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Diogo BarradasView profile

Assistant Professor

• Network Traffic Analysis
• Internet Censorship Circumvention
• Anonymous Communication
• +5 more

Diogo Barradas is an Assistant Professor in the Department of Computer Science at the University of Waterloo. His research focuses on network security, internet censorship circumvention, and anonymous communication systems. He holds a Ph.D., M.Sc., and B.Sc. from Instituto Superior Técnico, Universidade de Lisboa, Portugal. His work addresses challenges such as website fingerprinting defenses, programmable network security, and steganographic techniques for censorship resistance. Education: Ph.D., Instituto Superior Técnico, Universidade de Lisboa (2021) M.Sc., Instituto Superior Técnico, Universidade de Lisboa (2016) B.Sc., Instituto Superior Técnico, Universidade de Lisboa (2014) Research interests include: Network traffic analysis and obfuscation Security of programmable network infrastructures Digital forensics and information hiding Covert channels in multimedia protocols His recent publications explore cutting-edge topics like time series analysis for website fingerprinting detection, distributed traffic correlation on programmable networks, and satellite-based censorship circumvention. These contributions highlight advancements in both theoretical frameworks and practical tools for privacy-preserving communication.

Oya BeyanView profile

Professor

• Biomedical Informatics
• Semantic Web Technologies
• Clinical Decision Support
• +5 more

Prof. Dr. Oya Beyan is a Professor at the University of Cologne's Institute for Biomedical Informatics and a Core Scientist at the Center for Data and Simulation Science. Her research focuses on enabling FAIR (Findable, Accessible, Interoperable, Reusable) data management, distributed analytics on sensitive medical data, and data-driven innovations in healthcare. She leads projects like the PADME platform for federated machine learning and privacy-preserving analytics. Key areas include biomedical informatics, semantic web technologies, clinical decision support systems, and ethical challenges in data science. Research Interests: FAIR Data Principles & Infrastructure Privacy-Preserving Distributed Learning Explainable AI in Healthcare Semantic Interoperability Medical Data Integration Ethical & Social Implications of Data Use Notable Contributions: Development of the Personal Health Train framework for decentralized medical data analysis Leadership in EU-funded initiatives like NFDI4Health and Medical Informatics Collaborations Pioneering work on federated learning applications in oncology and rare disease research Lab & Affiliations: Prof. Beyan's work is anchored in the Institute for Biomedical Informatics and the Center for Data and Simulation Science, fostering interdisciplinary collaboration between computational science and medical research.

Mohammad RostamiView profile

Academic

• Machine Learning
• Transfer Learning
• Domain Adaptation
• +5 more

Mohammad Rostami is a Research Assistant Professor at the University of Southern California (USC) in the Department of Computer Science and Electrical and Computer Engineering, with a joint appointment at the USC Information Sciences Institute (ISI). He holds a PhD in Electrical and Systems Engineering from the University of Pennsylvania and additional degrees in Robotics, Philosophy, Electrical Engineering, and Pure Mathematics from prestigious institutions including the University of Waterloo and Sharif University of Technology. His research focuses on machine learning in data-scarce environments, particularly transfer learning, domain adaptation, low-shot learning, and improving learning efficiency through continual and collective learning. He incorporates symbolic logic and neuro-symbolic approaches to address challenges in catastrophic forgetting and knowledge retention. Applications span medical imaging, computer vision, and explainable AI. Rostami has received several accolades including the UPenn Best PhD Dissertation Award, IJCAI Distinguished Student Paper Award, and University of Waterloo Outstanding Achievement Award. His work bridges theoretical advancements with practical implementations, emphasizing real-world applications in healthcare and autonomous systems. He teaches graduate courses in applied natural language processing and knowledge graph construction. Rostami advises students at all academic levels and collaborates with remote researchers, emphasizing motivated, long-term project commitments.

Hui ZhangView profile

Professor

• Computer Science
• Networking
• Data-Driven Systems
• +3 more

Hui Zhang is a Professor in the Computer Science Department at Carnegie Mellon University. His research focuses on data-driven networking systems, video streaming optimization, and network control frameworks. He has contributed to innovations in adaptive resource allocation, real-time analytics, and sustainable strategies for resource utilization. Key research themes include time-state analytics, network anomaly detection, and integrating machine learning for enhanced performance. His work addresses challenges in content delivery networks (CDNs), peer-to-peer systems, and environmental applications like waste management. Recent publications (2021–2024) highlight advancements in neural network-based prediction, timeline frameworks, and sustainable material science innovations. No scientific awards are mentioned in the provided text. His research emphasizes practical solutions for improving video quality of experience (QoE), network efficiency, and cross-disciplinary applications.

Mathias RisseView profile

Professor

• Global Justice
• Human Rights
• Political Philosophy
• +5 more

Mathias Risse is the Berthold Beitz Professor in Human Rights, Global Affairs and Philosophy at Harvard Kennedy School (HKS), where he also directs the Carr-Ryan Center for Human Rights and the Program on the Ethics of Emerging Technologies. He teaches at HKS, Harvard College, and the Harvard Extension School, and is affiliated with the Philosophy Department and the Weatherhead Center for International Affairs. Education & Career: Risse earned his PhD from Princeton University (2000) and previously taught at Yale University. He has held visiting roles at the National University of Singapore, NYU Abu Dhabi, and Leuphana University (Germany). He joined Harvard in 2002 and currently resides in Somerville, MA. Research Focus: His work bridges political philosophy and technology ethics, addressing global justice, human rights, climate change, and the societal impacts of AI. Key themes include Indigenous philosophies, digital governance, and ethical trade frameworks. Recent books include Political Theory of the Digital Age (2023) and On Trade Justice (2019). Awards & Leadership: Risse organizes international conferences fostering cross-cultural collaboration, directs the McCloy Fellowship program for German students, and co-hosts the Carr Center’s Justice Matters podcast. His writings on race, protest, and technology ethics have shaped public discourse. Grants & Outreach: He advises on AI ethics, climate policy, and global governance. Recent projects include analyses of solar geoengineering, Indigenous rights frameworks, and the societal implications of advanced AI systems. Labs/Teams: Central roles in the Edmond J. Safra Center for Ethics, the Carr Center for Human Rights Policy, and interdisciplinary initiatives on emerging technologies.

• Market Shaping
• Social Impact
• Sustainability
• +3 more

Dr Jonathan Baker is a Senior Lecturer in Strategy at the Adelaide Business School , part of the Faculty of Arts, Business, Law and Economics at the University of Adelaide. He previously served as Director of the Yunus Centre for Business, Sustainability & Social Impact (2022-2023) and has held academic positions at Auckland University of Technology, University of Auckland, and guest professorship at University of Bayreuth. His research focuses on Interdisciplinary intersections of markets, strategy, and social impact Market-shaping strategies Sustainability and circularity transitions UN Sustainable Development Goals (9, 11, 12) Systemic business model perspectives Dr Baker's work appears in top journals including Industrial Marketing Management , Journal of Business Research , and Marketing Theory . He serves on the Editorial Review Board of Industrial Marketing Management (ABDC A*). Scientific Awards Excellence Early Career Researcher Award (ANZAM-European Management Journal, 2023) Emerging Career Researcher Award (Adelaide Business School, 2023) As a principal supervisor, he welcomes PhD/MPhil candidates interested in market shaping, sustainability transitions, or social entrepreneurship. His methodology emphasizes qualitative research and ecosystem-level analysis.

Stefan WrobelView profile

Professor

• Machine Learning
• Data Mining
• Artificial Intelligence
• +3 more

Prof. Stefan Wrobel is a Professor of Computer Science at the University of Bonn and Director of the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS). He holds leadership roles, including Co-Director of the Lamarr Institute for Machine Learning and Artificial Intelligence and Managing Director of the Bonn-Aachen International Center for Information Technology (b-it). His research focuses on AI, machine learning, and big data applications in industry and society. He earned his PhD from the University of Dortmund and has held academic positions at Magdeburg University and Berlin Technical University. Active in national/international AI initiatives, he chairs the Fraunhofer Strategic Research Field on Artificial Intelligence and co-leads the Machine Learning Rhine-Ruhr (ML2R) Competence Center. Education: Master's (Georgia Tech), PhD (University of Dortmund). Research emphasizes intelligent algorithms, data analysis, and AI ethics. Awarded GI-Fellow (2022) and honored by the German Computer Science Society for contributions to AI history. Key roles include Editorial Board member of Machine Learning journals and advisory roles in AI ethics and certification. Scientific contributions span over 100 publications in machine learning, data mining, and visual analytics. Advised numerous PhD students on topics like graph mining and trustworthy AI. Leadership in institutions like Fraunhofer Technology Hub for Machine Learning and the German Computer Science Society's Special Interest Group on Knowledge Discovery.

• Building Information Modeling (BIM)
• Civil Engineering Informatics
• Tunneling and Underground Construction
• +5 more

Markus König is a Professor of Informatics in Civil Engineering at Ruhr University Bochum, where he has been researching and teaching since October 2009. His work focuses on Building Information Modeling (BIM), digital construction technologies, and civil engineering informatics, with significant contributions to the development and implementation of digital methods in German construction industry. Dr. König earned his degree in civil engineering with a focus on applied computer science at Leibniz University Hannover, where he also completed his doctorate on cooperative building planning at the Institute for Building Informatics. He subsequently held a junior professorship for Theoretical Methods of Project Management at Bauhaus University Weimar before joining Ruhr University Bochum. His research spans multiple cutting-edge areas including Building Information Modeling (BIM), construction process simulation, tunneling informatics, infrastructure asset management, and the application of artificial intelligence and computer vision in civil engineering. As chair of the Building Informatics Working Group from 2012-2016, he played a key role in developing the first national BIM curriculum for German universities and serves as editor of the book 'Building Information Modeling: Technological Foundations and Industrial Practice.' Analysis of his recent publications reveals a strong trend toward semantic technologies, digital twins, automated compliance checking, and the integration of AI in construction processes. His work increasingly focuses on information containers, ontology development, and the application of large language models to infrastructure data, reflecting the evolving landscape of digital construction. Dr. König's significant contributions to digital construction have been recognized with prestigious awards: Lower Saxony-Bremen Construction Industry Award (2017) for 'services in the development and introduction of digital construction in Germany' Konrad Zuse Medal (2020) While specific details about his advising and grant activities aren't explicitly mentioned in the provided text, his extensive publication record with numerous co-authors suggests active supervision of doctoral students and research staff. His involvement in multiple collaborative research projects is evident from his publication history. At Ruhr University Bochum, Professor König leads a research group focused on civil engineering informatics, with particular emphasis on BIM, digital construction technologies, and their application across the building lifecycle. His team appears to work at the intersection of computer science and civil engineering, developing innovative solutions for construction process optimization, infrastructure management, and digital transformation of the AEC industry.

Chenyu YouView profile

Assistant Professor

• Machine Learning
• Medical Image Analysis
• Computer Vision
• +17 more

Chenyu You is an Assistant Professor in the Department of Applied Mathematics & Statistics and Department of Computer Science at Stony Brook University. He is affiliated with CVLab, AI Institute, and Institute for Advanced Computational Science. His research focuses on principles and practice of trustworthy machine intelligence, emphasizing generalization and reliability in machine learning, with applications to healthcare, biomedical imaging, and cognitive neuroscience. Ph.D. in Electrical Engineering from Yale University (2024) M.S. in Electrical Engineering from Stanford University (2019) B.S. in Electrical Engineering from Rensselaer Polytechnic Institute (2017) His research spans three major areas: Efficient World Foundation Models (task-agnostic pretraining, scalable adaptation), Learning with Imperfect Data (label scarcity, class imbalance), and Biomedical Foundation Models (large-scale medical AI agents). Applied work includes healthcare, biomedical imaging, and cognitive neuroscience. Recent publications (2025) include breakthroughs in sparse coding (ICML), cycle-consistent diffusion models (ICCV), optimal transport for survival analysis (MICCAI), and prompt theory (ACL). His team addresses challenges in trustworthy AI, spurious correlation mitigation, and multi-modality robustness. Scientific recognition includes Excellence in Teaching Award (2025) , World's Top 2% Scientists (2024) , and multiple IEEE TMI Platinum Distinguished Reviewer awards. He advises students Qin Ren and Yifan Wang, with alumni pursuing roles at Two Sigma, Amazon Science, and top PhD programs. His lab collaborates with leading institutions and actively seeks motivated students for flexible-start positions. He serves as Associate Editor for IEEE Transactions on Medical Imaging and Area Chair for major conferences like MICCAI and NeurIPS.

• Biomedical Informatics
• Health Informatics
• Artificial Intelligence
• +7 more

Zhe He is a Full Professor at Florida State University (FSU), leading the eHealth Lab in the School of Information (iSchool) within the College of Communication & Information. He holds courtesy appointments in the Department of Behavioral Sciences and Social Medicine (College of Medicine), Department of Computer Science, and Department of Statistics. His research focuses on biomedical informatics, AI, and big data analytics, aiming to improve population health and advance biomedical research through informatics applications. He directs the Institute for Successful Longevity and co-leads the Biostatistics, Informatics, and Research Design Program (BIRD) of the UF-FSU Clinical and Translational Science Award. Education: Postdoctoral training at Columbia University (2015), PhD in Computer Science from NJIT (2014), MS from Columbia University (2009), and BE from Beijing University of Posts and Telecommunications (2007). Research Interests: Clinical trial generalizability, ontology quality assurance, consumer health informatics, and AI in medicine. His work bridges biomedical terminologies, patient engagement, and healthcare equity, with a focus on older adults and underserved populations. Grants & Funding: Over $21.9M in grants from NIH (NLM, NIA, NIMH), AHRQ, Amazon, NVIDIA, and Eli Lilly. Active grants include projects on medical marijuana effects, AI-driven clinical training, HIV prevention, and lab result interpretation tools for older adults. Awards & Honors: 2022 Lois Lunin Award (ASIS&T), FAMIA (2022), two AMIA Distinguished Paper Awards, and recognition for interdisciplinary research. Promoted to Full Professor in 2025 after early tenure as Associate Professor (2020). Labs & Teams: Directs the eHealth Lab and collaborates with跨学科 teams in the OneFlorida Data Trust, UF-FSU Clinical and Translational Science Award, and the National Center for Biotechnology Information (during sabbatical).

Angelina WangView profile

Assistant Professor

• Machine Learning Fairness
• Algorithmic Bias
• Responsible AI
• +3 more

Angelina Wang is an incoming Assistant Professor at Cornell Tech and the Department of Information Science at Cornell University, starting Fall 2025. Her research focuses on responsible AI, particularly machine learning fairness and algorithmic bias. She holds a Ph.D. in Computer Science from Princeton University and a B.S. in Electrical Engineering and Computer Science from UC Berkeley. Current postdoctoral work at Stanford’s HAI and RegLab explores sociotechnical challenges in AI deployment. Her research addresses fairness evaluation in generative AI, societal impacts of AI systems, and ethical trade-offs in algorithm design. Notable awards include the NSF GRFP, Siebel Scholarship, and Microsoft AI & Society Fellowship. Her work bridges technical and social dimensions of AI, emphasizing human-centered evaluation and interdisciplinary collaboration. Recent publications span medical AI applications (e.g., Alzheimer’s subphenotypes, corticosteroid treatment efficacy) and foundational fairness research. She advocates for proactive ethical considerations in technical work, citing examples like surveillance risks in facial recognition and dataset biases in computer vision. Angelina advises prospective PhD students in Cornell’s Information Science program and collaborates on projects like SciDaSynth for scientific knowledge synthesis. Her advocacy includes challenging fairness impossibility theorems and promoting algorithmic pluralism in auditing practices.

Shahram RahimiView profile

Professor

• Computational Intelligence
• Machine Learning
• Artificial Intelligence
• +10 more

Shahram Rahimi is a Professor and Department Head in the Department of Computer Science at the University of Alabama, College of Engineering. He concurrently holds an Adjunct Professor position at Mississippi State University. His research spans computational intelligence, machine learning, healthcare AI, cybersecurity, and quantum computing. He leads the PATENT Lab, focusing on predictive analytics, decision support systems, and AI-driven healthcare solutions. His educational background includes a Ph.D. in Computer Science. Key research areas include multi-agent systems, generative models, and predictive maintenance. He has served as an editor for journals like Scalable Computing: Practice and Experience and Informatica . Rahimi’s recent work emphasizes secure MLOps, quantum algorithms, and patient-centric medical systems. His publications address challenges in explainable AI, anomaly detection, and healthcare informatics. He actively contributes to conferences and journals in AI, cybersecurity, and computational intelligence. Editorial Roles: Scalable Computing, Engineering Letters, Informatica Labs: Predictive Analytics & Technology Integration (PATENT) Lab Key Focus Areas: Healthcare AI, Quantum Computing, Cybersecurity, Explainable Machine Learning

• Deep Learning
• Data Mining
• Artificial Intelligence
• +7 more

Asad Abdi is a Lecturer in Computer Science at the College of Science and Engineering. His research focuses on deep learning, data mining, and artificial intelligence , with applications in traffic analysis, educational technology, and maritime logistics. He has published extensively on topics like social media-based traffic forecasting, fake news detection, and vessel arrival prediction. Abdi’s work bridges theoretical advancements in machine learning with practical challenges in domains such as transportation systems and education. He has explored hybrid approaches combining deep learning models with linguistic knowledge and knowledge graphs to address real-world problems. Notable contributions include frameworks for feedback analysis in hybrid classrooms and fusion-based prediction models for vessel arrival times. His recent articles highlight trends in leveraging large language models and multi-feature fusion techniques for tasks like opinion summarization and aspect extraction. Abdi’s research often emphasizes interdisciplinary collaboration, integrating insights from computer science, transportation engineering, and educational psychology. While no formal awards or grants are explicitly listed, his publication record demonstrates sustained contributions to applied AI and data-driven solutions across multiple sectors.

Cyrus ModyView profile

Professor

• History of Science and Technology
• Commercialization of Academic Research
• Responsible Research and Innovation (RRI)
• +5 more

Cyrus C.C. Mody is a Professor in the History of Science, Technology, and Innovation and Director of the STS Program at Maastricht University. Formerly an Associate Professor (2014–2015) and Assistant Professor (2007–2014) at Rice University's Department of History, his research focuses on the commercialization of academic science, energy humanities, and the technopolitics of scarcity. He leads the NWO-funded 'Managing Scarcity and Sustainability' project and co-leads the ERC Synergy 'Nanobubbles' initiative examining scientific record correction. His expertise spans applied physics, university-industry partnerships, and countercultural science in the US since 1965. Education: Ph.D. (2004), M.A. (2001), Cornell University, Science and Technology Studies A.B. (1997), Harvard University, Engineering Sciences (magna cum laude) Research Interests: Mody explores how scientific knowledge interacts with industry, policy, and culture. Key themes include: Energy transitions and environmental diplomacy Historical roles of oil and semiconductor industries Responsible innovation frameworks Risk communication in science Grants & Collaborations: NWO Vici Grant (2020–2025): Investigates oil industry's role in sustainability debates ERC Synergy 'Nanobubbles': Addresses scientific discourse integrity Postdoc and PhD supervision in energy humanities and nanotechnology ethics Public Engagement: Mody critiques authoritarian threats to science, advocates for interdisciplinary education, and publishes in venues like Volkskrant and Science & Education . His 2022 MIT Press book The Squares analyzes 1970s scientist activism.

Julie Michelle KlingerView profile

Associate Professor

• Critical Minerals Supply Chains
• Global Space Politics
• Community Survival Strategies
• +5 more

Julie Michelle Klinger is an Associate Professor in the Department of Geography and Spatial Sciences at the University of Delaware's College of Earth, Ocean & Environment. Her research examines global resource frontiers and space-based technologies through ethnographic fieldwork across China, Brazil, and the United States, with significant contributions to environmental politics and critical minerals governance. Her educational background includes: Ph.D. in Geography from the University of California, Berkeley (2015) B.A. from Sarah Lawrence College (2006) Dr. Klinger's research program centers on three interconnected themes: critical minerals supply chains (analyzing environmental/social impacts of rare earth extraction for sustainable decarbonization), global space politics (challenging privatization narratives through projects like her book 'Capitalizing the Cosmos'), and community survival strategies (collaborating with Indigenous groups like Brazil's Yanomami to document land use amid extractive pressures). Her work consistently bridges geopolitical analysis with on-the-ground survival tactics in resource frontier zones. Recent publications (2020-2024) reveal intensifying focus on US-China space rivalry, mineral supply chain vulnerabilities for renewable energy, and the environmental geopolitics of orbital infrastructure. She increasingly connects terrestrial mining impacts with space resource extraction debates, emphasizing Global South perspectives. Her accolades include the 2017 Meridian Book Prize for 'Rare Earth Frontiers: From Terrestrial Subsoils to Lunar Landscapes'. Dr. Klinger has secured funding from the National Science Foundation, Irmgard Coninx Stiftung, and Johns Hopkins University's China-Africa Research Initiative. She previously co-directed Boston University's Land Use and Livelihoods Initiative and mentors students in community-centered research partnerships, particularly with Amazonian Indigenous communities. Affiliated with UD's Embodiment Lab and Minerals, Materials and Society Program, she develops collaborative frameworks with remote sensing specialists and Indigenous knowledge holders to advance equitable climate solutions.