جست‌وجوی استاد و پژوهشگر

Jonathon Hutchinsonمشاهده پروفایل

دانشیار

• Social Media Studies
• Public Service Media
• Cultural Intermediation
• +۴ مورد دیگر

Introduction Jonathon Hutchinson is an Associate Professor and Chair of the Media and Communications Discipline at the University of Sydney. He holds roles as Editor-in-Chief of the Policy & Internet journal and Chief Investigator on major projects like the International Digital Policy Observatory (ARC LIEF) and the eSafety Commission's Emerging Online Safety Issues initiative. His work bridges digital media studies, policy analysis, and cultural theory. Education BComm (Hons), RMIT University PhD, ARC Center of Excellence for Creative Industries and Innovation, QUT Research Interests Hutchinson focuses on digital intermediation processes in cultural production, algorithmic governance, and public service media adaptation. Key areas include: Algorithmic influence on news diversity Social media policy and youth safety Platform politics and regulatory frameworks Recent Article Trends His 2020–2025 work emphasizes global digital policy challenges, generative AI ethics, and Vietnamese media dynamics. Recent projects highlight cross-national comparisons (e.g., China/South Korea news ecosystems) and participatory co-design approaches to online safety education. Awards & Grants 2023 ARC LIEF Grant 2021 eSafety Online Safety Grant Multiple industry partnerships (e.g., eSafety Commissioner, Hans-Bredow-Institut) Advising & Grants Supervised over 15+ graduate students (PhD/Master's/Honours) in media studies and digital culture. Active in interdisciplinary grants addressing cybersecurity, AI governance, and platform regulation. Labs & Networks Member of the Sydney Centre for Healthy Societies, Sydney Southeast Asia Centre, and Charles Perkins Centre. Leads the International Digital Policy Observatory project tracking global regulatory trends.

Felix Gomez Marmolمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Felix Gomez Marmol is an Associate Professor at the University of Murcia's Faculty of Informatics, Department of Information and Communication Engineering. His research focuses on cybersecurity, artificial intelligence, network security, and IoT security. He holds a PhD in Computer Science from the University of Murcia (2010), supervised by Dr. Gregorio Martínez Pérez. Key research interests include adaptive intrusion detection systems, dark web analysis, and AI-driven cybersecurity frameworks. He leads the Intelligent Systems and Telematics research group and previously contributed to the Sistemas Inteligentes group. His work emphasizes practical applications such as the SCORPION Cyber Range platform for cybersecurity training and gamification. Recent projects involve detecting hate networks on social media, optimizing malware defense using transfer learning, and developing SIEM systems for IoT environments. His contributions span technical papers on cybersecurity education, ethical hacking fundamentals, and blockchain-based security solutions. Prof. Gomez Marmol has collaborated on initiatives like the COBRA framework for simulating advanced persistent threats (APTs) and the COnVIDa dashboard for pandemic-related data analysis. His research bridges theoretical advancements with real-world cybersecurity challenges.

• Cybersecurity
• Internet of Things (IoT)
• Post-Quantum Cryptography
• +۵ مورد دیگر

Florina Almenares Mendoza is an Associate Professor at the Telematics Engineering Department of Carlos III University of Madrid , where she also serves as the Director of the University Master's Degree in Cybersecurity. Her research focuses on addressing security challenges in emerging technologies such as IoT, post-quantum cryptography, and privacy-preserving systems. Email: florina.almenares@uc3m.es Contact: 916246234 Location: 4.0.F06 - Quevedo Towers (Leganés) Research Interests Florina's work spans cybersecurity , Internet of Things (IoT) , and post-quantum cryptography , with a focus on scalable authentication, quantum-resistant protocols, and privacy. She explores machine learning applications for security, federated identity management , and smart grid security frameworks. Recent Publications Her recent research includes papers on DNSSEC soft delegation, hybrid quantum security for TLS/IPsec, PUF-based authentication in IoT, and blockchain-enabled auditability. These studies emphasize IoT security , quantum-resistant algorithms , and privacy-enhancing technologies .

Jean-François Godboutمشاهده پروفایل

استاد

• Data Science
• AI Safety
• Generative AI
• +۶ مورد دیگر

Jean-François Godbout is a Professor in the Department of Political Science at the Université de Montréal and an Associate Academic Member of Mila - the Quebec AI Institute. He directs the undergraduate program in Big Data Analytics in Social Sciences and Humanities at UdeM and conducts interdisciplinary research through the Complex Data Lab. Affiliated with IVADO (AI Consortium) Member of CÉRIUM (International Research Centre) and CECD (Democratic Citizenship Centre) His research focuses on: Data Science applications in political institutions AI Safety and generative AI's impact on political attitudes Misinformation Mitigation through large language models Comparative Political Development in Canadian and Lower Canada contexts Legislative Institutions and voting records analysis Political Polarization in online societies Recent publications analyze social media disinformation, AI persuasion on harmful topics, and education-focused text simplification. His articles frequently combine graph mining , machine learning , and political science methodologies. Scientific collaborations include: Mila researchers (Andreea Musulan, Maximilian Puelma Touzel) IVADO data science initiatives McGill University interdisciplinary projects He supervises students in: Political science (Julien Robin, Matthew Taylor) Artificial Intelligence (Kellin Pelrine, Camille Thibault) Computational social science applications

Jason Bennett Thatcherمشاهده پروفایل

استاد

• Information Systems
• Cybersecurity
• Strategic Alignment
• +۶ مورد دیگر

Dr. Jason Bennett Thatcher is a Professor at Temple University in the Department of Management Information Systems at the Fox School of Business. He holds additional faculty appointments at the Technical University of Munich, Information Technology University-Copenhagen, and Hong Kong Polytechnic University. His research bridges human behavior and information technology, focusing on cybersecurity, strategic alignment, and digital innovation. 20-year track record in top FT50 journals Top 35 active IS researcher by productivity Senior Editor roles at MIS Quarterly , Information Systems Research , and Journal of the AIS Research spans three pathways: strategic IT decisions (firm performance, governance), IT workforce management (job satisfaction, turnover), and post-adoption IT innovation (technostress, IT identity). 2022 publications emphasize digital commerce, social media ethics, and technostress mitigation. Awards include: Clemson's 2008 Undergraduate Teaching Award KPMG Foundation Circle of Compadres Top Associate Editor recognition by Information Systems Research Multiple productivity rankings Teaching spans undergraduate to Ph.D. levels with global mentorship experience. Editorial leadership roles include Senior Editor positions and former editorial board memberships. Productivity metrics highlight 12,000+ Google Scholar citations and consistent publication in FT50 journals since 2002.

Jung-Eun Kimمشاهده پروفایل

استادیار

• Trustworthy AI
• Interpretable AI
• Efficient Deep Learning
• +۷ مورد دیگر

Jung-Eun Kim is an Assistant Professor in the Department of Computer Science at North Carolina State University, where she conducts research at the intersection of artificial intelligence, machine learning, and cyber-physical systems. Her work focuses on creating trustworthy, interpretable, and efficient AI systems, particularly for safety-critical applications. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign (2017) M.S. in Computer Science and Engineering, Seoul National University (2009) B.S. in Computer Science and Engineering, Seoul National University (2007) Dr. Kim's research primarily investigates how to make AI systems more trustworthy, interpretable, and efficient, with particular emphasis on understanding failure modes, safety risks, vulnerabilities, and biases in deep learning models. Her work bridges theoretical understanding with practical applications in safety-critical systems. She explores how efficiency considerations interact with these issues, seeking to fundamentally anatomize neural networks to understand what causes failure modes and how to mitigate them. Her approach has been described as 'like a heart surgeon, we open the heart of a neural network architecture, look into it, interpret it, and cure it.' Her recent publications demonstrate a strong focus on safety alignment in large language models, mitigation of spurious correlations, privacy preservation against membership inference attacks, and sustainable AI development. Her work spans theoretical foundations of trustworthy AI while addressing practical challenges in model deployment, particularly for resource-constrained environments. She has made significant contributions to understanding how model compression techniques like pruning and quantization can inadvertently amplify biases and vulnerabilities. Scientific Awards: ICLR Spotlight, 2025 IBM Faculty award, 2023 CRA Early & Mid Career Mentoring Workshop, 2023 Cloud GPU provided by Lambda, worth $17,280, for course, Spring 2023 NeurIPS Spotlight and nomination for Best Paper Award, 2022 CRA Career Mentoring Workshop, 2022 GPU Grant by NVIDIA Corporation, 2018 The MIT EECS Rising Stars, 2015 The Richard T. Cheng Endowed Fellowship, 2015-2016 Dr. Kim actively mentors PhD students, currently advising Xingli Fang, Varun Mulchandani, Jianwei Li, Rishi Singhal, and Minseon Kim. She has secured significant research funding, including an NSF SaTC (Secure and Trustworthy Cyberspace) grant as Co-PI for 'Partition-Oblivious Real-Time Hierarchical Scheduling' ($281,629.00, 2022-2024). Her research has also been supported by an NVIDIA GPU Grant and cloud resources from Lambda. She serves on program committees for top AI conferences including ICLR, ICML, NeurIPS, AAAI, and IJCAI, and has held roles such as Publicity Chair for IJCAI 2024. Her research group focuses on developing methods to make AI systems more trustworthy, interpretable, and efficient, with particular attention to safety-critical applications. The group investigates how to identify and mitigate failure modes in neural networks while maintaining efficiency, exploring the fundamental relationship between model architecture, safety risks, and computational constraints.

Luis Sentisمشاهده پروفایل

استاد

• Robotics
• Humanoid Robotics
• Autonomous Systems
• +۷ مورد دیگر

Luis Sentis is a Professor in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin and holds the Frank and Kay Reese Endowed Professorship in Engineering . He leads the Human Centered Robotics Laboratory, focusing on control systems, human-robot interaction, and exoskeleton robotics. His affiliations include UT Austin's Good Systems initiative and Apptronik Systems as an innovation advisor. Ph.D. , Electrical Engineering, Stanford University B.S. , Telecommunications and Electronics Engineering, Polytechnic University of Catalonia His research spans humanoid robotics , agile manipulation , autonomous systems , and human-robot teaming . Recent work emphasizes FAIR datasets , EEG monitoring , and collision detection for legged robots, with applications in industrial automation and ethical AI. Scientific awards include the NASA Elite Team Award and La Caixa Foundation Fellowship . Funding sources include DARPA , NSF , NASA , and ONR .

• Software Testing
• Regression Testing
• Flaky Tests
• +۳ مورد دیگر

Darko Marinov is a Professor at the Siebel School of Computing and Data Science and a member of the Information Trust Institute at the University of Illinois at Urbana-Champaign. His research focuses on software testing methodologies, particularly regression testing, flaky tests, and software reliability engineering. He has contributed to frameworks like Ekstazi for regression test selection and DeFlaker for identifying flaky tests. Marinov holds an NSF CAREER Award (2008) for his work in this domain. His research interests span testing techniques for modern software systems, including configuration testing, test prioritization, and fault localization. He has pioneered studies on the characteristics of flaky tests in large-scale projects and developed tools to improve software quality assurance processes. Marinov collaborates across academic and industrial settings, addressing challenges in continuous integration, reproducibility of computational experiments, and hardware-software co-design for resilience. His work bridges theory and practice, with applications in cloud computing, AI workloads, and cybersecurity. Awards: NSF CAREER Award (2008) Key Contributions: Ekstazi, DeFlaker, FastFlip, and Ctest4J frameworks Labs/Teams: Active member of the Information Trust Institute and leads software testing research groups at UIUC

Amritanshu Pandeyمشاهده پروفایل

استادیار

• Grid Simulation and Optimization
• Grid Cybersecurity
• Modeling of Future Energy Systems
• +۳ مورد دیگر

Amritanshu Pandey is an Assistant Professor in Electrical Engineering at the University of Vermont, with a part-time adjunct appointment in Electrical and Computer Engineering at Carnegie Mellon University. His research focuses on enhancing the efficiency, reliability, and security of electric grids through methods in circuit theory, optimization, and machine learning. He pioneered the SUGAR simulation engine for power systems and collaborates globally on grid challenges. Research Interests: Pandey's work spans renewable integration, grid cybersecurity, digital twins, and decarbonization. Key projects include developing algorithms for large-scale grid optimization, anomaly detection, electric vehicle infrastructure modeling, and cyber-resilient energy systems. His research addresses real-world challenges in rapidly evolving grids across Asia and Africa. Awards: Best Paper Award, IEEE PES General Meeting (2017, 2021) Best-of-the-Best Paper Award, IEEE PES General Meeting (2021) Best Student Paper Runner-up, ECML-PKDD (2018) Students & Labs: He advises 7 PhD students and has graduated 11 advisees (PhD/MS/BS). His lab focuses on power systems innovation, including the SUGAR simulation framework and projects on grid cybersecurity and sustainable electrification.

Matthias Stürmerمشاهده پروفایل

استاد

• Digital Sustainability
• Artificial Intelligence
• Natural Language Processing (NLP)
• +۴ مورد دیگر

Matthias Stürmer is a Professor at Bern University of Applied Sciences (BFH) and Head of the Institute for Public Sector Transformation (90%) while also serving as Head of the Digital Sustainability Research Center at the University of Bern's Institute of Computer Science (10%). His roles include teaching, research, and consulting on digitalization topics such as digital sustainability, open source software, AI, NLP, open data, and public procurement. He earned a Dr. sc. ETH Zurich in 2009 and habilitation in 2020. His career includes senior roles at EY and Liip AG, and he holds leadership positions in organizations like CH Open and the Parliamentary Group for Digital Sustainability. **Education**: PhD (ETH Zurich, 2009), Licentiate in Business Administration (University of Bern, 2005). Studies included computer science and business administration, with an Erasmus semester at the University of Oviedo (Spain). **Research Interests**: Focus on digital sustainability, digital sovereignty, AI ethics, open source governance, smart cities, and public procurement strategies. His work bridges technical innovation with public sector challenges, emphasizing long-term societal benefits over short-term vendor dependencies. **Publications**: Over 38 peer-reviewed articles and book chapters, including foundational work on digital sustainability frameworks, open government data impact analysis, and collaborative innovation models. Recent focus areas include data colonialism risks and sustainable environmental data management. **Awards**: While no explicit awards listed, his leadership roles and prolific publications highlight recognition in academic and policy circles. **Advising & Grants**: Advises on public sector digitalization policies, contributes to Swiss federal IT strategies, and leads research projects funded by organizations like the University of Bern. Active in shaping Open Source adoption policies for public institutions. **Labs/Teams**: Directs the Research Center for Digital Sustainability at the University of Bern, collaborating with industry and government partners on projects like the Open Data Impact Framework and Open Finance initiatives.

Sagar Samtaniمشاهده پروفایل

دانشیار

• Artificial Intelligence for Cybersecurity
• Cyber Threat Intelligence
• Deep Learning
• +۵ مورد دیگر

Sagar Samtani is an Associate Professor and Weimer Faculty Fellow at the Kelley School of Business , Indiana University. He serves as Director of the Kelley’s Data Science and Artificial Intelligence Lab (DSAIL) . His research focuses on Artificial Intelligence for Cybersecurity , including cyber threat intelligence, deep learning, and dark web analytics. He holds a PhD from the University of Arizona (2018), and has received prestigious awards such as the Indiana University Outstanding Junior Faculty Award (2023) and IEEE Big Data Security Junior Research Award (2023). Education : PhD in Information Systems, University of Arizona, 2018 MSMIS, University of Arizona, 2014 BSBA, University of Arizona, 2013 Research Interests : Samtani’s work addresses cybersecurity challenges through AI, including proactive threat detection, vulnerability assessment, and healthcare analytics. He emphasizes explainable AI (XAI) for transparency in cybersecurity systems. Grants & Awards : NSF Grant: CyberCorps SFS Program ($2.3M, 2020–2025) NSF Grant: AI4Cyber Research Education ($300K, 2020–2022) Multiple teaching awards, including the Trustees Teaching Award (2023) and recognition as one of Top 50 Undergraduate Professors (2022) Labs & Teams : Leads the DSAIL lab, focusing on AI-driven solutions for business and cybersecurity. Collaborates with NSF-funded initiatives on cyber AI education and threat intelligence.

Wayne G. Luttersمشاهده پروفایل

استاد

• Computer-Supported Cooperative Work (CSCW)
• Social Informatics
• Social Computing
• +۹ مورد دیگر

Wayne G. Lutters is a Professor and Associate Dean for Faculty in the College of Information Studies (INFO) at the University of Maryland. He holds office in Patuxent 1109C and can be reached at lutters@umd.edu. His research focuses on sociotechnical systems, computer-supported cooperative work (CSCW), and social informatics, with emphasis on IT-mediated infrastructural work and cybersecurity advocacy. Current projects include studies on scientific cyberinfrastructure, usable privacy and security, and moderation in social media. Dr. Lutters advises the Dean’s Student Advisory Council and explores topics like data privacy, sociotechnical cybersecurity, and the future of work. His recent work addresses challenges in security awareness programs, code set redundancy in healthcare, and collaborative systems design. He is actively involved in developing tools like the Value Set Hub to improve healthcare data curation practices. His research consistently bridges theory and practice, emphasizing ethical technology design and interdisciplinary collaboration. Notable contributions include frameworks for cybersecurity advocacy roles and methodologies for synthesizing scholarly knowledge. While currently not accepting new PhD students, he remains a key figure in shaping academic and infrastructural innovation at UMD.

Zhiyu Quanمشاهده پروفایل

استادیار

• Actuarial Science
• Data Science
• Computational Statistics
• +۳ مورد دیگر

Zhiyu (Frank) Quan is an Assistant Professor at the University of Illinois at Urbana-Champaign (UIUC), holding positions in the Department of Mathematics, Department of Statistics, and National Center for Supercomputing Applications (NCSA). He is also an affiliate faculty member at Discovery Partners Institute as InsurTech Lead and serves as an ORMI Faculty Fellow in Finance. His research focuses on data science applications in actuarial science, including tree-based models, natural language processing, and deep learning for insurance risk modeling, predictive analytics, and InsurTech innovation. Education: Ph.D. in Actuarial Science (University of Connecticut, 2019), MS in Applied Statistics (Michigan State University, 2014), and BS in Mathematics and Applied Mathematics (Xiamen University, 2012). Research interests include computational statistics, insurance analytics, and leveraging machine learning for actuarial challenges such as claim prediction, rate-making, and cyber risk modeling. He leads the Illinois Risk Lab, bridging academic research with industry needs, and has pioneered hybrid tree-based models to address imbalanced data in insurance. Notable achievements include the Arnold O. Beckman Research Award and Society of Actuaries Research Institute recognition. He advises two doctoral students and teaches advanced predictive analytics courses, emphasizing practical applications in actuarial science and data ethics. Key collaborations involve InsurTech companies and NCSA, focusing on NLP-driven academic paper repositories (CyLit) and federated learning for privacy-preserving insurance data sharing. His work addresses real-world challenges in cyber insurance and automated machine learning systems.

Daniel Angusمشاهده پروفایل

استاد

• Artificial Intelligence
• Social Media Analysis
• Computational Social Science
• +۳ مورد دیگر

Professor Daniel Angus is a faculty member at Queensland University of Technology (QUT), holding the position of Professor of Digital Communication in the School of Communication and serving as Director of QUT's Digital Media Research Centre (DMRC). His research focuses on computational methods applied to communication and media studies, with a particular emphasis on AI, automation, misinformation, and digital societal impacts. He holds a PhD in computer science from Swinburne University of Technology and has extensive experience in interdisciplinary research across computer science, design, communication, linguistics, and journalism. Affiliations: ARC Centre of Excellence for Automated Decision Making & Society, ARC Centre of Excellence for the Dynamics of Language. Research Projects: Leads projects like 'Using Machine Vision to Explore Instagram’s Everyday Promotional Cultures' and 'Evaluating the Challenge of ‘Fake News’ and Other Malinformation'. Research Interests: Daniel’s work bridges technology and society, exploring AI ethics, algorithmic transparency, social media governance, and computational methodologies for analyzing communication patterns. He develops tools like Discursis and PauseCode to study discourse and conversational dynamics in healthcare, aged care, and media contexts. Grants & Awards: Principal Investigator on multiple ARC grants and collaborates with industry stakeholders to address challenges like unhealthy food advertising and platform accountability. His research has informed policy submissions to parliamentary committees on social media regulation and AI adoption. Supervision: Current PhD students focus on topics like algorithmic transparency, computational methods for meme analysis, and AI in publishing. Labs/Teams: Directs the Digital Media Research Centre, fostering interdisciplinary projects on digital culture and platform studies.

• Food Safety
• Cumulative Risk Assessment
• Pesticide Residues
• +۳ مورد دیگر

Johannes Kruisselbrink is a Researcher at Biometris , a department within Wageningen University & Research , specializing in food safety and cumulative risk assessment. His work focuses on pesticide residues, dietary exposure, and computational modeling for regulatory compliance. Key Collaborations: European Food Safety Authority, EFSA Projects: Active in pesticide exposure analysis (2024-2028), cumulative risk assessment tools (2019-2023), and regulatory frameworks (2018-2019). His research integrates data modeling and statistical software to enhance risk assessment methodologies. Recent projects emphasize interoperability and accessibility of platforms like MCRA and PARC. Scientific Contributions: Developed AMIGA Power Analysis tool for equivalence testing Authored reports on pesticide risk surveillance in fruits and vegetables Advancing EFSA standards for acute reference dose calculations