جستجوی استاد راهنمای دانشگاهی

Jeff Offutt is a Professor and Chair of the Department of Computer Science at the University at Albany, College of Nanotechnology, Software, & Engineering. Previously, he was a Full Professor with Tenure in Software Engineering at George Mason University since 2005. He received his PhD in Information & Computer Science from the Georgia Institute of Technology in 1988. His research spans software testing, mutation testing, model-based testing, automatic test data generation, web application testing, and software engineering education. He has led significant projects such as the NSF-funded integration of CS into K-5 classrooms and the Google-funded SPARC project for scalable CS1/CS2 instruction. The 15 most recent articles reflect a continued focus on mutation testing cost reduction, model-based testing oracles, educational innovations, and security aspects of web applications. Trends include empirical validation, industrial applicability, and bridging theory with practice in software testing and engineering education. John Toups Presidential Medal for Excellence in Teaching (2020) George Mason University’s Alumni Association Faculty Member of the Year (2020) Outstanding Faculty Award from the State Council of Higher Education for Virginia (2019) Best Paper Award at ICST 2021 10-Year Most Influential Paper Award at MODELS 2020 George Mason University Teaching Excellence Award (2013) ACM Notable Article Award (2013) Jeff Offutt has mentored numerous graduate students including Upsorn Praphamontripong, Nan Li, and Yu-Seung Ma, and has led major grant-funded projects such as the SPARC educational model and NSF initiatives on K-5 CS integration. His textbook Introduction to Software Testing (with Paul Ammann) is widely adopted globally. He led the MS in Software Engineering program at GMU and developed several new courses in software testing, web engineering, and usability. He pioneered innovative teaching methods using web technologies and asynchronous learning models. He also co-founded the IEEE International Conference on Software Testing, Verification and Validation (ICST) and served as Editor-in-Chief of Software Testing, Verification and Reliability from 2007 to 2019.

• Software Testing
• Mutation Testing
• Model-Based Testing
• +۷ مورد دیگر

Dr. Nour Moustafa is an Associate Professor and ARC DECRA Fellow at the School of Systems & Computing (SysCom) , University of New South Wales (UNSW) Canberra , Australia. He leads the Intelligent Security Group and focuses on developing AI/ML-driven cybersecurity frameworks for smart systems. Educated at Helwan University (BSc/MSc in Information Systems) and UNSW (PhD in Cybersecurity). Research Interests include intrusion detection, threat intelligence, privacy preservation, digital forensics, and cyber resilience, with methodologies spanning statistical analysis , machine learning , and deep learning applied to IoT , Edge/Cloud , and Industrial IoT environments. His work emphasizes federated learning for privacy preservation, blockchain for secure AI, and digital twins for network self-healing. Notable contributions include the TON-IoT , Bot-IoT , and UNSW-NB15 datasets for cybersecurity evaluation. Scientific Awards : 2020 Spitfire Memorial Defence Fellowship ACM Distinguished Speaker IEEE Senior Member He has served as guest associate editor for IEEE Transactions journals and held leadership roles in conferences like IEEE TrustCom . His research bridges academia and industry, with over 75 publications in top-tier venues.

• Cyber Security
• Computer System Security
• Networking and Communications
• +۷ مورد دیگر

Björn Ross is a Lecturer in Computational Social Science at the University of Edinburgh's School of Informatics, where he is affiliated with the Institute for Language, Cognition and Computation. He serves as Director of the SMASH research group and is part of the management team for the Centre for Doctoral Training in Natural Language Processing (CDT in NLP). His educational background includes: PhD (2019) from the University of Duisburg-Essen MSc in Computer Science (2016) from the University of Münster Exchange year (2014-2015) at the University of Strasbourg BSc in Information Systems (2013) from the University of Münster Ross's research focuses on computational social science, particularly using natural language processing, social network analysis, and agent-based modeling to study social media phenomena. His work examines misinformation, hate speech, bot activity, and the ethical implications of computational methods. He also investigates how social media can be leveraged for social good, especially in crisis communication contexts. A significant portion of his recent research addresses bias and fairness issues in AI systems, particularly regarding marginalized communities and LGBTQ+ identities. His work spans both technical development of computational methods and critical examination of their societal impacts. Analysis of his recent publications reveals a strong trend toward examining bias in AI systems, particularly regarding marginalized communities. His work spans multiple methodologies including computational analysis of social media data, development of NLP techniques, and critical examination of AI ethics. He frequently collaborates across disciplines, working with researchers in computer science, social sciences, and healthcare domains. His professional recognition includes: Best Paper Award at the Hawaii International Conference on System Sciences (HICSS) in 2018 Associate Editor for Business & Information Systems Engineering Active membership in professional organizations including AIS, ACL, and ACM Ross currently supervises multiple PhD students including Agostina Calabrese, Eddie Ungless, Sandrine Chausson, Wendy Zheng, Seraphina Goldfarb-Tarrant, and Mahmoud Ibrahim. At the University of Edinburgh, he teaches courses such as 'Text Technologies for Data Science' and 'Evidence, Argument and Persuasion in a Digital Age,' reflecting his expertise at the intersection of computational methods and social implications.

• Computational social science
• Social computing
• Information systems
• +۹ مورد دیگر

Robert Gorwa is a Research Fellow at the WZB Berlin Social Science Center, specializing in technology policy, transnational regulation, and international political economy. His work focuses on platform governance, digital policy, and AI governance, with a particular interest in how governments and institutions shape online content moderation and platform ecosystems. He holds a DPhil in Politics and International Relations from the University of Oxford, an MSc in Media and Communication from the Oxford Internet Institute, and a BA from the University of British Columbia. Education: Doctorate (DPhil) in Politics and International Relations, University of Oxford MSc in Media and Communication (Internet Studies), Oxford Internet Institute Bachelor's degree from the University of British Columbia Research Interests: Interdisciplinary studies on platform governance, AI intermediaries, automated content moderation, transnational digital policy, and the intersection of law, technology, and political economy. His 2024 book, The Politics of Platform Regulation , explores how governments influence online content moderation globally. Key Contributions: Founded and coordinates the Platform Governance Research Network (PlatGovNet) Organizes the WZB's Platform Politics and Policy Seminar series Authored influential works on AI governance, platform lobbying, and live-streaming content moderation Awards: Top departmental honors for his doctoral dissertation at the University of Oxford. Grants & Collaborations: Holds fellowships at the Centre for International Governance Innovation (CIGI), Weizenbaum Institute, and has collaborated with institutions like the Center for Democracy and Technology (CDT) and Stanford's Center for Philanthropy and Civil Society. Labs & Teams: Active in the Platform Governance Research Network and affiliated with the WZB's research group on Globalization, Work, and Production.

• Technology Policy
• Transnational Regulation
• International Political Economy
• +۴ مورد دیگر

Véronique Hoste is Senior Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy, where she serves as Department Head of Translation, Interpreting and Communication and Director of the LT3 language technology research team. She also holds the position of Research Director for the Faculty of Arts and Philosophy. Her educational background includes a PhD in Computational Linguistics from the University of Antwerp (2005) focused on optimization in machine learning for coreference resolution. Key research areas encompass machine learning for natural language processing, semantic and discourse modeling, including specialized work in event detection, entity/event coreference resolution, irony detection, and emotion analysis. Hoste's publication trends reveal strong interdisciplinary focus, with recent work bridging NLP with crisis communication, digital humanities, and ethical AI. Her team develops high-quality datasets (e.g., EmoTwiCS for emotion trajectories) and collaborates extensively with commercial partners on projects like SentEMO for aspect-based sentiment analysis. Current research emphasizes multimodal emotion analysis, fuzzy rough set methods for sentiment detection, and cross-document event coreference. Elected member of the Royal Flemish Academy of Belgium for Science and the Arts (KVAB) Francqui Chair appointment by Université Libre de Bruxelles (2023-2024) Co-founded LT3 spin-off AlfaSent (2024) for customer feedback analysis Authored first Dutch-language book on NLP: "Taaltechnologie ontrafeld" She actively supervises multiple PhD students on projects including Common-sense knowledge in irony detection (Common-sense), cross-document event coreference (Encore), and empathy modeling in conversational agents (FlandersAI). Her team secures funding through interdisciplinary collaborations like NewsDNA for news recommendation and METRICS for emotion trajectory analysis. Hoste also engages in public outreach through the "AI at school" initiative and advises on language technology integration in high school curricula. The LT3 laboratory under her leadership maintains strong industry partnerships and develops practical NLP tools including EmotioNL and Automatic Term Extraction systems, while advancing core research through projects like CLARIAH-VL for data curation.

• Computational Linguistics
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Rémi Giraud is an Associate Professor at ENSEIRB-MATMECA (Bordeaux INP) in the Electronic department, conducting research at the IMS laboratory within the Signal and Image Processing group (MOTIVE team). He is also a member of the In2Brain research group. Dr. Giraud received his M.Sc. in telecommunications from ENSEIRB-MATMECA and a Master's in signal and image processing from the University of Bordeaux in 2014, graduating with honors as top of his class. He completed his Ph.D. in computer science at the University of Bordeaux in 2017, followed by a year as Assistant Professor before becoming Associate Professor in 2018. Current position: Associate Professor at ENSEIRB-MATMECA (Bordeaux INP), Electronic department Research affiliation: IMS laboratory, Signal and Image Processing group, MOTIVE team Additional affiliation: In2Brain research group Education: PhD in Computer Science (2017, University of Bordeaux), M.Sc. in Telecommunications and Signal/Image Processing (2014, ENSEIRB-MATMECA and University of Bordeaux) His research focuses on image processing and analysis, deep learning, and computer vision, with particular expertise in (un)supervised image segmentation, colorization, matching techniques, irregular under-representations (superpixels), spatial relations, and medical imaging (3D MRI applications). His work bridges theoretical computer vision with practical medical applications, developing algorithms that enhance image understanding in both general and specialized contexts. Dr. Giraud has developed several significant methodologies including SCALP (Superpixels with Contour Adherence using Linear Path), TASP (Texture-Aware SuperPixel), DSP (Dual Superpixel Descriptors), and NNSC (Nearest Neighbor-based Superpixel Clustering). His publications demonstrate consistent advancement in superpixel segmentation techniques with increasing focus on medical imaging applications, particularly brain MRI analysis. He currently supervises multiple PhD students including Julien Walther (working on Deep Learning Models from Structural Image Representations), Eloi Navet (An AI Assembly for Neurological Disease Prediction), Edern Le Bot (Holistic Brain MRI Segmentation), and Matthieu Vilain (Semi-supervised Deep Learning for image sequences). His research has resulted in numerous publications in top-tier conferences and journals, with a clear trajectory from theoretical algorithm development to practical implementation in medical contexts.

• Image processing
• Deep learning
• Computer vision
• +۳ مورد دیگر

Abdullah Mueen is a Professor and Associate Chair in the Department of Computer Science at the University of New Mexico (UNM), where he has been since 2013. Previously, he worked as a Scientist in the Cloud and Information Sciences Lab at Microsoft Corporation. Research Interests : His work focuses on Temporal Data Mining , with emphasis on efficiency , interactivity , and interpretability . Key areas include Blockchain Data Mining (e.g., BitLink for Bitcoin cluster analysis), Seismic Data Mining (e.g., PAW for aftershock detection), and Social Media Mining (e.g., DeBot for Twitter bot detection). Article Trends : His recent publications span four domains: Seismology : Algorithms for earthquake data analysis (e.g., focal depth inference, aftershock classification). Blockchain : Temporal linkage of Bitcoin addresses (BitLink) and cryptocurrency fraud detection. Traffic Safety : Multi-LiDAR data fusion for real-time road safety monitoring. Time Series Methods : Innovations like MASS similarity search and DAMP anomaly detection for massive datasets. Scientific Awards : ACM SIGKDD Test-of-Time Award (2022) UNM Provost Research Leader Award UNM School of Engineering Junior Faculty Research Excellence Award KDD 2012 Doctoral Dissertation Contest Runner-Up KDD 2012 Best Paper Award Advising and Grants : He has mentored 11 PhD students now employed at institutions like Microsoft, Meta, and Lawrence Livermore National Lab. His research is funded by NSF , NIH , DARPA , AFRL , NEC , Exxon , Microsoft , and LANL .

• Temporal Data Mining
• Blockchain Data Mining
• Social Media Mining
• +۵ مورد دیگر

Maurizio MUZZUPAPPA is a Full Professor at the Department of Mechanical, Energy and Management Engineering (University of Calabria) since 2018. His roles include Rector's Delegate for Technology Transfer, Academic Delegate for Education at DIMEG, and Head of the Physical Prototyping Laboratory at the MaTeRiA Center (UNICAL-CNISM collaboration). He supervises the Unical Racing Team in Formula SAE competitions and co-founded three university spin-offs: 3DResearch, Tech4Sea, and Q-BOT. As Scientific Director of projects like TECH4YOU (climate change adaptation technologies) and GROWN IN THE BLUE (Mediterranean reef conservation), he integrates research in industrial design, augmented reality, and underwater cultural heritage. He has authored over 200 publications (h-index 27) and holds 10 patents. His teaching includes Tools and Methods for Industrial Design and Formula SAE LAB . His research focuses on: Industrial design methodologies with parametric and sustainable approaches 3D prototyping and additive manufacturing User-Centered Design for product ergonomics Virtual/Augmented Reality applications in engineering and cultural heritage Underwater robotics and artifact restoration Recent publications highlight trends in AR for industrial maintenance, generative design tools, and mechatronic solutions for underwater heritage. He has supervised over 300 theses and 10 Ph.D. students while leading technology transfer initiatives.

• Industrial Engineering Design
• Augmented Reality (AR) Applications
• Product Development Methodologies
• +۵ مورد دیگر

Professor Marius Portmann is the UQ-Cisco Chair of Network Security at the School of Electrical Engineering and Computer Science (EECS), University of Queensland. His expertise spans Cybersecurity, IoT, and Applied AI. He holds a PhD from ETH Zurich (2003) and has led research in Software Defined Networking (SDN), blockchain, and energy-harvesting IoT systems. Education: PhD in Electrical Engineering from Swiss Federal Institute of Technology (ETH Zurich), 2003. Research focuses on securing IoT networks, AI-driven intrusion detection, and sustainable sensor systems. He has pioneered self-powered IoT systems using energy harvesters and developed frameworks like FlowTransformer for network analysis. His work bridges theoretical advancements with practical applications in smart tourism, energy efficiency, and edge computing. Recent publications highlight innovations in DDoS detection (P4-Secure), sensor-based environmental monitoring (EcoShower), and graph-based anomaly detection (XG-BoT). His datasets (e.g., NF-ToN-IoT-v3) are widely used in ML-based cybersecurity research. Collaborations include industry partners like Cisco and institutions like RMIT. Grants and leadership roles in interdisciplinary projects underscore his impact. He advises on IoT security standards and contributes to open-source tools for network research. Current projects explore edge-AI integration and sustainable sensor networks.

• Cybersecurity
• Computer Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Blake Miller is an Assistant Professor of Computational Social Science in the Department of Methodology at the London School of Economics (LSE), affiliated with the Data Science Institute. Their research focuses on computational methods applied to political communication in authoritarian regimes, particularly China, and the intersection of social media with political violence and identity politics. They hold a PhD from the University of Michigan (2018) and conducted postdoctoral research at Dartmouth College. Key substantive areas include: China's surveillance-driven security state and information control mechanisms Political mobilization through moral outrage and outgroup targeting Technological adaptations in authoritarian governance Methodological expertise spans machine learning, text analysis, and fairness in AI applications. Their book project Platforms and Power examines how authoritarian states delegate censorship to private platforms. Teaching focuses on quantitative text analysis and machine learning in political contexts. Research outputs include influential work on: Censorship patterns during China's zero-COVID protests Moral-emotional triggers for violence support Evaluation of active learning algorithms for text labeling Blake's work has been featured in The Washington Post , China File , and the CSIS Pekingology Podcast. They maintain an active presence in interdisciplinary research communities.

• Computational Social Science
• Text Analysis
• Social Media Politics
• +۷ مورد دیگر

Professor Patrik Wikstrom is a computational communication scholar at Queensland University of Technology (QUT), leading the School of Communication. He serves as Chief Investigator in QUT's Digital Media Research Centre (DMRC) and Associate Investigator in the Australian Research Council's ADM+S Centre. His expertise spans digital media's impact on music and meme cultures, algorithmic systems, and cultural economics. Education: PhD in Media and Communication Studies (Karlstad University), MScEng (Chalmers University). Former roles include Director of DMRC, Associate Dean (Research) at QUT's Creative Industries Faculty, and academic leadership at Northeastern University, Jönköping International Business School, and Karlstad University. Research focuses on digital technologies' societal impacts, including recommender systems, platform governance, and music industry dynamics. Key publications include TikTok: Creativity and Culture in Short Video and The Music Industry: Music in the Cloud . Active in grants like the Australian Cultural and Creative Activity Analysis project (LP160101724). Supervised over 10 doctoral and master's students on topics ranging from platform governance to decolonizing copyright. Current projects explore algorithmic culture, AI ethics, and fair payment models for artists. Labs/Teams: DMRC and ADM+S collaborate on automated decision-making's societal implications. Advocates for responsible AI and interdisciplinary computational methods in social sciences.

• Computational Communication
• Music Industries
• Algorithmic Culture
• +۳ مورد دیگر

Tom Zick serves as Director of Responsible AI at Charles Schwab and holds an academic affiliation as a Research Fellow at Harvard University's Berkman Klein Center for Internet & Society. Her work bridges technical AI development and legal frameworks, focusing on governance mechanisms for emerging technologies. She has advised organizations from startups to Fortune 500 companies while collaborating with frontier AI labs and public institutions like the City of Boston on AI deployment and data governance initiatives. Her educational foundation includes a JD from Harvard Law School and a PhD in Astrophysics from UC Berkeley, providing interdisciplinary expertise critical to her research. This dual background enables rigorous analysis of complex technology-policy intersections. Zick's research centers on creating accountable AI systems through technical oversight frameworks and regulatory compliance strategies. She investigates generative AI's societal impacts, reinforcement learning risks, and privacy-preserving identity solutions like personhood credentials. Her work emphasizes red teaming, model alignment, and global regulatory harmonization, addressing both immediate implementation challenges and long-term existential risks through law-technology integration. Analysis of her publication trajectory reveals escalating focus on governance scalability as AI capabilities advance. Early work examined foundational risks in reinforcement learning, while recent publications address generative AI's disruption of education systems and the urgent need for cross-jurisdictional regulatory frameworks. Her taxonomy development for AI regulation demonstrates systematic approaches to navigating fragmented global policy landscapes. As an advisor, Zick has guided corporate and municipal entities through AI implementation challenges, notably helping Boston operationalize data governance frameworks. Her Berkman Klein fellowship involved direct collaboration with major AI labs on alignment research and red teaming exercises. She contributes to industry-wide initiatives including Twitter's decentralized social media project (bluesky), focusing on protocol-level solutions for content integrity. Zick's collaborative ecosystem spans frontier AI companies, academic researchers, and public sector innovators. Her current work with the City of Boston demonstrates practical governance implementation, while ongoing personhood credentials research addresses AI-generated content verification challenges. These partnerships reflect her commitment to translating theoretical frameworks into operational systems across multiple sectors.

• AI Governance
• Privacy
• Generative AI
• +۴ مورد دیگر

Dr. Panagiotis Andriotis is a Lecturer in Computer Science at the School of Computer Science, University of Birmingham, within the College of Engineering and Physical Sciences. He is also a GIAC Certified Forensic Examiner (GCFE, GASF) and a Senior Fellow of the Higher Education Academy (SFHEA). His interdisciplinary research spans Cyber Security, Human Factors, and Mobile and Ubiquitous Computing. He teaches courses in Computer Science, Cyber Security, and Digital Forensics. His educational background includes a PhD in Computer Science from the University of Bristol (2016), an MSc with Distinction in Computer Science from the same institution (2011), and a BSc in Mathematics from the National and Kapodistrian University of Athens (2004). Dr. Andriotis’s research interests focus on user-centered security, particularly in mobile environments. He investigates how users interact with Android’s permission systems, develops novel authentication mechanisms like Bu-Dash, and explores adversarial machine learning in cybersecurity. His work bridges technical and human aspects, aiming to improve both system robustness and user experience. His recent publications reflect a strong trend in adversarial machine learning, mobile malware detection, usable privacy, and the societal implications of AI in education. He has contributed to high-impact journals such as IEEE Transactions on Cybernetics, ACM Transactions on Privacy and Security, and Elsevier’s Journal of Information Security and Applications. Best Paper Award at HCI International 2020 Impact Award, UWE Bristol Student Union GIAC Certified Forensic Examiner (GCFE) GIAC Advanced Smartphone Forensics (GASF) SANS Lethal Forensicator Coin Dr. Andriotis has advised PhD students, including Andrew McCarthy, and has been involved in funded research projects such as those related to fuzzing, software security, and critical infrastructure protection in collaboration with Airbus. He has served as an External Examiner at Cardiff Metropolitan University and is currently on the editorial boards of Digital Threats: Research and Practice (ACM) and the Journal of Responsible Technology (Elsevier). He has held visiting roles at the National Institute of Informatics in Tokyo, including as a JSPS Fellow and Toshiba Fellow. He leads research in digital forensics and security, with a lab focus on mobile ecosystems, behavioral modeling, and AI-driven threat detection. His team explores both technical and human dimensions of cybersecurity, contributing to tools and frameworks that enhance mobile security and user awareness.

• Cyber Security
• Human Factors in Security
• Mobile and Ubiquitous Computing
• +۷ مورد دیگر

Susan Fussell is a Professor at Cornell University in both the Department of Communication and Department of Information Science. She received her Ph.D. in psychology from Columbia University and directs graduate studies in Communication. Key research areas: Computer-Mediated Communication, Intercultural Communication, Human-Computer Interaction, Multilingual Collaboration, and Collaborative Intelligence Analysis. Teaching focus: Theories of communication, research methods in social computing, and behavioral foundations of technology. Her publications from 2015-2025 reveal trends in cross-cultural communication technology , AI-mediated interaction , and collaborative problem-solving . Scientific awards include NSF grants #1025425, #1318899, #1314778 Google Faculty Gift She advises students like Nanyi Bi, Ge Gao, and Bin Xu. Notable collaborations include work with Claire Cardie, Sara Kiesler, and Dan Cosley. Projects include Tools for multilingual collaboration Energy conservation through social computing Telepresence robotics and human-robot interaction Contact: 226 Gates Hall, Ithaca, NY 14853 | sfussell@cornell.edu

• Computer-Mediated Communication
• Intercultural Communication
• Human-Computer Interaction
• +۵ مورد دیگر

Balazs Vedres is a **Professor** at the **Central European University (CEU)**, with a joint appointment in the **Department of Network and Data Science**. His research integrates network science, data science, and social theory to explore creativity, innovation, and historical processes in collaborative networks. He holds a **PhD in Sociology from Columbia University** and an **MA in Economics from Corvinus University**. **Research Interests**: Focuses on structural dynamics in creative fields (e.g., jazz, video games, open-source software), gender inequality in collaborative platforms, historical network evolution, and the impact of social bots on human collaboration. He analyzes how network configurations like *structural folds* and *forbidden triads* drive innovation and creativity. **Awards**: Elected **Member of the European Academy of Sociology (2017)**, recognizing his contributions to sociological research. His work bridges computational methods with sociological theory, as seen in his publications in *American Journal of Sociology* and interdisciplinary journals. **Projects**: Leads initiatives like *Gendered Creative Teams: From Marginality to Success* and *Ceunet/Indra Mapping European Network Science*. His research often involves empirical studies of transnational activism, entrepreneurial networks, and digital platforms. **Labs/Teams**: Active in CEU’s **Data and Network Dynamics Studies (DNDS)** group, fostering interdisciplinary collaboration in computational social science. His work emphasizes the interplay between global economic integration and local developmental agency.

• Network Science
• Data Science
• Sociology
• +۷ مورد دیگر