جست‌وجوی استاد و پژوهشگر

• Research Data Management
• Semantic Web Technologies
• Machine Learning
• +۳ مورد دیگر

Tomasz Miksa is a researcher affiliated with TU Wien's Department of Research Data Management, focusing on machine-actionable data management plans (maDMPs), semantic web technologies, and data reproducibility. He collaborates extensively on projects involving automated assessment of data management workflows, FAIR data implementation, and privacy-preserving analysis platforms. Primary affiliation: TU Wien Department: Research Data Management Key projects: WellFort, FAIR Data Austria, openEO API His research integrates semantic technologies with data governance to enhance reproducibility in scientific workflows, particularly in domains like environmental monitoring and legal informatics. Recent publications emphasize ontological frameworks (DCSO), API harmonization, and auditable machine learning systems. Notable collaborative works include: Reproducibility standards for soil moisture data Knowledge graph applications in cyber-physical energy systems Dynamic data citation mechanisms He supervises students in theses related to maDMP integration, data citation frameworks, and institutional research data planning architectures.

• Multiple Sclerosis
• Neurogenetics
• Bioinformatics
• +۵ مورد دیگر

Sergio Baranzini is a Professor in the Department of Neurology at the University of California, San Francisco (UCSF) School of Medicine and a member of the UCSF Weill Institute for Neurosciences. With a distinguished career spanning over two decades at UCSF, Dr. Baranzini has established himself as a leading researcher in multiple sclerosis (MS) and neuroimmunology. Dr. Baranzini earned his BS/MS and PhD in Biochemistry/Biotechnology and Human Molecular Genetics from the University of Buenos Aires, Argentina, completing his PhD with honors in 1997. He then pursued postdoctoral training in neurogenetics at UCSF before joining the faculty in 2003. His research focuses on the genetic, genomic, and immunological aspects of multiple sclerosis, with particular emphasis on the gut-brain axis and microbiome's role in neuroinflammation. Dr. Baranzini's research employs a multidisciplinary approach integrating wet lab techniques (including DNA microarrays, proteomics, and laser capture microdissection) with dry lab analytical approaches (bioinformatics, complexity theory, and mathematical modeling). His work has revealed critical insights into MS pathogenesis, particularly how gut microbiota influences disease development and progression. Recent groundbreaking studies have demonstrated how specific gut bacteria from MS patients can trigger MS-like disease in animal models and how microbial metabolites affect remyelination processes. His laboratory has secured significant funding through multiple NIH grants, including as Principal Investigator on projects examining the genetic basis of MS progression and post-GWAS approaches to identify cell-specific genetic pathways underlying MS risk. As evidenced by his extensive publication record in top-tier journals including Science, Nature, and PNAS, Dr. Baranzini's work represents some of the most innovative research in neuroimmunology and MS pathogenesis. National Multiple Sclerosis Society (US) Advanced Postdoctoral Fellowship (2001) National Multiple Sclerosis Society (US) Harry Weaver Neuroscience Scholar Award (2009-2014) Department of Neurology UCSF Endowed Chair in Neurology (2010) National Multiple Sclerosis Society Stephen C. Reingold Award (2015) Department of Neurology UCSF Distinguished Professorship in Neurology I (2019) Department of Neurology UCSF Neurology Research Incentive Program 2 (N-RIP2) (2023) Barancik Prize for Innovation in Multiple Sclerosis Research (2024) Dr. Baranzini serves as an ad-hoc reviewer for numerous specialized journals and is an elected member of the American Neurological Association. His laboratory (iMSMS) actively collaborates with interdisciplinary teams worldwide to integrate knowledge across research domains through systems biology approaches. His current NIH-funded research explores automated evidential support from raw data for relay agents in biomedical knowledge graph queries and investigates the genetic basis of progression in multiple sclerosis.

Raymond Chengمشاهده پروفایل

پژوهشگر

• Security
• Privacy
• Distributed Systems
• +۵ مورد دیگر

Raymond Cheng is a Researcher and blockchain lecturer with a focus on security, privacy, and distributed systems. He earned his Ph.D. in Computer Science from the University of Washington and holds degrees in Physics, Electrical Engineering, and Computer Science from MIT. His research spans blockchain scalability, privacy-preserving protocols, and decentralized infrastructure. Key projects include Kariba Labs , MASQ Foundation , and Open Source Observer , where he works on tools for public goods funding, secure smart contracts, and open-source analytics. Raymond's publications highlight advancements in blockchain-based databases (FalconDB), confidential smart contracts (Ekiden), and privacy-preserving messaging (Talek). His work often intersects with internet freedom and secure, scalable systems. He co-founded multiple organizations, including the Decentralization Institute and Public Goods Foundation , and has been featured in Forbes , Wired , and MIT Technology Review for his contributions to privacy and blockchain innovation.

Mario Alvianoمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Combinatorial Search and Optimization
• +۵ مورد دیگر

Mario Alviano is a Full Professor in Computer Science (INF/01) at the University of Calabria, Department of Mathematics and Computer Science. He leads the LAIA lab (Laboratorio di Applicazioni dell'Intelligenza Artificiale) and serves as co-PI in the PRIN project PRODE ('Probabilistic Declarative Process Mining'). Current projects: FAIR ('Future AI Research'), Tech4You ('Technologies for climate change adaptation'), SERICS ('SEcurity and RIghts in the CyberSpace'), CAL.HUB.RIA , RADIOAMICA , and STROKE 5.0 His research focuses on Answer Set Programming (ASP), particularly in optimization, nonmonotonic reasoning, and applications to logistics, healthcare, and cybersecurity. He has authored over 120 publications in top venues like AIJ, AAAI, and IJCAI. Recent academic contributions includes work on: Temporal Many-valued Conditional Logics Weighted Knowledge Bases with Typicality Explainable AI via xASP and ASP Chef Defeasible Reasoning Scalability Notable awards: Artificial Intelligence Award 'Marco Somalvico' (2017) ICLP Best Paper Awards (2015, 2016) LPNMR Best Paper Award (2022) CILC Best Paper Award (2023)

Abbas Razaghpanahمشاهده پروفایل

پژوهشگر

• Internet Privacy
• Network Security
• Mobile Security
• +۴ مورد دیگر

Abbas Razaghpanah is a Researcher at the International Computer Science Institute (ICSI) , focusing on Internet privacy, security, and network measurement . He earned his PhD at Stony Brook University and previously interned at ICSI, leading the Haystack Project and developing the Lumen app . Research Focus: Mobile app security, TLS deployment, censorship measurement, and traffic differentiation Key Projects: Haystack, Lumen, ICLab Scientific Awards : ACM Research Competition Runner-Up Award Open Technology Fund Information Controls Fellowship ACM IMC 2018 Distinguished Paper Award His work involves collaboration with Citizen Lab at the University of Toronto and includes grants for studying global information controls. Abbas develops tools for user-space network monitoring to enhance transparency and regulatory compliance.

Alexandra Krollمشاهده پروفایل

پژوهشگر

• Ecotoxicology
• Environmental Risk Assessment
• Nanotoxicology
• +۳ مورد دیگر

Alexandra Kroll is a Researcher at the Ecotox Center (Eawag) since 2019, specializing in Environmental Risk Assessment and Ecotoxicology . Her work focuses on micropollutants, nanoparticles, microplastics, and pesticides in aquatic systems, with a particular emphasis on regulatory frameworks and chemical safety. PhD in Nanotoxicology (University Hospital Münster, 2006-2009) Postdoctoral research at Eawag (2010-2016) Her research interests span environmental risk assessment of pharmaceuticals, nanoparticle interactions with biofilms, microplastic effects on freshwater organisms, and pesticide regulation. Recent projects include evaluating UV-filters in Swiss lakes and deriving environmental quality standards. Key scientific contributions involve flow cytometry for biofilm analysis , pH-specific aquatic thresholds , and landscape-based ERA frameworks . She has been recognized with the SNSF Ambizione Fellowship (2010-2016) for her nanotoxicology research.

• Big Data Analytics
• Cloud Computing
• Data Stream Processing
• +۴ مورد دیگر

Yanlei Diao is a Professor of Computer Science at École Polytechnique (France) with a joint appointment at the University of Massachusetts Amherst. She received her PhD from UC Berkeley in 2005. Her research focuses on scalable data systems, particularly in big data analytics, cloud computing optimization, and real-time stream processing. Research Interests: Her work spans cloud infrastructure optimization (UDAO project), explainable anomaly detection in data streams (EXAD), interactive data exploration (AIDEme), genomic data analysis (GESALL), and uncertain data management (CLARO). She leads the CEDAR team at Inria/LIX focusing on cloud-scale data exploration. Awards & Honors: ERC Consolidator Grant (2017-2023) CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) Keynote speaker at ACM DEBS 2021 and SWIFT 2023 AI Forum Best Paper Award at SIGMOD 2011 ACM SIGMOD Dissertation Honorable Mention (2005) Advising & Leadership: Mentored over 20 PhD students and postdocs, currently supervising 7 researchers. Served as PVLDB PC Co-Chair (2025-2026) and ACM SIGMOD Editor-in-Chief (2014-2019). Leads multiple projects with industry partners including Alibaba Cloud.

Scott Shriverمشاهده پروفایل

دانشیار

• Online Privacy
• Network Effects
• Sustainability
• +۵ مورد دیگر

Scott Shriver is an Associate Professor of Marketing at the Leeds School of Business , University of Colorado Boulder . He holds a PhD in Marketing from Stanford University , with additional Master's degrees in Economics and Physics from Stanford, and an MBA from UCLA Anderson School of Management . His research spans online privacy , network effects , sustainability , empirical industrial organization , and applied econometrics . Education : PhD (Marketing, Stanford), MA (Economics, Stanford), MA (Physics, Stanford), MBA (UCLA) Shriver's publications appear in Management Science , Marketing Science , and Marketing Letters . His work on GDPR's economic impacts (2024) and ethanol market diffusion (2015) has earned John D.C. Little Awards (2015, 2020) and the Frank M. Bass Dissertation Award (2015). He teaches Customer Analytics across degree levels and Quantitative Marketing in the PhD program. Recent research trends include privacy regulation , multi-channel demand analysis , and user-generated content on digital platforms. Earlier works from his physics background include planetary studies (1994) but his modern focus remains on digital economics and sustainable business practices . Scientific Awards : John D.C. Little Award (2015, 2020) Frank M. Bass Award (2015) Swiss Academy of Marketing Science Award (2014) Shriver advises PhD students and contributes to curriculum development in analytics programs. His personal faculty website hosts working papers and publications. Office hours are held in Koelbel 429 .

Jim Clarkمشاهده پروفایل

مدرس ارشد

• E-commerce
• Information Systems
• Data Analytics
• +۲ مورد دیگر

Jim Clark is a Senior Lecturer at the University of Lethbridge's Dhillon School of Business, specializing in E-commerce and Information Systems. He has been teaching at the institution since 1990 and maintains an active presence through his course instruction and professional blog. His educational background includes degrees from BYU and Ivey School of Business. Clark's professional experience extends beyond academia, with previous positions at Revenue Canada, Shell Canada, and Drowland Technologies, along with numerous small business consulting projects. Clark's research and teaching interests focus on E-commerce, Information Systems, Data Analytics, and Data Visualization, with particular emphasis on financing, organizational design, and entrepreneurship within E-commerce organizations. His work explores the application of technology in business contexts and classroom pedagogy. His recent publications and blog posts demonstrate consistent engagement with current technology trends affecting business, including digital advertising evolution, AI in finance, e-commerce strategies, and ethical considerations in technology adoption. These works reflect his commitment to connecting academic concepts with real-world business applications. Clark teaches Management of Information Systems (MGT 3061) and maintains an active online presence through his blog 'Info Systems in Practice' where he discusses relevant technology topics for business students and professionals. He has developed extensive teaching materials including video lectures, chapter projects, and discussion questions that integrate current business technology examples with core information systems concepts. His teaching approach emphasizes practical application of information systems knowledge in business decision-making contexts.

Aryan Pasikhaniمشاهده پروفایل

مدرس

• Intrusion Detection and Prevention Systems
• Reinforcement Learning
• Machine Learning
• +۹ مورد دیگر

Dr. Aryan Pasikhani is a Lecturer in Cybersecurity at the University of Sheffield , affiliated with the Security of Advanced Systems research group . Holding a PhD from the same institution, his research focuses on Intrusion Detection Systems , Reinforcement Learning , and Quantum Computing applications in security. Specializes in securing Embedded Systems and Internet of Things architectures Active in Adversarial Machine Learning and Privacy-Preserving Technologies Peer-reviewer for IEEE Internet of Things Journal and IEEE Transactions on Industrial Informatics His recent work explores 6LoWPAN security through reinforcement learning and Federated Learning frameworks for privacy-preserving data analysis. Awards include Fellow of the Higher Education Academy . Current grants involve real-time ransomware detection (CipherGrit) and automated threat modeling for AI systems. He supervises four PhD students and teaches Security of Control and Embedded Systems .

Salvatore Ramponeمشاهده پروفایل

دانشیار

• Machine Learning
• Cybersecurity
• Internet of Things (IoT)
• +۷ مورد دیگر

Salvatore Rampone is an Associate Professor at the Department of Law, Economics, Management and Quantitative Methods (DEMM) of Università degli Studi del Sannio (Unisannio). His research focuses on Machine Learning , Internet of Things (IoT) , and Cybersecurity , with applications in intrusion detection, bioinformatics, and financial systems. Research Interests : Privacy-preserving Machine Learning Hybrid Cloud-IoT Architectures Genetic Programming Neural Network Applications Data Processing in Distributed Environments Recent Publication Trends : His work spans federated learning for IoT security ( 2025 ), DNA splicing site prediction ( 2020 ), meningitis classification ( 2019 ), RFID-based traceability systems ( 2015 ), and geological data analysis using neural networks ( 1995-1996 ). Key technologies include Apache Spark , MLlib , and Wavelet Transform . Teaching Activities : He teaches courses like Applied Machine Learning and Principles of Computer Sciences across multiple degree programs including Statistical and Actuarial Sciences and Economics and Management .

• Data Management
• Knowledge Graphs
• Machine Learning
• +۳ مورد دیگر

Zoi Kaoudi is a researcher at the IT University of Copenhagen , specializing in Data Management , Knowledge Graphs , and Machine Learning . Her work focuses on cross-platform data processing, query optimization, and scalable systems for graph analytics. She has published extensively in venues like SIGMOD , VLDB , and ISWC , with recent contributions to Apache Wayang , DORIAN , and Space-Efficient Graph Algorithms . Her research bridges theoretical advancements with practical frameworks for data science pipelines. Collaborations include Volker Markl, Jorge-Arnulfo Quiané-Ruiz, and Ioana Manolescu. She has explored topics such as Parameter Servers , Knowledge Graph Embeddings , and RDF Data Management in the cloud. Her work emphasizes open science and system integration.

Thomas W. Priceمشاهده پروفایل

استادیار

• Computing Education
• Educational Data Mining
• Advanced Learning Technologies
• +۵ مورد دیگر

Thomas W. Price is an Assistant Professor in the Department of Computer Science at North Carolina State University's College of Engineering. He directs the Help through INTelligent Support (HINTS) Lab and is affiliated with NCSU's Center for Educational Informatics. His work bridges computer science, education, and artificial intelligence to create intelligent learning environments. Dr. Price earned his M.S. and Ph.D. in Computer Science from NC State University in 2015 and 2018 respectively, and was named the College of Engineering Doctoral Scholar of the Year in 2018. His research focuses on computing education with an emphasis on automatically generating programming hints and feedback using student data. He has evaluated innovative programming environments including block-based and frame-based systems, and designs intelligent support tools that integrate with these technologies. His work examines how students seek and use help in both classroom and online settings, with particular interest in open-ended programming projects, data-driven feedback systems, and understanding student programming behaviors. His recent publications reveal a strong trend toward integrating AI and educational data mining techniques to support programming education. His work spans from fundamental research on student help-seeking behaviors to practical tools that provide immediate feedback, detect student struggles, and offer personalized support. A significant portion of his recent work addresses emerging challenges like student use of generative AI tools and detecting AI-generated code submissions. College of Engineering Doctoral Scholar of the Year (2018) Exemplary Paper Award from International Conference on Educational Data Mining Exemplary Paper Award from ACM Technical Symposium on Computer Science Education Recognition by STARS Computing Corps for leadership in computing outreach Dr. Price mentors several Ph.D. students including James Skripchuk, John Thomas Bacher, and Keith Tran. He has secured over $4 million in research funding from the National Science Foundation for projects including infrastructure for sustainable innovation in computer science education, data-driven technologies for STEM instruction, and intelligent support for creative programming projects. His research has practical applications in classroom settings and aims to create scalable solutions that don't place additional burden on instructors. As director of the HINTS Lab, Dr. Price leads a team investigating how to re-imagine educational programming environments as adaptive, data-driven systems. The lab focuses on supporting students working in creative, open-ended contexts through automated tools for planning, hint generation, and progress monitoring. Their research emphasizes practical methods that can scale to new classrooms and contexts while providing personalized support tailored to individual student needs.

• Educational Technology
• Human-Computer Interaction
• Cyberbullying and Internet Safety
• +۷ مورد دیگر

Hasan ÖZGÜR is an Associate Professor at Trakya University, Faculty of Education, Department of Computer and Educational Technologies. He currently serves as Department Head since February 2022 and is a Member of the University Rectorate Board of Directors since September 2024. His academic career at Trakya University spans over 18 years, progressing from Education Expert in 2006 to Associate Professor in 2023. His educational background includes a PhD in Engineering Education from Trakya University (2011), a Master's Degree in Educational Sciences from Marmara University (2005), and a Bachelor's Degree from Marmara University Atatürk Faculty of Education (2002). Dr. ÖZGÜR's research focuses on educational technology, human-computer interaction, and digital media effects on learning. His work examines cyberbullying, internet safety, gamification in education, technology integration in teaching, and internet parenting styles. He investigates how digital technologies impact student learning, teacher effectiveness, and adolescent development in the digital age. His research often involves scale development and validation for Turkish educational contexts. His publication record shows consistent research output since 2009, with increasing focus on practical applications of technology in Turkish education. Recent work emphasizes gamification trends, social media integration in learning, and psychological impacts of digital technology on students and teachers. His research bridges theoretical frameworks with practical educational applications, addressing both K-12 and higher education contexts. Dr. ÖZGÜR has contributed significantly to teacher training programs, focusing on developing digital competencies for educators. His administrative roles demonstrate leadership in shaping educational technology policy and implementation at the institutional level. He has collaborated extensively with colleagues including F. Akgün, C. Çuhadar, and F. Arıkan on numerous research projects examining technology adoption challenges within the Turkish educational system.

Christophe Hurterمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Data Visualization
• Augmented Reality
• +۹ مورد دیگر

Christophe Hurter is a Researcher at the National School of Civil Aviation , specializing in Artificial Intelligence , Data Visualization , and Human-Computer Interaction . His work bridges Aviation Technology , Neuroscience , and Extended Reality (XR) , focusing on enhancing human performance through AI-driven systems. Affiliation: National School of Civil Aviation (Faculty Member, AI axis) Research Interests include: Explainable AI for aviation systems Neurophysiological monitoring using thermal imaging Eye tracking and cognitive processes in memory retrieval Graph and trajectory visualization for air traffic control Augmented/Virtual Reality interfaces for remote collaboration Event-based vision systems for spiking neural networks Recent article trends highlight his expertise in machine learning for medical diagnostics , XR applications in aviation , and visual analytics for human factors research . His work often addresses real-world challenges in air traffic control, piloting training, and biomedical data interpretation.