find Academic Supervisors

Steven J. RehseView profile

Professor

• Biomedical Physics
• Analytical Chemistry
• Medical Diagnostics
• +3 more

Dr. Steven J. Rehse is the Department Head and Professor in the Department of Physics at the University of Windsor, specializing in Experimental Biomedical Physics and AMO (Atomic, Molecular, Optical) Physics. His research focuses on laser-induced breakdown spectroscopy (LIBS) for rapid bacterial pathogen detection in clinical specimens such as blood, urine, and cerebrospinal fluid. He has led a prolific research group, mentoring over 20 graduate and undergraduate students, and has presented at international conferences including LIBS XIII, SciX, and the Canadian Association of Physicists (CAP) Congress. His work bridges physics, biomedicine, and chemistry, aiming to develop faster diagnostic tools for infectious diseases. Dr. Rehse holds a Ph.D. from Colorado State University and has held academic positions at the University of Western Ontario and Wayne State University. His awards include the Roger Thibert Teaching Excellence Award (2013) and multiple NSERC grants. His lab collaborates with medical professionals and industry, advancing LIBS applications in clinical settings. Recent projects include emission enhancement techniques using silver thin films and interdisciplinary outreach with pre-optometry students. Key achievements include developing LIBS protocols for urinary tract infections and bacterial meningitis diagnosis, with publications in Spectrochimica Acta, Applied Spectroscopy, and other journals. He advocates for undergraduate research through programs like the Outstanding Scholars initiative and has engaged the public via media appearances and science outreach events.

Amit Kumar MishraView profile

Professor

• Machine Learning
• Radar Technology
• Synthetic Aperture Radar (SAR)
• +7 more

Amit Kumar Mishra is a Professor of Communications Engineering and Director of the National Spectrum Centre at Aberystwyth University, UK. His primary affiliation is within the Faculty of Business and Physical Sciences. He leads interdisciplinary research in radar technology, machine learning, and cognitive architectures with applications in environmental monitoring, biomedical engineering, and cybersecurity. His research interests include Synthetic Aperture Radar (SAR) imaging, AI-driven environmental sensing (e.g., agricultural monitoring, biodiversity tracking), and advanced communication systems like IRS-enhanced NOMA networks. Recent work focuses on developing symbiotic AI-human cognitive systems for attention management and sensor data assimilation in industrial environments. Over 200+ publications span journals like Sensors , IEEE Transactions , and conference proceedings. Notable collaborations include projects on oil spill detection, underwater object recognition, and patient-specific medical modeling. He co-led the SMART Expertise project (2025) focused on innovation bridging. Media highlights include reports on medical imaging applications (Coarctation of Aorta studies) and the Aberystwyth University Technology Centre's innovation initiatives. His work aligns with UN SDGs related to sustainable cities and responsible consumption patterns.

Roberto MenichettiView profile

Researcher

• Theoretical Physics
• Computational Physics
• Statistical Mechanics
• +7 more

Roberto Menichetti is a theoretical physicist at the University of Trento , affiliated with the Department of Physics and the VARIAMOLS research group . His work integrates computational physics, statistical mechanics, and machine learning to model biomolecules and soft matter systems. Prior roles include postdoctoral research at the Max Planck Institute for Polymer Research (2016-2018) and academic training at the University of Rome 'La Sapienza'. PhD in Physics (La Sapienza, 2016) BSc/MSc in Physics (La Sapienza, 2012) His research spans: Coarse-Graining Methods for polymers, colloids, and biomolecules High-throughput Molecular Dynamics Simulations in drug-membrane permeability studies Integration of Machine Learning with physical models for multi-scale analysis Applications in Biophysics (e.g., chromatin condensates, protein dynamics) Article trends highlight his focus on computational frameworks like EXCOGITO and theoretical investigations of non-equilibrium systems and allosteric regulation . He actively develops tools for systematic model reduction and conformational sampling in biomolecular systems. Contact: roberto.menichetti@unitn.it

Christophe RoyonView profile

Professor

• Particle Physics
• High-Energy Physics
• Collider Physics
• +3 more

Christophe Royon is a Foundation Distinguished Professor at the University of Kansas, leading research in high-energy particle physics with a focus on collider experiments at the Large Hadron Collider (LHC). His work primarily involves analyzing data from the CMS experiment to explore fundamental questions in particle physics, such as dark matter detection, Higgs boson properties, and quantum chromodynamics (QCD) dynamics. Research interests include probing new physics scenarios through precision measurements of top quark interactions, vector boson production, and jet substructure. He actively contributes to studies of heavy ion collisions to understand quark-gluon plasma behavior and gluon saturation effects. His experimental expertise spans detector calibration, systematic uncertainty quantification, and machine learning applications in data analysis. Notable achievements include the APS Award for collaboration with Brazil (2017-2018), recognizing his international research contributions. His recent publications (2024-2025) highlight advancements in measuring W boson properties, constraining Higgs Yukawa couplings, and discovering anomalous top quark pair production signals. Dr. Royon collaborates extensively with global physics communities, advancing experimental techniques for future collider projects like the Electron Ion Collider (ECCE). His work bridges theoretical predictions with experimental validation, contributing to both precision Standard Model tests and searches for physics beyond the Standard Model.

Hosameldin O. A. AhmedView profile

Research Fellow

• Multimodal Medical Imaging
• Artificial Intelligence
• Extended Reality (XR)
• +4 more

Dr. Hosameldin Ahmed is a Research Fellow at Aston Digital Futures Institute , Aston University , with a focus on interdisciplinary applications of artificial intelligence (AI) , extended reality (XR) , and data analytics in healthcare, industrial systems, and cultural heritage preservation. His collaborative work includes partnerships with Imperial College London and Brunel University (CEPROQHA Project).

Ali DehghantanhaView profile

Professor

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +7 more

Dr. Ali Dehghantanha is a Professor and Canada Research Chair in Cybersecurity and Threat Intelligence (Tier 2) at the University of Guelph's School of Computer Science. He founded the Cyber Science Lab, the Master of Cybersecurity and Threat Intelligence (MCTI) program, and the Canada Cyber Foundry. His expertise spans cybersecurity, AI, and critical infrastructure protection, with a focus on federated learning, threat intelligence, and enterprise risk management. Research Interests: Cybersecurity & AI Integration Federated Learning Security IoT and Industrial Cyber-Physical Systems Adversarial Machine Learning Cyber Threat Intelligence Automation His research emphasizes practical applications, such as securing agri-food systems, blockchain-enabled frameworks, and autonomous cybersecurity solutions. Notable achievements include the IEEE Outstanding Leadership Award (2021) and leadership in national cybersecurity initiatives. Recent Contributions: Recent work explores federated learning for privacy-preserving threat detection in IoT, AI-driven malware hunting, and autonomous systems for intrusion detection. His publications highlight interdisciplinary approaches to cybersecurity challenges in critical sectors like agriculture and transportation. Awards: Canada Research Chair (2020–present), IEEE Outstanding Leadership Award (2021). Labs & Initiatives: Cyber Science Lab: Pioneering research in AI-driven cybersecurity Canada Cyber Foundry: Bridging academic and industry cybersecurity innovation MCTI Program: Training next-generation cybersecurity professionals

Zacharakis GiannisView profile

Research Professor

• Biophotonics
• Biomedical Imaging
• Optical Imaging
• +3 more

Dr. Zacharakis Giannis is a Research Professor and Research Director at the Institute of Electronic Structure and Laser (IESL) of the Foundation for Research and Technology (FORTH). He heads the Laboratory for Biophotonics and Molecular Imaging, focusing on developing advanced imaging technologies for biomedical and cultural heritage applications. He served as Vice President and President of the European Society for Molecular Imaging (ESMI) and holds leadership roles at FORTH. Education: BSc in Physics (1997), PhD in Biomedical Imaging (2002), both from the University of Crete. Postdoctoral Research Fellow at Harvard University (2003-2004). Research Interests: Biophotonics, optoacoustic imaging, biomedical optics, and non-invasive diagnostic tools. His work spans label-free imaging techniques, hybrid microscopy systems, and applications in healthcare, art conservation, and plant biology. Key Achievements: Over 60 peer-reviewed journal articles, 48 conference papers, 2 book chapters, 2 patents, and an h-index of 19 (Google Scholar). Awards include 3 first prizes at international conferences and 20+ invited talks globally. Labs & Groups: Leads the Biophotonics and Molecular Imaging Lab at FORTH-IESL, collaborating on projects like optical projection tomography, adaptive light-sheet microscopy, and optoacoustic technologies for cultural heritage diagnostics.

• Environmental Biotechnology
• Wastewater Treatment Processes
• Quantum Computing Applications
• +6 more

Po-Heng (Henry) Lee is an Associate Professor in the Department of Civil and Environmental Engineering at Imperial College London, part of the Faculty of Engineering. His research focuses on wastewater engineering, environmental biotechnology, and quantum computing applications in microbial systems. He leads the Industrial Biotechnology Hub, Microbiome Network, and Quantum Engineering, Science and Technology initiatives. Dr. Lee holds a PhD from Iowa State University (2010) and earlier degrees from institutions in Taiwan. His academic career includes roles at Hong Kong Polytechnic University (2012-2018) and Inha University (2010-2012) before joining Imperial College in 2019. His research integrates quantum information theory with environmental engineering, exploring electron transfer mechanisms, anaerobic digestion optimization, and water reuse in AI/semiconductor contexts. Techniques include quantum computing platforms (IBM Qiskit, Xanadu), meta-omics, and Gaussian Bosonic Sampling. Key application areas include enhancing antibiotic and nitrogen removal via microbiome-conductive material interactions, smart chemical dosing for industrial cooling systems, and optimizing full-scale wastewater plants. His work bridges quantum mechanics and microbial ecology to address sustainability challenges. Dr. Lee's lab develops innovative solutions for resource recovery, greenhouse gas reduction, and bioplastic production. Major collaborations focus on AI-driven process control and semiconductor manufacturing wastewater treatment.

Karthika PrasadView profile

Research Fellow

• Carbon Nanoparticles
• Polymer Nanocomposites
• Biotechnology for Agriculture
• +3 more

Karthika Prasad is a Senior Research Fellow at the Australian National University (ANU), affiliated with the ANU College of Systems & Society and the School of Engineering. She also serves as the Chief Technology Officer (CTO) of BudMore, an agritech company. Her research focuses on carbon nanoparticles, polymer nanocomposites, and biotechnology applications in agriculture, including smart plasma systems for agricultural innovation. Dr. Prasad holds a PhD in Science and Engineering from Queensland University of Technology (QUT, 2019), a Master’s in Nanoscience from VELS University (2014), and a BSc in Nanotechnology from the University of Wollongong (2012). Key achievements include the QUT Executive Dean’s Commendation for Outstanding Doctoral Thesis (2020) and the QUT Higher Achiever Award (2018). Her work spans biomedical applications of nanomaterials, aerospace materials, and sustainable technologies derived from natural products. Recent research trends highlight innovations in nanocomposite materials for medical implants, space technology, and agricultural systems. Professional contributions include postdoctoral research at QUT (2017–2020) and sessional academic roles. She has pioneered studies on plasma-activated solutions for disinfection and explored synergistic effects of plant metabolites with antimicrobial agents. Current projects emphasize functional nanomaterials from waste and low-value natural products, reflecting her commitment to sustainable technological advancements.

Daniel IerodiaconouView profile

Professor

• Marine Ecology
• Environmental Management
• Geology
• +6 more

Professor Daniel Ierodiaconou is a marine ecologist at Deakin University, where he serves as Professor in Marine Science and leads the Deakin Marine Mapping Group. He acts as Victorian Node Leader for the Integrated Marine Observing System (IMOS), Board Director for the Great Ocean Road Coast and Parks Authority, and Coastal Lead Scientist for the CoastRI Initiative. His work combines multi-disciplinary approaches to advance marine ecosystem-based management. Doctor of Philosophy, Deakin University Bachelor of Science (Aquatic Science), Deakin University Bachelor of Science (Fisheries Management & Aquaculture), Deakin University Daniel's research focuses on Benthic Habitat Mapping , Marine Protected Areas , and Coastal Process Monitoring . His work integrates Remote Sensing , Image Classification , and Change Detection techniques to inform marine conservation and climate adaptation strategies. Recent publications highlight advancements in Seafloor Habitat Classification , Coastal Erosion Modeling , and Seagrass Restoration . Scientific awards include: 2020 Eureka Prize for Innovation in Citizen Science 2020 Victorian Coastal Award for Innovative Applied Research 2018 Victorian Coastal Award for Partnership Research 2009 Tall Poppy Award Daniel supervises 10 current doctoral students and has advised 16 PhD completions. His grants portfolio exceeds $7 million, including a $5 million NCRIS-funded CoastRI Coastal Monitoring Network. He specializes in integrating Geospatial Technologies with Marine Conservation through his leadership in citizen science drone programs and Victoria's first wave buoy network.

• Electric Machines
• Finite Element Analysis
• Open Source Software
• +3 more

Simone Ferrari is a Fixed-term Assistant Professor in the Department of Energy (DENERG) at Politecnico di Torino. He is a member of the Interdepartmental Center PEIC (Power Electronics Innovation Center) and affiliated with the College of Electrical and Energy Engineering and College of Mechanical, Aerospace and Automotive Engineering as an invited member. His research focuses on electric machines, finite element analysis, and open-source software development for electromagnetic systems. He has supervised multiple PhD students in electrical engineering and has contributed to commercial consulting projects such as the design of electric motors for lifting applications and supervision of high-power motor development. Teaching responsibilities include courses on Propulsion of Hybrid and Electric Vehicles, Applied Electromagnetism, and Electrical Machines across multiple academic years. His work emphasizes multiphysics simulation, data-driven modeling, and the development of efficient traction motors for electric vehicles. Key research outputs include advancements in flux-map-based modeling, fault-tolerant motor designs, and thermal/structural scaling techniques for synchronous machines. Dr. Ferrari holds a patent for a method to identify spatial harmonic flux and torque maps without torque transducers. His recent publications (2024-2025) address challenges in electric motor efficiency, fault performance, and NVH mitigation, reflecting his commitment to advancing sustainable power electronics and clean energy technologies aligned with SDGs 7 and 9.

Sandip KunduView profile

Professor

• Hardware Security
• VLSI Design
• CAD Algorithms
• +7 more

Sandip Kundu is a Professor of Electrical and Computer Engineering at the University of Massachusetts Amherst since 2005. Prior roles include Senior Researcher at Intel (1997–2005) and IBM Research (1988–1997). He holds a Ph.D. from the University of Iowa (1988) and a B.Tech from IIT Kharagpur (1984). Research Interests: Focuses on hardware security, VLSI design, CAD algorithms, microarchitecture, and neural processing. Notable contributions include work on physically unclonable functions (PUF), blockchain-based IC traceability, and securing embedded systems against adversarial attacks. Key Activities: Served as Associate Editor for multiple IEEE journals and held visiting professorships at institutions like University of Freiburg (Germany), Kyushu Institute of Technology (Japan), and Tsinghua University (China). Awarded IEEE Fellow and JSPS Invitational Fellowships. Awards: Includes five best paper awards, Intel’s Development Leadership Pioneer Award, IBM’s Outstanding Technical Achievement Award, and recognition as a Distinguished Visitor by IEEE Computer Society. Grants & Labs: Active in NSF-funded research and leads the Advanced VLSI Design and Test Group, exploring secure hardware design, neuromorphic computing, and resilient architectures for edge devices.

Ralf SchlüterView profile

Lecturer

• Automatic Speech Recognition
• Machine Learning
• Pattern Recognition
• +4 more

Ralf Schlüter is a senior researcher and Lecturer (Privatdozent) at RWTH Aachen University, where he leads the Automatic Speech Recognition Group within the Department of Computer Science. His academic roles include serving as Academic Director and leading research initiatives at Lehrstuhl Informatik 6: Human Language Technology and Pattern Recognition. He holds a Dipl. in Physics (1995), a Dr. rer. nat. in Computer Science (2000), and a Habilitation in Computer Science (2019), all from RWTH Aachen University. His research focuses on advanced speech recognition technologies, including end-to-end architectures, acoustic modeling, discriminative training, and machine learning applications. He has led numerous national and international projects, such as EU-funded initiatives like BABEL, BOLT, and GALE. Schlüter has published extensively in top-tier conferences like Interspeech and ICASSP, contributing to advancements in neural network frameworks, feature extraction, and error analysis. He teaches courses on speech recognition, pattern recognition, and signal processing, and serves as a Subject Editor for Speech Communication . His work also involves developing the RWTH ASR toolkit, emphasizing scalable and efficient speech recognition systems. Schlüter’s contributions to speech technology have earned recognition, including the ISCA Best Student Paper Award (2019).

Luca ManneschiView profile

Lecturer

• Machine Learning
• Neuromorphic Computing
• Biological Networks
• +3 more

Dr Luca Manneschi is a Lecturer in Machine Learning at the School of Computer Science, University of Sheffield, with an IBM Liaison role. He holds a PhD in Physics from the University of Sheffield (2021) and completed a PostDoc there before his current position since March 2022. His research focuses on designing learning algorithms inspired by biological networks for physically defined systems, emphasizing neuromorphic computing, reservoir computing, and stochastic environments. Education: Bachelor's in Physics: University of Padua (Italy) Master's in Physics: Sapienza University of Rome (Italy) PhD in Physics: University of Sheffield (2021) Research Interests: Dr. Manneschi explores algorithms for physically defined networks, leveraging biological network principles to enhance computation in dynamic environments. His work bridges machine learning with neuromorphic hardware, emphasizing adaptability and energy efficiency. Key areas include reservoir computing, magnetic metamaterials, and multi-timescale learning strategies. Grants & Funding: "Real-time Reservoir Computing on Prosthetic Devices" (2023–2025, Royal Society, PI) "MARCH: Magnetic Architectures for Reservoir Computing Hardware" (2021–2025, EPSRC, Co-PI) "CausalXRL: Causal Explanations in Reinforcement Learning" (2021–2024, EPSRC, Co-PI) "ActiveAI" (2019–2024, EPSRC, Co-PI) Lab/Team Affiliation: Machine Learning Research Group, School of Computer Science.

Matt BowerView profile

Professor

• Technology-Enhanced Learning
• Artificial Intelligence in Education
• Augmented Reality
• +7 more

Professor Matt Bower is a leading academic in educational technology at Macquarie University's School of Education. Specialising in technology-enhanced learning, his work explores AI, AR, VR, and other tools to improve cognitive and collaborative learning. He has published over 100 peer-reviewed articles, led over 30 funded projects (totaling $3M+), and advised educational policymakers. His research spans teacher education, computing education, and learning design frameworks. Notable contributions include the Design of Technology-Enhanced Learning textbook (2018 AECT Award winner) and leadership in the Australian Technologies Teacher Educators Network (2019–2024). Research interests include AI in education, blended synchronous learning, and the impact of emerging technologies like wearable devices and generative AI on pedagogy. He collaborates with industry and education sectors to develop innovative learning solutions. Awards include the 2021 Australian Teaching Excellence Award and multiple Macquarie Vice-Chancellor awards. Current projects focus on screen use in education, teacher attitudes toward AI, and post-pandemic learning strategies. Professional activities include roles on ACARA’s Technologies Panel and NSW Educational Standards Authority committees. His work bridges research and practice, emphasizing teacher training and policy engagement. Projects like the ChatGPT survey and analyses of remote learning during the pandemic highlight his focus on real-world educational challenges.