جست‌وجوی استاد و پژوهشگر

Christian Alexander Hildebrandمشاهده پروفایل

استاد

• Marketing Analytics
• Digital Marketing
• Behavioral Science
• +۴ مورد دیگر

Christian Alexander Hildebrand is a Full Professor of Marketing Analytics and Director of the Institute of Behavioral Science and Technology (IBT-HSG) at the University of St. Gallen. His research bridges Human-Computer Interaction (HCI) and consumer behavior, focusing on digital voice assistants, chatbots, and mobile devices. He holds post-doctoral affiliations with Stanford University, Duke University, and the University of Michigan. Education: Doctoral studies and post-doctoral visits at Stanford, Duke, and University of Michigan His research emphasizes methodologies like large-scale field experiments and feature extraction from voice/image/text data. Key themes include consumer-firm interface optimization and technology's impact on decision-making. His work appears in top journals such as Journal of Consumer Research and Information Systems Research . Awarded the Swiss Academy of Marketing Science’s 'Rigor and Relevance Award,' his research is funded by public/private institutions and disseminated through practitioner outlets like NIM Marketing Intelligence Review . He teaches Machine Learning for Marketers, Web Data Analytics, and experimental design. Grants: Supported by major public/private institutions Labs/Teams: Leads IBT-HSG, collaborating with corporations in retail, consumer electronics, automotive, and finance sectors

Chuan Yueمشاهده پروفایل

استاد

• Cybersecurity
• Web Security
• Mobile Security
• +۷ مورد دیگر

Chuan Yue is a Professor of Computer Science at the Colorado School of Mines (Mines), leading research in Cybersecurity with a focus on Web, Mobile, Cloud, CPS/IoT, and AI systems security. He founded the Center for Cyber Security and Privacy (CCSP) at Mines and serves as its point of contact. His research emphasizes usable security, privacy, vulnerability analysis, and cybersecurity education. Education: B.E. and M.E. in Computer Science from Xidian University (China, 1996/1999), Ph.D. in Computer Science from College of William and Mary (2010). Pre-Mines career: Bell Labs (1999-2003) and University of Colorado Colorado Springs (UCCS, 2003-2013). Awards include the Daniels Fund Faculty Fellowship (2016-2019) and an Outstanding Paper Award at CODASPY 2018. Research interests span security/privacy in web-based systems, human-computer interaction, and distributed computing. His work is funded by NSF, DOD, and Meta. Key contributions include PolicyChecker for GDPR compliance analysis, WtaGraph for web tracking detection, and studies on smart home privacy negotiation. Over 50 peer-reviewed publications in top venues like IEEE S&P, CCS, and CHI. Advised numerous PhD, Master’s, and undergraduate researchers, emphasizing interdisciplinary collaboration with industry/government. Developed security tools like LoginInspector (best paper at LISA 2012) and SafeSky cloud middleware.

Sebastian Diehlمشاهده پروفایل

استاد

• Aquatic Ecology
• Ecological Modeling
• Climate Change Impacts on Ecosystems
• +۵ مورد دیگر

Sebastian Diehl is a Professor at Umeå University's Department of Ecology, Environment and Geoscience. His research focuses on mathematical modeling of aquatic ecosystem dynamics, with particular emphasis on consumer-resource interactions and climate change impacts on northern lake ecosystems. Current affiliations: Umeå University (Department of Ecology, Environment and Geoscience) Previous affiliations: Ludwig-Maximilians-Universität München (Professor of Aquatic Ecology) Academic background: Biology undergrad from University of Göttingen, PhD in Animal Ecology from Umeå University (1994) Research interests center around aquatic ecosystem dynamics in response to environmental change, including: Climate change effects on lake ecosystems (temperature and terrestrial nutrient inputs) Mathematical modeling of consumer-resource interactions Benthic-pelagic coupling in nutrient and energy flows Phytoplankton-zooplankton dynamics under environmental stressors Trophic interactions in stream and lake systems Stoichiometric constraints on ecosystem function His recent publications (2025-2020) demonstrate an integrated approach combining mathematical modeling with experimental validation through field studies and lab experiments, focusing particularly on: Climate-induced regime shifts in lake ecosystems Stoichiometric mismatch in warming systems Functional response modeling Vertical niche partitioning in plankton Resource acquisition trade-offs Browning impacts on primary producers Administrative roles include: Final examiner for PhD education Chair of Umeå Marine Science Centre advisory council Steering group member of Integrated Science Lab (IceLab)

• Artificial Intelligence
• Geospatial Data Science
• Knowledge Graphs
• +۵ مورد دیگر

Professor Manolis Koubarakis is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on geospatial data science, knowledge graphs, entity resolution, and AI applications in Earth observation. He leads projects like ExtremeEarth and Plato, advancing semantic data cube systems and geospatial question answering engines. His work bridges AI and geospatial technologies, with contributions to frameworks like pyJedAI and Strabo 2 for managing big geospatial data. Research Interests include: Geospatial Question Answering Systems Entity Resolution and Entity Linking Ontology-Based Data Access (OBDA) Knowledge Graph Construction and Applications Earth Observation Data Analytics AI for Geoinformatics Notable Projects: ExtremeEarth: Combines Copernicus satellite data with machine learning for environmental analytics. Plato: Semantic data cube system enabling advanced querying of multidimensional datasets. GeoQA2: A geospatial question answering engine evaluated on large benchmarks. JedAI Family: Tools for scalable entity resolution in structured/semi-structured data. His publications span 20+ years, with recent emphasis on: AI-driven Earth observation systems Geospatial RDF benchmarking 3D geospatial interlinking Large language models for legal and health content delivery

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Masoud Makrehchi is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. His research focuses on Natural Language Processing, Artificial Intelligence, Machine Learning, and Social Computing, with a strong emphasis on applications in network science and moral AI. He holds a PhD from the University of Waterloo (2007), along with earlier degrees from Shiraz University and Iran University of Science and Technology. Prior to academia, he worked as a Senior Research Scientist at Thomson Reuters (2008–2012) and completed a postdoctoral fellowship at the University of Waterloo (2007–2008). His research expertise includes text mining, social network analysis, and network science, addressing challenges such as signed social network analysis, document classification, and crime trend prediction using social media data. He has received several awards, including the NSERC Postgraduate Scholarship and the SBP Challenge Award (2012). His work spans over 50 peer-reviewed publications in journals like Expert Systems with Applications, Social Network Analysis and Mining, and Web Intelligence, with contributions to conferences such as GECCO and IEEE/ACM. Dr. Makrehchi’s publications highlight innovations in feature selection, text segmentation, and AI-driven frameworks for requirements elicitation. His recent work explores coherence graphs for text segmentation, generative AI in education, and bias detection in medical datasets. He has also contributed to patent applications related to sentiment analysis and text extraction systems.

Franjo Ceceljaمشاهده پروفایل

استاد

• Systems Engineering for Energy and Industrial Applications
• Optimisation and Decision Making
• Knowledge Modelling (Ontology Engineering)
• +۳ مورد دیگر

Dr. Franjo Cecelja is a Reader in the School of Chemistry and Chemical Engineering at the University of Surrey. He holds a Dipl. Eng. from the University of Zagreb, an M.Sc. from Cranfield Institute of Technology, and a Ph.D. from Brunel University. His research focuses on systems engineering for energy and industrial applications, optimization, decision making, and semantic technologies. He has led projects such as the FP7 (Marie Curie LTN) initiative on renewable energy systems engineering (£425k, 2013–2018). His work spans ontology engineering applications in biorefining, waste valorization, and sustainable processing. Notable contributions include semantic frameworks for model and data integration in biorefineries and decision support systems for industrial symbiosis. Education: Ph.D., Brunel University (Optical Sensors for Electric Fields) M.Sc., Cranfield Institute of Technology (Control & Signal Processing) Dipl. Eng., University of Zagreb (Aerospace Technology) His research interests integrate ontology engineering with process systems engineering to address challenges in biorefining, industrial symbiosis, and sustainable resource management. Recent publications emphasize semantic technologies for waste valorization, PFAS treatment, and decision-making frameworks in biorefining. Dr. Cecelja’s FP7 project demonstrated leadership in renewable energy systems, leveraging semantic networking facilities and value chain optimization. His work bridges academic research with industrial applications, emphasizing circular economy principles and model-driven decision support. Labs/Teams: His research is conducted within the University of Surrey’s School of Chemistry and Chemical Engineering facilities, collaborating with interdisciplinary teams on biorefining and process systems engineering.

Siamak Shahandashtiمشاهده پروفایل

مدرس ارشد

• Cyber Security
• Privacy-Enhancing Technologies
• Applied Cryptography
• +۴ مورد دیگر

Dr. Siamak Shahandashti is a Senior Lecturer in the Department of Computer Science at the University of York, UK. He leads the Cyber Security & Privacy Research Group and is actively involved in academic governance roles including Chair of the Physical Sciences Ethics Committee and Programme Lead for the MSc Cyber Security programme. His research focuses on applied cryptography, privacy-preserving technologies, electronic voting systems, and blockchain applications. He holds a PhD in Computer Science and has contributed to over 40 peer-reviewed publications. Education: PhD in Computer Science, MSc in Telecommunications Engineering, BSc in Electrical Engineering. Professional qualifications include a PGCert in Academic Practice. Research interests span cyber security fundamentals, usable security mechanisms, and the intersection of cryptography with real-world systems. Notable projects include verifiable electronic voting systems and DoS-resilient blockchain protocols. He has led funded projects on e-voting scalability and contributed to standards reviews for ISO/IEC protocols. Award-winning educator in cyber security curriculum development, with active roles in admissions and academic ethics compliance. His work bridges theoretical cryptography with practical implementations, emphasizing user-centric security design principles. Labs/Teams: Cyber Security & Privacy Research Group (lead), Departmental Ethics Team (lead). Collaborations include institutions in Australia, France, and across Europe.

Phillipa Gillمشاهده پروفایل

دانشیار مدعو

• Computer Networking
• Cybersecurity
• Network Measurement
• +۳ مورد دیگر

Phillipa Gill is an Adjunct Associate Professor at the University of Massachusetts Amherst and a Research Scientist at Google, focusing on the Measurement Lab Project. She holds a Ph.D. in Computer Science from the University of Toronto (2012) and completed a postdoctoral fellowship at the Citizen Lab, Munk School of Global Affairs. Her research emphasizes computer networking and security, particularly network measurement techniques to study online information controls, routing security, and traffic differentiation. Education: Ph.D. in Computer Science, University of Toronto (2012) Postdoctoral Fellowship, Citizen Lab, University of Toronto (2012–2013) M.Sc. in Computer Science, University of Calgary (2007–2008) Bachelor’s Degree (not explicitly stated) Research Interests: Gill’s work addresses network interference, reliability, and security. She develops tools like the ICLab platform for measuring online censorship and collaborates across disciplines, including law and political science. Recent projects include analyzing China’s DNS censorship and evaluating domain name encryption privacy. Key Activities: General co-Chair, ACM Internet Measurement Conference (2016) Program co-Chair, USENIX FOCI (2015) and ACM CoNEXT Student Workshop (2013) Area Editor, ACM SIGCOMM Computer Communications Review (2013–2015) Awards: NSF CAREER Award, Google Research Award Best Paper Awards at IMC (2013) and PAM (2008) IBM Best Presentation Award (Cloud Computing) Anita Borg Fellowship finalist (2009–2010) Labs & Outreach: Leads the ICLab and Calipr Research Group. Co-founded the LED-Programming-Workshop to engage pre-college students in programming and STEM. Active in promoting diversity, such as hosting Women in Computer Science events.

Evimaria Terziمشاهده پروفایل

استاد

• algorithmic data mining
• network analysis
• recommendation systems
• +۳ مورد دیگر

Evimaria Terzi is a Professor and Department Vice Chair at Boston University (BU), affiliated with the Data Management Lab@BU. Her research focuses on algorithmic data mining with applications in network analysis, recommendation systems, ranking, and clustering. She holds a PhD from the University of Helsinki and has held prior roles at IBM Almaden Research Center (2007–2009) and the Helsinki Institute for Information Technology (HIIT) before 2007. Her work spans theoretical and applied domains, including team formation algorithms, fairness in AI, and large language model evaluation. Notable contributions include studies on LSM tree optimization, counterfactual explanations for auditing fairness, and the dynamics of memorization in LLMs. Her recent publications emphasize flexibility in database systems and ethical AI practices. Evimaria’s research has been recognized through her contributions to conferences like WSDM and KDD, where she has served in organizing roles. The themes of her work consistently bridge algorithmic innovation with real-world applications in social networks, healthcare, and collaborative systems.

Michael Foxمشاهده پروفایل

استادیار

• digital humanities
• philosophy and ethics of AI
• natural language processing
• +۵ مورد دیگر

Michael Fox is a Teaching Assistant Professor in the School of Information and Library Science (SILS) at the University of North Carolina at Chapel Hill. Prior roles include Senior Lecturer and Academic Director for the Digital Studies of Language, Culture, and History program at the University of Chicago, and Assistant Editor/Software Architect of the William Blake Archive. He holds a PhD in English and BS in Computer Science. His research bridges literary criticism and information science, focusing on digital humanities, AI ethics, and textual studies. Key areas include graph databases, network analysis, and AI methods in literary history, alongside studies of Aestheticism, poetics, and literary history. His first book examines intersections between literary and historical writing, using computational approaches like graph databases. Michael has contributed to the William Blake Archive, a pioneering digital humanities project, and serves on the editorial board of Textual Cultures . His courses span literature, information science, and their intersections (e.g., Digital Humanities, The Idea of AI). His work earned the ADE 2017 Featured Project award for the Blake Archive's redesign. Grants and advising details are pending explicit mentions in texts.

Olakunle Olayinkaمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Digital Forensics
• Gamification in Education
• +۳ مورد دیگر

Dr. Olakunle Olayinka is a Senior University Teacher and Deputy School Director of Education in the Department of Computer Science at the University of Sheffield. He is a member of the Institute of Coding and has over a decade of experience in IT and academia. Prior to his current role, he worked as a Research Assistant at the University of Gloucestershire, teaching Cybersecurity and related modules. He holds a PhD in Computing from the University of Gloucestershire, alongside an MSc in Computer Forensics and BSc in Computer Science from Babcock University and University of Glamorgan respectively. His research focuses on Cybersecurity & Gamification , Digital Forensics , and Information Systems Adoption . He has contributed to studies on generative AI in education, cybersecurity training methodologies, and digital transformation strategies for small businesses. Recent work includes exploring AI-driven approaches to web application security and IoT threat hunting using bio-inspired models. His publications span journals like Sustainability and Journal of Applied Learning & Teaching , with a focus on bridging educational technology gaps and enhancing cybersecurity practices. He has co-authored book chapters on digital transformation in Nigerian enterprises and cybersecurity frameworks. Teaching responsibilities include Cybersecurity Team Project, Cyber Threat Hunting, and Software Engineering modules. He advocates for project-based learning approaches, as demonstrated in his work on Agile methodologies in software projects.

• IoT Security
• Network Measurement
• Privacy Engineering
• +۳ مورد دیگر

Dr. Anna Maria Mandalari is an Assistant Professor at University College London (UCL), affiliated with the Electronic and Electrical Engineering Department. She serves as Director of the SafeNetIoT laboratory and the Internet Engineering/Telecommunications MSc/MRes Programme at UCL. She holds an Honorary Research Fellow position at the Institute for Security Science and Technology at Imperial College London. Her research focuses on IoT security, privacy engineering, and network measurement techniques, particularly analyzing information exposure from consumer devices and developing adaptive network security strategies. Her work has led to significant contributions such as the IMC'19 Community Contribution Award-winning study on multidimensional IoT device exposure and the Telekom Challenge-winning IoTrim prototype for blocking non-essential IoT traffic. She has secured funding through InnovateUK’s CyberASAP program and participated in high-impact projects like NATwatcher and the European roaming analysis initiative. Key Awards: Community Contribution Award (IMC'19), Best Paper Award (C2B(I)D 2015) Grants: InnovateUK CyberASAP Phase 2 funding, Telekom Challenge Development Stream Top 5 prize Labs/Teams: Director of SafeNetIoT Lab, Leading M2M and IoT security teams at UCL Her recent work addresses IoT device misactivation risks (e.g., smart speakers), scalable detection of IoT devices in the wild, and protocol design informed by crowdsourced data. She actively collaborates with industry partners like Telekom and academic institutions on network infrastructure security and performance optimization.

• Climate Change Mitigation
• Industrial Ecology
• Life Cycle Assessment (LCA)
• +۷ مورد دیگر

Francesco Cherubini is a Professor and Director of the Industrial Ecology Programme at NTNU's Department of Energy and Process Engineering. He leads multidisciplinary research on climate change mitigation, environmental sustainability, and bio-based systems. His work integrates field studies, climate models, and life cycle assessment (LCA) to evaluate energy systems, land use, and technological innovations. Education & Roles: Professor at NTNU since [year not explicitly stated, inferred from roles] Lead Author for IPBES Nexus Assessment Report and IPCC Special Report on Climate Change and Land Director of the Industrial Ecology Programme Research Focus: Climate impacts of energy systems and land use (agriculture, forestry) Sustainable bioenergy and bio-based technologies (biofuels, biorefinery) Environmental impacts of hydrogen, aviation fuels, and industrial processes Climate-smart agriculture and land management strategies Life cycle assessment methodological advancements Key Projects (2020–2027): LCA4BIO: Harmonized LCA methods for bio-based systems ICARUS: Sustainable aviation biofuels development HYDROGENi: Norwegian hydrogen innovation center AGRISCASCADE: Circular fertilizers from agricultural waste SusLand: Sustainable land management for climate mitigation Scientific Recognition: Web of Science 'Highly Cited Researcher' (top 1% by citations) Teaching: Graduate course TEP 4300: 'Climate Change Mitigation'

Richard Boyceمشاهده پروفایل

دانشیار

• Clinical Decision Support Systems
• Pharmacovigilance
• Drug Interaction Analysis
• +۳ مورد دیگر

Richard Boyce is an Associate Professor in the Department of Biomedical Informatics at the University of Pittsburgh's School of Computing and Information. His work focuses on clinical decision support systems (CDSS), pharmacovigilance, and distributed knowledge bases. He leads research in drug interaction analysis, particularly involving natural products like cannabis, and develops machine learning tools for healthcare applications. His address is 530 DBMI Building, Pittsburgh, PA 15260, with contact email rdb20@pitt.edu. Boyce’s research integrates clinical and pharmacological data to improve patient safety through advanced analytics. Recent projects include predicting Alzheimer’s disease using EHR data, falls prediction in nursing homes, and optimizing CDSS modules for resource-limited settings. His team also develops open-source knowledge graphs for life sciences, enhancing data interoperability. Education: Details not explicitly listed in the provided text. Labs/Teams: Affiliated with the Department of Biomedical Informatics and School of Computing and Information at Pitt. Publications highlight his contributions to pharmacovigilance signal detection, machine learning in healthcare, and ontology engineering. Notable works include studies on cannabis-drug interactions and CDSS design for clinical practice.

James Bradburyمشاهده پروفایل

مدرس

• Machine Learning
• Sound Art
• Computer Music
• +۳ مورد دیگر

James Bradbury is a Music Lecturer at the Conservatorium of Music, University of Western Australia. He holds a PhD in Music Technology (2021) from the same institution. His research focuses on integrating machine learning into music creation and performance, with expertise in sound art, experimental art, and software development for creative applications. Previously, he served as a Post-Doctoral Research Fellow in Creative Coding at the University of Huddersfield (2021–2022). Education: Doctor of Philosophy in Music Technology, University of Western Australia (2021) Research Interests : Bradbury explores machine learning's role in shaping contemporary music through real-time interactive systems, sound art installations, and experimental music performance. His work emphasizes computational tools for creative processes, including the Fluid Corpus Manipulation (FluCoMa) platform, which enables novel compositional workflows. He investigates how algorithmic approaches can expand artistic expression while maintaining human creativity at the core. Research Trends : Recent works highlight interdisciplinary collaborations between music and computer science, particularly in developing open-source tools like FluCoMa. His performances and publications demonstrate a focus on non-narrative musical forms and real-time algorithmic generation. The 2025 Audible Edge performance exemplifies this through live machine learning-driven sample selection. Awards and Grants : No specific awards or grants mentioned in the provided texts. His contributions are primarily reflected in creative outputs and academic publications. Labs and Teams : Active within the Conservatorium of Music, Bradbury collaborates with institutions like the University of Huddersfield and participates in festivals such as Audible Edge. His work is closely tied to the FluCoMa research collective, emphasizing open-source software development for artistic innovation.