Find Academic Supervisors

• Laser Spectroscopy
• Molecular Spectroscopy
• Metrology
• +7 more

Christophe Daussy is an Assistant Professor (Maître de Conférences) at Université Sorbonne Paris Nord, where he conducts research in the Laboratoire de Physique des Lasers (LPL). His work spans precision metrology, molecular spectroscopy, and physics education, with significant contributions to the redefinition of the International System of Units, particularly regarding the Boltzmann constant and thermodynamic temperature measurements. He maintains strong connections with the Laboratoire commun de métrologie LNE-CNAM and Systèmes de Référence Temps Espace. Daussy's research focuses on high-precision laser spectroscopy, particularly for fundamental constant determinations and metrological applications. His work on the Boltzmann constant has been instrumental in the redefinition of the kelvin, and he has made significant contributions to quantum cascade laser stabilization, optical frequency dissemination, and the search for parity violation effects in chiral molecules. More recently, he has expanded his interests to include physics education research, particularly the integration of metrological concepts in biology education. His publication record shows consistent high-impact research since the early 2000s, with recent work spanning both fundamental metrology (Boltzmann constant measurements, quantum cascade laser stabilization) and science education (metrological concepts in biology courses). His work appears in prestigious journals including Physical Review Letters, Metrologia, and Nature Photonics. Daussy has also been active in developing educational tools like the LightBox kit for optics education. Daussy leads research within the Metrology, Molecules and Fundamental Tests group at LPL, focusing on precision molecular spectroscopy for fundamental physics tests and metrological applications. His laboratory work combines advanced laser techniques with precision measurement methodologies to address fundamental questions in physics while maintaining practical applications in metrology.

Alice TowlerView profile

Part-Time Lecturer

• Forensic Psychology
• Face Identification
• Cognitive Science
• +3 more

Dr. Alice Towler is a Casual Academic at the School of Psychology within the University of New South Wales (UNSW). Her research focuses on improving face identification accuracy and efficiency in forensic settings, including the study of super-recognition abilities, development of evidence-based facial comparison methods, and optimization of human-software collaboration in identity verification. Her primary research interests include: Forensic face identification techniques and error reduction Predictors of superior face recognition ability (super-recognition) Development of evidence-based training protocols for facial image comparison Integration of human expertise with facial recognition software systems Identity fraud detection in critical applications like passport verification Dr. Towler collaborates extensively with the UNSW Forensic Psychology Lab under Dr. David White and Prof. Richard Kemp. She maintains an active partnership with the Australian Passport Office to enhance identity fraud detection capabilities. As a member of the Evidence-Based Forensics Initiative, she advocates for scientifically validated practices in forensic sciences through interdisciplinary collaboration between legal professionals, forensic scientists, and cognitive researchers. Her recent publications demonstrate consistent focus on face recognition mechanisms, perceptual expertise development, and forensic applications. Research themes include optimization of training protocols, individual differences in recognition abilities, validation of forensic methodologies, and real-world implementation challenges.

• Particle Physics
• Supersymmetry
• Higgs Boson Research
• +3 more

Professor Dan Tovey is affiliated with the School of Mathematical and Physical Sciences at the University of Sheffield. His research focuses on Supersymmetry searches , Dark Matter , and ATLAS detector upgrades at the Large Hadron Collider (LHC). Role: Professor of Particle Physics Institution: University of Sheffield Research: ATLAS experiment, Higgs boson properties, detector performance Research Interests Dan Tovey leads studies on supersymmetry and dark matter using the ATLAS detector. His work spans Higgs boson decays , top quark interactions , and detector upgrades for the High-Luminosity LHC. He investigates non-standard model phenomena like long-lived particles and exotic Higgs decays . Publications (2023–2025) Recent articles highlight his contributions to Higgs boson mass measurements , top quark production , and ATLAS trigger system optimizations . Key trends include searches for new physics , precision electroweak tests , and detector simulations . Scientific Awards ERC Advanced Grant No. 694202 for 'LHCDMTOP: Novel Dark Matter Searches with Top Quarks'

Dongkuan XuView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Computer Vision
• +7 more

Dongkuan Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University, leading the Generative Intelligent Computing (GIC) Lab. His research spans Artificial Intelligence , focusing on scalable, efficient, and reliable AI systems for large language models, diffusion models, and generative frameworks. Education Ph.D. in Computer Science, Pennsylvania State University (2022) M.S. in Optimization and Data Mining, University of Chinese Academy of Sciences (2017) B.E. in Information Management and System, Renmin University of China (2014) His research explores test-time adaptation, computational efficiency, and trustworthy AI through uncertainty-aware learning and robust generalization. Applications include Education , Robotics , Agriculture , Networking , and Healthcare . Recent work emphasizes hardware-algorithm co-design and domain-specific AI platforms like Synthora and Gentopia. His publications from 2024–2025 highlight advancements in Vision Transformers , Diffusion Models , Edge Computing , and Trustworthy AI , with grants from NVIDIA , Microsoft , and the National Science Foundation . Awards include the AAAI Best Demonstration Award (2025), NVIDIA Academic Grant (2025), and the Carla Savage Award (2024). He actively mentors undergraduate researchers and co-chairs workshops at top venues like DAC , CVPR , and KDD , aiming to democratize AI access and enhance its reliability across real-world domains.

• Data Science Systems
• Machine Learning Systems
• Database Systems
• +7 more

Yongjoo Park is an Assistant Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign, affiliated with the Siebel School of Computing and Data Science and the Data and Information Systems (DAIS) Research Lab. He co-founded and serves as Chief Scientist at Keebo, Inc., a startup developing automated data warehouse optimization platforms. Ph.D. in Computer Science and Engineering, University of Michigan, Ann Arbor (2017) M.S. in Computer Science, University of Michigan, Ann Arbor (2013) B.S. in Electrical Engineering, Seoul National University (2009) His research focuses on building intelligent data-intensive systems that integrate statistical and AI techniques for improved reliability, scalability, and usability in data science workflows. Key projects include Kishu (undoable Jupyter notebooks), AirIndex (automated index optimization), and CARE (causal-reasoning data systems). His work bridges database systems and machine learning, emphasizing end-to-end optimization for structured/unstructured data processing. Recent publications highlight trends in computational notebook checkpointing, index tuning through data-aware storage, and AI-driven database learning. His projects have been recognized at top venues including SIGMOD, VLDB, and CHI, with a focus on practical implementations for real-world data challenges. Scientific Awards: NSF CAREER Award (2025) Best Demo Award at SIGMOD 2025 ACM SIGMOD Jim Gray Dissertation Award Runner-up (2018) Engineering Council Outstanding Advising Award (2021) Teaching Excellence Awards (2023, 2024) Yongjoo advises multiple PhD and MS students, including Supawit Chockchowwat (joining CMKL University in Thailand) and Nikhil Sheoran (now at Databricks). His research group maintains strong industry collaborations and open-sources systems like Kishu and VerdictDB through their GitHub organization .

Henri GavinView profile

Professor

• Earthquake Engineering
• Structural Control
• Vibration Isolation
• +5 more

Henri Gavin is a Professor in the Department of Civil and Environmental Engineering. His research focuses on developing innovative solutions for structural resilience, control systems, and earthquake engineering. He leads interdisciplinary projects integrating sensor technology, IoT systems, and machine learning for real-world applications such as earthquake early warning systems. Research Interests: Professor Gavin's work spans earthquake engineering, structural dynamics, vibration isolation, robotics, optimization, and machine learning applications in civil infrastructure. His signature project—Pilot Earthquake Early Warning in Kathmandu (Data+, 2022)—demonstrates his approach to combining AI models with geophone sensors and IoT networks for on-site seismic alerts. Publication Trends: His recent articles (2020-2024) emphasize structural reliability, decentralized control of robotic systems (UAVs/swarms), optimization algorithms, and seismic protection strategies. This reflects a consistent focus on theoretical rigor applied to practical engineering challenges, particularly in nonlinear dynamics and multi-agent coordination. Projects and Advising: He mentors students through Duke's Data+ program, guiding projects in energy data analytics and earthquake early warning systems. Notable funded initiatives include instrumentation and modeling of seismic isolation systems (EAGER, 2012) and performance analysis of base-isolated structures during seismic events.

Andrea CramptonView profile

Senior Lecturer

• Health Literacy
• Science Education
• Sustainability
• +6 more

Andrea Crampton is a Senior Lecturer in the School of Dentistry and Medical Sciences at Charles Sturt University (CSU), specializing in Medical Science and Pathology. With a career spanning laboratory management, sub-dean roles in two faculties, and international research experience, she integrates her multidisciplinary background into science education and public health literacy initiatives. B.Sc. (First Class Honours), Parasitology, University of Queensland (1994) Ph.D., Microbiology and Parasitology, University of Queensland (1999) Her research focuses on enhancing public capacity to engage critically with health and environmental information, particularly in rural communities. This includes studies on: Water quality and pollution risks Plastic consumption behaviors Health literacy for smoke exposure Technology-driven teaching innovations Distance education engagement strategies Sustainability policy implementation Her teaching philosophy emphasizes adaptable, student-centered methodologies informed by her research background. She has explored: Online learning environments Technology integration in microbiology Student anxiety and motivation factors Distributed leadership models (via SaMnet network)

• Neonatology
• Ophthalmology
• Clinical neurology
• +5 more

Dr. Melanie Boileau is a Professor in Veterinary Clinical Sciences at Oklahoma State University's College of Veterinary Medicine. She holds the McCasland Foundation Chair of the Clinical Professorship and serves as a Food Animal Clinician at the Veterinary Medical Hospital. Originally from Québec, Canada, she earned her DVM from Montreal University in 2000 and completed a residency and MS in Veterinary Biomedical Sciences at Oklahoma State University. DVM, Montreal University (1996-2000) MS, Veterinary Biomedical Sciences, Oklahoma State University (2002-2004) Residency in Large Animal Internal Medicine with emphasis in Food Animal Diplomate, American College of Veterinary Internal Medicine (2004-present) Licensed in Oklahoma (2005-present) and Québec (2017-2018) Dr. Boileau's research focuses on neonatology, ophthalmology, clinical neurology, and small ruminants and camelid medicine. Her work bridges clinical practice and scientific investigation, with particular emphasis on practical applications for food animal practitioners. She has made significant contributions to understanding pregnancy toxemia in goats, lidocaine therapy for gastrointestinal issues in ruminants, and innovative surgical techniques for small ruminants. Her recent publications demonstrate a consistent focus on practical veterinary medicine for food animals, particularly goats and cattle. The research spans diagnostic methods, therapeutic interventions, surgical techniques, and disease management. Her work on Bdellovibrio bacteriovorus represents innovative approaches to antimicrobial alternatives, while her clinical studies on pregnancy toxemia and sinusitis provide valuable insights for practicing veterinarians. 2021 Large animal faculty leadership award 2020 Outstanding Class Teaching Award 2019 Outstanding Class Teaching Award Oklahoma State University Regent's Distinguished Teaching Award (2018) Dr. Boileau has secured multiple research grants from Nova Biomedical, Oklahoma State University Research Advisory Committee, and Oklahoma University COBRE grant programs. Her grant-funded work has focused on point-of-care diagnostics, pregnancy toxemia in goats, and non-antimicrobial treatments for cattle infections. She actively serves on various committees including the Dermatology Faculty Search Committee, Hospital Administrator Search Committee, and CVM Reappointment Promotion and Tenure Committee. Her outreach activities include Alpaca dystocia wet labs and Food Animal Case Discussions. Within the Veterinary Medical Hospital's Large Animal/ Food Animal section, Dr. Boileau contributes to clinical services while mentoring students in food animal medicine. Her work connects academic research with practical herd health management for Oklahoma's agricultural community.

• Zoological Medicine
• Avian Medicine
• Exotic Animal Medicine
• +3 more

João Lemos Brandão is a Professor in Veterinary Clinical Sciences at Oklahoma State University, holding the Debbie and Wayne Bell Professorship. He specializes in Zoological Medicine with a focus on avian and exotic animal medicine. His expertise spans clinical care, research, and education for non-traditional species including birds, reptiles, and small mammals across the College of Veterinary Medicine. His educational background includes: Licenciado em Medicina Veterinária (Licensed in Veterinary Medicine) from Universidade de Tras-os-Montes e Alto Douro, Portugal (2008) Master of Science in Veterinary Medicine from Louisiana State University, Baton Rouge, Louisiana, United States (2014) Dr. Brandão is a Diplomate of the European College of Zoological Medicine (Avian) and an EBVS® Diplomate of the American College of Zoological Medicine. His postgraduate training includes a Zoological Medicine Residency at Louisiana State University (2011-2014) and internships at University of Georgia, Tufts University, and Great Western Referrals in the UK. His research interests focus on comparative medicine across diverse exotic species. He investigates gastrointestinal physiology, anesthesia protocols, diagnostic imaging techniques, and disease management in zoo animals and wildlife. His work bridges clinical practice with scientific research to improve veterinary care for non-traditional companion animals and wildlife species through evidence-based approaches. Analysis of his recent publications reveals a strong emphasis on translational research with practical clinical applications. His work spans diagnostic techniques, surgical interventions, pharmacological studies, and disease management across multiple species including birds, reptiles, marsupials, and small mammals. Many studies employ advanced methodologies including next-generation sequencing, specialized imaging techniques, and rigorous pharmacological testing to address clinically relevant questions in exotic animal medicine. His scientific recognition includes: Distinguished Early Career Faculty Award from Oklahoma State University (2021) 1st Place Poster Award at the 5th Exoticscon Conference (2021) Dr. Brandão serves as a mentor for graduate students through Master's Research and Thesis projects. His grant portfolio includes significant funding from organizations like Boehringer Ingelheim, Morris Animal Foundation, and the Association of Exotic Mammal Veterinarians, supporting research in exotic animal medicine, anesthesia protocols, and disease management. He has served on numerous committees including the Institutional Animal Care and Use Committee and as Chair of various search committees. His service extends to peer reviewing for multiple veterinary journals and serving as a Guest Editor for Veterinary Clinics of North America - Exotic Animal Practice.

• Fair Machine Learning
• Federated Learning
• Graph Neural Networks
• +3 more

Yijun Bian is a Postdoctoral Research Fellow at the Department of Computer Science (DIKU), University of Copenhagen, specializing in machine learning research. They are affiliated with the Machine Learning section and the SCIENCE AI Centre, focusing on theoretical and applied aspects of fair machine learning, federated learning, and adversarial robustness. Their research spans multiple domains including: Fairness-aware algorithms (HL-HGAT, FairSHAP) Federated learning security Heterogeneous graph modeling Adversarial attack analysis Ensemble learning optimization Biomedical data modeling Recent publications highlight their work on fairness evaluation, topological graph attention networks, and robustness in vision-based tasks. They actively contribute to advancing trustworthy AI systems through theoretical foundations and practical implementations.

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

Enrico Robutti is a Professor at the Department of Physics, University of Genoa (Italy), affiliated with INFN (National Institute for Nuclear Physics). He specializes in experimental particle physics, focusing on collider-based studies of fundamental particles such as the Higgs boson, top quarks, and supersymmetric particles. His work involves analyzing data from high-energy proton-proton and proton-nucleus collisions at facilities like CERN's Large Hadron Collider (LHC). He actively contributes to the CMS experiment and has published extensively on topics such as Higgs boson pair production, supersymmetry searches, and detector technologies. He teaches Particle Detector Physics (course code 114701) as part of the Master's program in Physics at the University of Genoa, emphasizing practical applications of detector systems in modern experiments. His research spans both theoretical and experimental aspects of high-energy physics, with recent emphasis on precision measurements and beyond Standard Model physics. Key contributions include studies on top quark production in proton-nucleus collisions and constraints on anomalous Higgs couplings. His detector-related work includes upgrades and operational analyses for the BaBar experiment.

Hang Trung DinhView profile

Associate Professor

• Quantum Computing
• Computer Security
• Algorithms Analysis
• +3 more

Hang Trung Dinh is an Associate Professor at the Department of Computer and Information Sciences, Indiana University South Bend. He specializes in Quantum Computing, Post-Quantum Cryptography, and Theoretical Computer Science Education. He co-founded ExtentWorld, a social media platform emphasizing privacy-conscious design. Education: PhD in Computer Science from the University of Connecticut (2010), advised by Professor Alexander Russell. His research bridges quantum computing fundamentals, heuristic search optimization, and educational methodologies in computing theory. Research Interests: Quantum Algorithms and Lower Bounds Post-Quantum Cryptographic Systems Algorithmic Analysis of Heuristic Search Methods Computer Security & Cryptography Innovative Course Development in Discrete Mathematics Publications highlight contributions to quantum-resistant encryption (e.g., McEliece Cryptosystem analysis) and heuristic search efficiency studies. His work has been featured in venues like Quantum Information & Computation and AAAI. Grants: Secured two IUSB Faculty Research Grants ($8,500 each) for projects on heuristic search empirical analysis (2011) and algorithmic pedagogy (2013).

• Internet of Things (IoT)
• Context-aware computing
• Edge and cloud computing
• +7 more

Prem Prakash Jayaraman is a Professor in the Department of Computer Science and Software Engineering within the Faculty of Science, Engineering and Technology at Swinburne University of Technology. His research focuses on the intersection of Internet of Things, context-aware computing, and distributed systems, with particular emphasis on practical applications in smart cities, digital manufacturing, and healthcare. Dr. Jayaraman's research interests span a wide range of topics within the IoT ecosystem, including context-aware computing, edge and cloud computing integration, digital twins for industrial applications, sensor network optimization, and performance evaluation of IoT middleware platforms. His work often addresses the challenges of real-world deployment, focusing on practical solutions for context management, data quality assurance, and resource optimization in distributed environments. He has made significant contributions to frameworks for context query generation, adaptive context monitoring, and caching strategies that enhance the efficiency of IoT applications. His recent publications demonstrate a strong trend toward applied research with practical implementations in smart city infrastructure, digital manufacturing, and healthcare applications. His work often combines theoretical frameworks with real-world validation, particularly evident in his studies on 5G-enabled smart cities, AI-driven roadside infrastructure monitoring, and digital twin implementations for manufacturing quality control. The research spans multiple sub-disciplines including context-aware systems, performance evaluation methodologies, and resource optimization techniques for distributed IoT environments. Dr. Jayaraman maintains an extensive collaborative network with researchers across Australia and internationally, particularly with Dimitrios Georgakopoulos, Rajiv Ranjan, Arkady Zaslavsky, and Abdur Forkan. His work appears in top-tier journals and conferences including IEEE Transactions on Industrial Informatics, Future Generation Computer Systems, IEEE Internet of Things Journal, and major conferences like MDM, HICSS, and IEEE Cloud.

• HIV/AIDS Research
• Infectious Diseases
• Global Health
• +5 more

Diane Havlir, MD, is a Professor of Medicine and Chief of the HIV, Infectious Diseases, and Global Medicine Division at Zuckerberg San Francisco General Hospital (ZSFG), part of UCSF. She serves as the Associate Chair of Clinical Research in the Department of Medicine and directs the UCSF AIDS Research Institute. She holds the Robert L. Weiss Memorial Chair for HIV/AIDS Research and was elected to the National Academy of Medicine in 2019. Her work focuses on HIV/AIDS, tuberculosis (TB), and global health, with an emphasis on community-based interventions and policy. Havlir co-founded San Francisco Getting to Zero (GTZ), a citywide initiative to eliminate HIV transmission and deaths. She leads the Sustainable East Africa Research in Community Health (SEARCH) Collaboration, a large-scale trial demonstrating how universal HIV testing and treatment reduces transmission and improves population health. Her research integrates telehealth, long-acting antiretrovirals, and AI-driven precision health to address healthcare equity. Education: MD from UCSF, residency in internal medicine at UCSF during the early AIDS crisis. She has over 400 publications in high-impact journals like NEJM and JAMA. Awards include the National Academy of Medicine membership and leadership roles in the WHO HIV-TB working group and UN AIDS Scientific Advisory Committee. Research interests span HIV prevention, TB co-infection, and global pandemic responses. Key projects include the SEARCH-Sapphire study (AI-driven community health strategies) and the Unidos en Salud partnership (Latinx community HIV/COVID-19 care). She has pioneered interventions like dynamic choice HIV prevention models and telemedicine for marginalized populations. Grants/Awards: NIH-funded investigator, SEARCH Collaboration, Robert L. Weiss Chair, National Academy of Medicine. Labs/Teams: AIDS Research Institute, SEARCH Consortium, GTZ partnership.

• Artificial Intelligence
• Bioinformatics
• Natural Language Processing
• +3 more

Dr. Ahmad Aghaebrahimian is a researcher at the ZHAW School of Life Sciences and Facility Management, affiliated with the Institute of Computational Life Sciences. He specializes in computational methods applied to healthcare, natural language processing (NLP), and bioinformatics. His work integrates deep learning, ontology-based systems, and signal processing to address challenges in healthcare informatics, biomedical research, and security systems. Research Projects: Project Leader: Advancing Information Accessibility in Hospitals (LLMs) Project Leader: Multi-document Patient Records Summarization Project Leader: Plant Cell Cultures with Deep Learning Deputy Leader: Automatic Supply Chain Monitoring Research Interests: His research focuses on AI-driven solutions for healthcare, including ontology-aware relation extraction, medical text mining, and robust signal processing systems. He also explores NLP applications in question answering, entity disambiguation, and parallel corpus creation. Recent work includes drone detection using CNNs in low SNR environments and computational methods for natural products discovery. Publications Trends: Over the past decade, his publications emphasize interdisciplinary approaches combining machine learning with bioinformatics and medical informatics. Key themes include deep learning model optimization, biomedical knowledge graph construction, and practical applications of NLP in healthcare systems. Grants & Collaboration: Leads research initiatives on AI in colorectal cancer classification and supply chain monitoring, demonstrating expertise in securing project leadership roles within academic-industry collaborations.