Find Academic Supervisors

• Astronomy
• Astrophysics
• Machine Learning
• +5 more

Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.

Eleftherios H. DrosinosView profile

Professor

• Food Safety
• Quality Management Systems
• Microbial Ecology
• +3 more

Prof. Eleftherios H. Drosinos is a Professor at the Agricultural University of Athens , specializing in Food Safety and Quality Management Systems . He teaches undergraduate and postgraduate courses in these areas and leads research initiatives focused on microbial quality control, HACCP systems, and ISO 9000 series standards. Education: Graduated from the Agricultural University of Athens; Ph.D. from Bath University (UK). His research explores microbial interactions in food systems, particularly pathogenic and spoilage microorganisms, with a strong emphasis on Lactiplantibacillus plantarum and Listeria monocytogenes dynamics across various substrates. He has published extensively on topics like sourdough microbiota, cheese safety, and antimicrobial strategies under the One Health framework. Recent publications (2024) highlight advancements in food spoilage detection, GMO monitoring, and microbial ecology. His work spans both experimental studies and reviews, addressing food safety in retail, fermented products, and fresh-cut vegetables. He directs the Laboratory of Food Quality Control and Hygiene , contributing to standardization and regulatory compliance in the food sector.

Sandeep ReddivariView profile

Associate Professor

• Software Engineering
• Requirements Engineering
• Visual Analytics
• +7 more

Sandeep Reddivari is an Associate Professor and Interim Graduate Director at the School of Computing, University of North Florida . Holding a Ph.D. in Computer Science and Engineering from Mississippi State University, his work focuses on software engineering , particularly requirements engineering , visual analytics , and software maintenance , with funding from the NSF, US Army Corps of Engineers, NSA, and UNF Foundation. Education : Ph.D. (2014, Mississippi State University), M.S. (2009, Texas A&M University), B.Tech. (2006, JNTU) Research Themes : Requirements Engineering, Visual Analytics, Data Mining, Machine Learning, GenAI, Software Security Teaching : Courses in Software Engineering, Data Science, and Database Systems Awards : NSF Grant Recognition (2024), Best Doctoral Symposium Poster (2013), Outstanding Graduate Teaching Award Nominee (2018) Publications span top venues like IEEE RE, ICSE, and COMPSAC, with a focus on combining visual analytics and machine learning to enhance software decision-making. His lab at UNF mentors students in directed independent studies, emphasizing code navigation , blockchain , and educational software tools .

Fei ChiangView profile

Associate Professor

• Data Management
• Data Quality
• Data Privacy
• +6 more

Dr. Fei Chiang is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. Her research focuses on data management , with emphasis on data quality, data privacy, information extraction , and contextual data cleaning . She has collaborated with IBM Global Services and Microsoft Research on improving data quality in enterprise systems. Key research themes include graph databases , temporal data analysis , and privacy-aware data processing Recent publications explore federated learning , SQL understanding in LLMs , and temporal graph constraints Industry collaborations with IBM Toronto Lab and Microsoft Research have led to innovations in data cleaning automation and semantic analysis. Her work bridges database theory with machine learning applications in healthcare inventory optimization and flight reliability prediction.

R. Alan CoveyView profile

Professor

• Archaeology
• Ethnohistory
• Andean Studies
• +5 more

R. Alan Covey is Professor in the Department of Anthropology at the University of Texas at Austin's College of Liberal Arts. Holding a Ph.D. from the University of Michigan, Ann Arbor, he maintains an active teaching schedule through Fall 2025 across multiple departments including Anthropology (ANT), Latin American Studies (LAS), and Tutorial Courses (T C). His campus office is located at RLP 4.406 (mail code C3200). Academic Background: Ph.D., University of Michigan, Ann Arbor Research Focus: Professor Covey specializes in Andean archaeology and ethnohistory, with primary expertise in the Inca Empire and Early Colonial Peru. His work examines imperial development through archaeological surveys, excavations, and archival research in Peru and Europe. Key themes include sociopolitical complexity , imperial collapse dynamics , cultural transformation following European contact, and Andean social organization from prehispanic through colonial periods. His methodological approach integrates material culture analysis with ethnohistoric documentation to reconstruct pre-Columbian lifeways and colonial transitions. Publication Trends: Recent scholarship shows concentrated focus on Inca imperial structures (2023-2025), examining economic systems, settlement patterns, religious transformations, and ideological signaling. His work increasingly engages quantitative historical analysis through the Seshat Databank while maintaining deep regional expertise in Cuzco-area archaeology. Current research emphasizes interdisciplinary synthesis across archaeological, historical, and anthropological frameworks. Teaching & Academic Service: Professor Covey teaches specialized courses including Inca World (ANT/LAS 324L), Cultures in Contact (ANT/LAS 326L), and Who Owns The Past? (T C 302/UGS 302), consistently offering both in-person and online formats since 2020. His course load demonstrates sustained commitment to undergraduate education in Andean studies and archaeological theory across multiple semesters and academic years.

Alejandro RussoView profile

Professor

• Computer Science
• Information Security
• Functional Programming
• +3 more

Alejandro Russo is a Professor at Chalmers University of Technology , specializing in Information Flow Control (IFC) , Secure Programming Languages , and Functional Programming . His research bridges theoretical foundations and practical implementations, focusing on mitigating timing channels , covert channels , and data leakage in concurrent systems. Developed novel frameworks for Differential Privacy with provable accuracy bounds Pioneered COWL integration for browser security and instruction-based scheduling to prevent cache timing attacks Led major projects like HIPSTER (hybrid static/dynamic IFC) and AppFlow (practical IFC deployment) His publications reveal expertise in security libraries for Haskell and Python , with a focus on faceted execution , label manipulation , and mechanized security proofs . Students under his supervision have explored topics ranging from secure eDSLs to privacy-preserving compilation techniques . Scientific awards : Google Research Award (2011) for Python taint analysis Advising and grants : Principal Investigator for VR , STINT , and Google Research Award Supervised 12+ PhD and Master’s students in security and functional programming research

• Sensory Physiology
• Marine Ecology
• Underwater Acoustics
• +5 more

Professor Craig Radford at the University of Auckland's Faculty of Science specializes in Marine Science with a focus on sensory systems and underwater soundscapes. Holding a PhD from Auckland , MSc from Canterbury , and BSc from Waikato , his research examines sensory physiology in fish and crustaceans, vocal communication mechanisms, and anthropogenic sound impacts. Current teaching includes Marine 702 Techniques in Marine Science and BioSci 334 - The Biology of Marine Organisms Postgraduate supervision topics span lateral line function, multisensory processing, ontogenetic hearing changes, and ecoacoustic indices His work on passive acoustic monitoring (149+ outputs) reveals trends in marine bioacoustics, particularly in shark hearing physiology , crustacean sound detection , and anthropogenic noise mitigation . Key collaborations exist with marine technologists and statisticians for developing machine learning boat classification systems and ecoacoustic biodiversity metrics. Research extends to auditory evoked potential thresholds across elasmobranchs, shark sleep electrophysiology , and global soundscape synthesis projects. Current projects include analyzing recreational boat noise impacts in Hauraki Gulf and investigating directional hearing mechanisms in sharks using advanced bioimaging techniques.

• Geographic Information Systems (GIS)
• Geomatics
• HBIM (Historical Building Information Modeling)
• +5 more

Fulvio Rinaudo is a Full Professor in the Department of Architecture and Design (DAD) at Politecnico di Torino, Italy, specializing in geomatics and cultural heritage documentation. With decades of experience in the field, he leads research in Geographic Information Systems (GIS), Historical Building Information Modeling (HBIM), photogrammetry, and the documentation of cultural heritage through advanced metric surveying techniques. His research interests span across multiple domains of cultural heritage preservation, including: Georeferenced databases (GIS) for cultural heritage management HBIM applications for architectural documentation and conservation Automatic digital photogrammetry for objects and contexts of varying scales Metric survey techniques for documenting historical buildings and urban contexts Digital documentation methodologies for cultural heritage preservation Rinaudo's recent scholarly output demonstrates a clear focus on advancing technological approaches to cultural heritage documentation, particularly through HBIM systems, environmental risk assessment for heritage sites, and innovative surveying methodologies. His work increasingly integrates emerging technologies like SLAM systems, 360° imaging, and cloud-based platforms to create more efficient and accurate documentation workflows. A significant portion of his recent research addresses the challenges of documenting and preserving heritage in Central Asia, particularly through the ERAMCA project focused on environmental risk assessment. Among his notable recognitions is the Best Poster Award at the CIPA Symposium awarded by ICOMOS CIPA-HD in France (2013). His leadership in the field is further evidenced by his current role as President of CIPA Heritage Documentation (2024-2027) and previous position as Secretary of ICOMOS Italy (2020-2022). Professor Rinaudo actively supervises PhD students across multiple institutions including Politecnico di Torino and Sapienza University of Rome. He has secured significant research funding through competitive grants including the ERAMCA project (Environmental Risk Assessment and Mitigation on Cultural Heritage assets in Central Asia), the RURITAGE project, and the GAMHER project (Geomatics data Acquisition and Management for landscape and built Heritage in an European Perspective). He serves on editorial boards for journals including VIRTUAL ARCHAEOLOGY REVIEW and APPLIED GEOMATICS, and participates in major international conferences as a scientific committee member for CIPA and ISPRS events. His external teaching engagements include positions at Katholieke Universiteit Leuven (Belgium) and Turin Polytechnic University in Tashkent.

• Bayesian Statistics
• Expert Knowledge Elicitation
• Robust Analyses
• +3 more

Professor John Paul Gosling is an applied statistician affiliated with the Department of Mathematical Sciences at Durham University . With a background in industry, academia, and the civil service, his work bridges statistical theory and real-world applications, particularly in criminal justice, toxicology, and climate science. Education: MMath in Mathematics (University of York, 1998–2002), PhD in Statistics (University of Sheffield, 2002–2005) Current Role: Professor in Statistics, focusing on human interaction with statistical information His research interests include: Bayesian Statistics : Developing models for complex systems Expert Knowledge Elicitation : Structuring expert input for risk assessment Uncertainty Quantification : Analyzing and communicating uncertainty in data Machine Learning Integration : Combining statistical inference with AI for decision-making Key trends from his recent articles include: Application of Voronoi Tessellations in Bayesian regression and classification Development of emulation techniques for computationally intensive models Focus on legal and public health domains Integration of copula methods for dependent variables He actively supervises PhD students in Bayesian theory and machine learning interfaces and contributes to Statistics research at Durham University.

Morteza ZihayatView profile

Associate Professor

• Data Analytics
• Human-centered AI
• Decentralized AI
• +6 more

Morteza Zihayat is an Associate Professor and Canada Research Chair (Tier 2) in Human-Centered Artificial Intelligence at Toronto Metropolitan University. He holds dual appointments in the Faculty of Engineering and Architectural Science (Department of Electrical, Computer, and Biomedical Engineering) and the Ted Rogers School of Management. Additionally, he serves as an Adjunct Professor at the University of Waterloo in Management Sciences and is a Faculty Fellow at IBM's Centre for Advanced Studies. Dr. Zihayat's educational background includes: PhD in Computer Science from York University (2016) MSc in Computer Engineering from University of Tehran (2011) Postdoctoral Research Fellowship at University of Toronto's Faculty of Information (2017) His research lies at the intersection of AI, security, and society with a focus on building fair and transparent AI systems. Dr. Zihayat's expertise spans human-centered AI, fair information retrieval systems, and blockchain-enabled AI infrastructures. His work emphasizes creating AI systems that are accountable and designed to serve the public good, with applications in healthcare, digital media, and social networks. Dr. Zihayat has received numerous accolades including the Canada Research Chair (Tier 2) in Human-Centered AI (2024), Dean's Outstanding Scholarly, Research, and Creative Activity Award (2023), Best Short Paper Award at ECIR (2023), and IBM CAS Faculty Fellowship (2021). His research has attracted over $1.7 million in external funding from agencies such as NSERC, Mitacs, and multiple industry partners including Toronto Transit Commission, The Globe and Mail, AT&T, and IBM. Dr. Zihayat serves as Associate Editor of the Computational Intelligence Journal and is an active reviewer for top-tier venues. He is also Co-director and Co-founder of the Digital Enterprise Analytics and Leadership (DEAL) Research Center.

Jignesh M. PatelView profile

Professor

• Database Systems
• Query Optimization
• Data Analytics
• +3 more

Jignesh M. Patel is a Professor in the Computer Science Department at Carnegie Mellon University, where he leads research on efficient data analysis methods. His work focuses on improving both system efficiency (e.g., high-performance data algorithms) and human efficiency (e.g., user productivity with data systems). Research Focus: Patel's group specializes in database systems, query optimization, hardware acceleration, and human-data interaction. Their interdisciplinary work spans: Transactional processing and real-time analytics Query optimization techniques Hardware-algorithm co-design Natural language interfaces for data systems Memory-efficient data processing Professional Activities: Co-founded four technology companies (Paradise, Locomatix, Quickstep, DataChat). Serves on program committees for premier conferences including SIGMOD and CIDR (as co-chair). Teaches database systems courses at CMU. Awards: Received Best Paper Award at DaMoN 2010 for work on cluster efficiency.

• Computational Biophysics
• Machine Learning
• Molecular Dynamics

Dr. Matteo Degiacomi is a Visiting Associate Professor in the Department of Physics at Durham University. His research focuses on integrative computational methods combining machine learning and molecular dynamics simulations to model biomolecular systems at near-atomistic resolution. Education: MSc in Computer Science (2008), PhD in computational biophysics (2012) from EPFL. His work leverages ion mobility , cross-linking , SAXS , and electron microscopy data to study protein assembly mechanisms. Recent publications highlight applications in virology , nanomaterials , and membrane protein dynamics . He develops open-source tools like ClayCode and JabberDock . Scientific awards include a Swiss National Science Foundation Early Postdoc Mobility Fellowship (2013-2017) and an EPSRC Junior Research Fellowship (2017-2020). He supervises postgraduate researchers Ajeeth Kanagarajan , Breanna Voss , and Listra Ginting .

Patrick DohertyView profile

Professor

• Cardiovascular Disease Prevention
• Cardiac Rehabilitation
• Exercise Physiology
• +13 more

Professor Patrick Doherty, Chair of Cardiovascular Health at the University of York's Department of Health Sciences, is a leading figure in cardiovascular disease prevention and rehabilitation. As Director of the National Audit of Cardiac Rehabilitation (NACR) and former president of the British Association for Cardiovascular Prevention and Rehabilitation (BACPR), he has shaped national and international clinical guidelines, including the EXPert Working Group Consensus on exercise prescription and the DIAMONDS Programme for diabetes self-management in severe mental illness. His research, funded by NIHR, BHF, and Janssen, has driven NHS policy changes and earned a world-leading REF 2021 impact case. Research Interests His work spans: Cardiovascular disease prevention and cardiac rehabilitation Exercise physiology and physical activity interventions Patient self-management strategies Health service policy and registry-based research Multimorbidity analysis and mHealth applications Systematic reviews and implementation science Recent publications highlight his focus on cost-effective rehab models, psychological interventions (PATHWAY Programme), and digital health integration via projects like REACH-HF and PERFORM. Scientific Awards Fellow of the European Society of Cardiology University of York External Engagement Award (2014) Janssen Healthcare Innovation Award (2014-2016) Advising and Grants Doherty has supervised 16 PhD students (11 international), including current researchers Kholoud Alotaibi and Mosab Alhejaili. His funded projects include: NIHR Programme Grant (£2.8M) for DIAMONDS BHF Research Grants (£399,548 & £453,000) Strategic Initiative Funded Project (£25,000) PATHWAY Programme (£1.995M) for heart failure rehab Laboratories & Teams He leads the Cardiovascular Health Research Group (hosting NACR) and collaborates globally with institutions like the University of Copenhagen, National University of Malaysia, and University of Heidelberg.

Stefan BöttcherView profile

Professor

• Databases
• Data Compression
• Graph Algorithms
• +3 more

Prof. Dr. Stefan Böttcher serves as Professor and Section Owner of Databases and Electronic Commerce within the Department of Computer Science at the University of Paderborn's Faculty of Computer Science, Electrical Engineering and Mathematics. His office (F2.217, Fürstenallee 11) operates by email appointment, and he teaches courses including Betriebssysteme (Operating Systems), maintaining active academic engagement through current publications and institutional roles. His research centers on advanced data compression methodologies for complex structures, specializing in grammar-based techniques for graphs, strings, and trees. Key focus areas include enabling efficient query processing directly on compressed representations—critical for semantic web triple stores and big data systems—while optimizing storage-performance tradeoffs through novel algorithmic approaches in Burrows-Wheeler transforms and tree recompression. Analysis of his 2018-2025 publications reveals consistent innovation in compressing non-linear data structures: from RECUT's tree recompression to 2025's string partitioning for BWTs, his work bridges theoretical algorithm design with practical database applications, particularly targeting high-performance querying in grammar-compressed graph frameworks for RDF triple stores. Scientific Awards No awards documented in source materials Prof. Böttcher mentors graduate researchers in database compression technologies through his Databases and Electronic Commerce section, with research outcomes published in premier venues like IEEE DCC and Big Data conferences. His projects demonstrate sustained funding through continuous high-impact outputs without explicit grant documentation in the provided texts. He leads the Databases and Electronic Commerce research group, driving innovations in compressed data structures that reduce storage overhead while maintaining query efficiency for semantic web and large-scale graph database implementations.

Wei LiView profile

Professor

• Computer Security
• Network Security
• Artificial Intelligence
• +3 more

Wei Li is a Professor in the Department of Computing at Nova Southeastern University's College of Computing & Engineering. He joined NSU in 2005 after earning his Ph.D. from Mississippi State University. His research focuses on enhancing computer system security through interdisciplinary approaches, including network security, artificial intelligence applications, and software engineering practices. Dr. Li’s research areas encompass computer security, network security, software engineering, artificial intelligence, and database systems. His work bridges theoretical advancements and practical cybersecurity solutions, such as improving intrusion detection systems, analyzing social engineering attack vulnerabilities, and developing machine learning models for IoT security. His recent publications (2020–2025) address topics like password policy effectiveness, remote worker cybersecurity risks, and adaptive deep learning models for anomaly detection. These contributions highlight his focus on mitigating organizational cybersecurity risks through empirical studies and innovative technical solutions. No scientific awards or grants are explicitly listed in the provided information. His advising record remains unspecified, and no active labs or teams are mentioned.