جست‌وجوی استاد و پژوهشگر

Kelly Ormondمشاهده پروفایل

مدرس

• Bioethics
• Genetic Counseling
• Medical Ethics
• +۴ مورد دیگر

Kelly Ormond is a Lecturer at the Department of Health Sciences and Technology, ETH Zurich, and an Adjunct Professor at Stanford University's Department of Genetics. She is a certified genetic counselor with over 25 years of clinical and academic experience in genetic counseling, bioethics, and translational medicine. Her primary affiliation is with the Health Ethics and Policy Lab at ETH Zurich, where she focuses on ethical challenges in genetics, personalized medicine, and emerging technologies like gene editing. Education: MS in Genetic Counseling (Northwestern University, 1994), Post-Graduate Certificate in Clinical Medical Ethics (University of Chicago, 2001) Professional Roles: Registered Genetic Counselor (US and Europe), Member of ESHG Policy and Ethics Committee, President of Transnational Alliance for Genetic Counseling (TAGC) Her research emphasizes ethical issues in prenatal testing, gene editing, and the intersection of genetics with disability rights. Current grants include studies on prenatal testing ethics in Switzerland and gene editing governance. She has held leadership roles in US genetic organizations (ASHG, NSGC) and contributed to global policy frameworks for genetic technologies. Teaching and Training: Former Director of Genetic Counseling Programs at Northwestern University (1999–2007) and Stanford (2007–2020), where she taught ethics, genetics, and research methodologies. Key Professional Contributions: Authored over 100 peer-reviewed articles, developed ethical guidelines for genetic testing disclosure, and advocated for global genetic counseling standards. Active in public-private partnerships to address health data governance challenges in Switzerland and beyond.

Kerstin Vokingerمشاهده پروفایل

دانشیار

• Health Policy
• Pharmaceutical Economics
• Medical Technology Regulation
• +۳ مورد دیگر

Prof. Kerstin Vokinger is an Associate Professor at the Department of Health Sciences and Technology, ETH Zurich. Her research focuses on pharmaceutical economics, healthcare policy, AI in medicine, and regulatory science. She investigates drug pricing strategies, managed entry agreements, and the therapeutic value of medicines. Her work often compares policies between the US, Europe, and Switzerland, addressing issues like cancer drug pricing, orphan drug designation, and AI-based medical devices' regulation. Key research areas include: Clinical trial outcomes and drug approval processes Health technology assessment and cost-effectiveness analysis Legal frameworks governing healthcare innovation Data privacy in medical research and AI applications Her recent articles analyze trends such as the 'cancer premium' in drug pricing, the impact of expedited approvals on therapeutic value, and global disparities in cancer drug access. She also explores regulatory challenges in AI-driven medical devices and the ethical implications of anonymized healthcare data. Prof. Vokinger collaborates with institutions worldwide to shape evidence-based health policies and improve drug affordability. Her work bridges legal, economic, and scientific dimensions of healthcare systems.

Tom Ginsburgمشاهده پروفایل

استاد

• Comparative Law
• International Law
• Constitutional Law
• +۳ مورد دیگر

Tom Ginsburg is the Leo Spitz Distinguished Service Professor of International Law and Professor of Political Science at the University of Chicago. He holds a PhD and JD from the University of California, Berkeley. His research focuses on comparative and international law, with expertise in constitutional design, democratic governance, and legal institutions. He co-directs the Comparative Constitutions Project, funded by the NSF, analyzing global constitutional trends since 1789. Awards include multiple best book prizes and membership in the American Academy of Arts and Sciences. Education: PhD in Jurisprudence and Social Policy (1999), JD (1997), and BA in Asian Studies (1989) from UC Berkeley. Research Interests: Ginsburg’s work bridges law and political science, emphasizing constitutional endurance, democratic backsliding, and transnational legal influences. Recent publications include *Democracies and International Law* (2021) and *How to Save a Constitutional Democracy* (2018). His analyses often address how constitutions function as political insurance and the interplay between domestic and international law. Articles Trends: Focus on AI-driven legal analysis, democratic procedures in constitutional reforms, and the role of religion in legal systems. Recent work critiques authoritarian uses of international law and explores machine learning applications in human rights studies. Awards: Highlighted prizes include the APSA’s C. Herman Pritchett Award (2003) and the International Society of Constitutional Law’s Best Book Award (2018). His work frequently appears in top law and political science journals. Advising & Grants: Ginsburg advises international organizations like International IDEA and has led NSF-funded projects. He co-founded the Forum on Free Inquiry and Expression at UChicago, emphasizing academic freedom. Labs/Teams: Central to his work is the Comparative Constitutions Project, a collaborative effort digitizing and analyzing global constitutions. He also collaborates with the Malyi Center for the Study of Institutional and Legal Integrity.

• Data Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Mohsen Farid is a Senior Lecturer in Data Science at the College of Science and Engineering. His research spans interdisciplinary areas including artificial intelligence, machine learning, neurotechnology, and healthcare analytics. He has contributed to advancements in genomics data management, video authentication, and neurotechnological solutions for mental health conditions like PTSD. His work frequently integrates computational methods with real-world applications in healthcare and cybersecurity. Key research outputs include studies on storage-optimized genomics systems (2024), neurotechnological interventions for PTSD (2023), and deep learning analyses of histopathology images (2021). His earlier contributions include gait recognition systems (2018) and semantic mapping of legal arguments (2015). Farid’s publications reflect a strong focus on applied data science and its societal impact, particularly in healthcare, security, and biomedical engineering. While no specific awards or grants are explicitly mentioned, his extensive publication record highlights sustained contributions to interdisciplinary data-driven research. His articles often address challenges in data management, pattern recognition, and ethical applications of AI.

Jonas Rieskampمشاهده پروفایل

پژوهشگر

• Social Media Analytics
• Artificial Intelligence
• Digital Disinformation
• +۴ مورد دیگر

Jonas Rieskamp serves as a Researcher at the Chair of Business Informatics, especially AI Engineering in Business within the Faculty of Business Information Systems and Applied Computer Science at Otto-Friedrich University Bamberg, contributing to research and teaching since March 2022. Education: Bachelor's in Business Informatics, South Westphalia University of Applied Sciences (2018) Master's in Business Informatics, University of Paderborn, specializing in machine learning for computational linguistics His research centers on social media polarization and digital disinformation , employing social media analytics and artificial intelligence to investigate societal phenomena. As a key contributor to the PREVENT project, he develops countermeasures against disinformation campaigns using AI-driven agent-based modeling while exploring generative AI applications in crisis communication and virtual work environments. Publications from 2022-2025 reveal consistent focus on platform-specific disinformation dynamics (Twitter/Telegram), conversational agents in healthcare/open science ecosystems, and ethical AI deployment in hiring processes, with emerging work on social bot interventions during natural disasters. Jonas supervises Bachelor's and Master's theses across AI Engineering and Digital Innovations courses while actively teaching in both programs. He maintains affiliation with Prof. Dr. Milad Mirbabaie's research team at Gutenbergstraße 13, Room GU13/03.04b.

Achim Rettingerمشاهده پروفایل

استاد

• Machine Learning
• Knowledge Representation
• Natural Language Processing
• +۴ مورد دیگر

Achim Rettinger is a full professor at Trier University, leading the research group krAil (Knowledge Representation Learning). He specializes in machine learning, natural language understanding, and human-centered AI. His work focuses on expressive knowledge representations and their applications in semantic technologies. Education: Studied Computer Science at Universität Koblenz (Germany), University of Georgia (USA), and University of Alberta (Canada). PhD in machine learning at TU Munich/Siemens AG, followed by habilitation at KIT (2016). Served as interim professor at Karlsruhe Institute of Technology (2018/19). Research interests include knowledge graphs, cross-lingual semantic annotation, and data-driven analysis in political and medical domains. Notable contributions include the X-LiSA framework and work on semantic web technologies. Awards include best paper and challenge awards at ISWC and ESWC conferences. Leadership roles include senior PC member at ISWC, track chair at ESWC, and membership in AI for Good Foundation. Active in EU projects, DFG grants, and large-scale collaborative initiatives. Key projects: BreXearch (cross-lingual Brexit analysis), xLiMe System (semantic search), and medical decision support systems for liver surgery. Collaborates with interdisciplinary teams on cognition-guided surgery and data integration. Publications span top venues like ISWC, NeurIPS, ICLR, and CVPR, with a focus on semantic web, machine learning, and applied AI solutions.

Jennifer Hyndmanمشاهده پروفایل

مدرس

• Data Analytics
• STEM
• Technology Enhanced Learning
• +۳ مورد دیگر

Jennifer Hyndman is a Lecturer in the Department of Computing at Atlantic Technological University, Ireland. Her work bridges academic teaching and cutting-edge research, with a focus on integrating technology into education and advancing computational methodologies. Education : PhD in Computing (2008), supervised by Dr. Tom Lunney and Prof. Paul Mc Kevitt at the University of Ulster, Magee, Derry. Research Interests Jennifer's research spans Data Analytics , STEM , Technology Enhanced Learning , and IoT . Her work explores applications of Artificial Intelligence and Machine Learning in educational contexts, robotics, and ambient intelligent systems. Publication Trends Her publications (2008–2024) demonstrate a trajectory from foundational work in ambient learning environments for children to advanced studies in swarm robotics and deep learning applications. Recent contributions focus on tertiary education pedagogy, cloud computing , and autonomous systems . Teaching Contributions She has taught diverse subjects including Mathematics for Computing , Python Scripting , Data Analytics , and Legal, Ethical, and Social Issues in Computing .

Shiri Dori-Hacohenمشاهده پروفایل

استادیار

• Information Ecosystem Threats
• AI Safety
• Sociotechnical AI Alignment
• +۵ مورد دیگر

Shiri Dori-Hacohen is an Assistant Professor of Computer Science & Engineering at the University of Connecticut, directing the Reducing Information Ecosystem Threats (RIET) Lab. Her work focuses on AI safety, sociotechnical AI alignment, and mitigating information ecosystem threats through transdisciplinary collaboration. She has secured $7.7M in NSF funding and received awards including the 2023 D-30 Disability Impact List for groundbreaking fairness research. Education: B.Sc. and M.Sc. (cum laude) in Computer Science, University of Haifa, Israel M.S. and Ph.D. in Computer Science, University of Massachusetts Amherst Research Interests: Combating misinformation, controversy detection, AI ethics, and health equity. Her work bridges computer science with medicine, public health, and social sciences. Current projects address disinformation, botnet detection, and fairness in medical AI systems. Awards and Recognition: 2023 D-30 Disability Impact List 2022 AI Risk Analysis Award (NeurIPS) 2016 UMass Amherst Innovation Challenge First Place 2011 Google Lime Scholarship Leadership & Advocacy: Co-founder of Graduate Women in STEM @ UMass, Women in Information Retrieval, and Disabled In Computing. Active media commentator featured in Reuters, The Guardian, Forbes, and Galei Tzahal radio. Labs & Initiatives: PI of RIET Lab which develops computational tools to detect threats in information ecosystems. Research incorporates petabyte-scale social network data and graph-theoretic approaches. Current focus on medical fairness and misinformation mitigation in marginalized communities.

Michael J. Hasdayمشاهده پروفایل

استادیار

• Civil Procedure
• Complex Litigation
• Health Law
• +۳ مورد دیگر

Michael J. Hasday is an Assistant Professor of Law at St. Thomas University's Benjamin L. Crump College of Law, joining in 2023. Previously, he served as a Visiting Professor at the University of Massachusetts School of Law and a lecturer at DeSales University. His expertise spans Civil Procedure, Complex Litigation, Health Law, Game Theory, and Artificial Intelligence. Education: B.A. in Political Science (cum laude) from the University of Pennsylvania and J.D. (cum laude) from Northwestern Pritzker School of Law. Research focuses on applying game theory and AI to improve legal decision-making. Notable projects include redesigning appellate court panel selection methods and proposing equitable arbitration frameworks. His work has been featured at the 33rd Stony Brook International Conference on Game Theory and the 2020 MIT Sloan Sports Analytics Conference. Teaching emphasizes practical legal skills, informed by over a decade of litigation experience in New York City and Pennsylvania, and as in-house counsel for a healthcare consulting firm. Awards: Finalist in 2020 MIT Sloan Sports Analytics Conference research paper competition Advising/Grants: No explicit student advisees or grants mentioned. Research supported by academic contributions to conferences.

Nancy Scheidtمشاهده پروفایل

مدرس

• Digital and IoT Forensics
• Cybercrime
• Digital Forensic Training for Investigators
• +۲ مورد دیگر

Nancy Scheidt is a Lecturer in Criminology at the University of Winchester, affiliated with the Faculty of Law, Crime and Justice. She joined the university in 2022 after earning her PhD in IoT Forensics (2022) from the University of Portsmouth, following a BSc (Hons) in Criminology and Forensic Studies (Portsmouth) and an MSc in Forensic Information Technology (Portsmouth). Her research focuses on IoT Forensics challenges, investigator training, and forensic psychology, with notable contributions to cybercrime analysis and digital evidence methodologies. She teaches modules like Cybercrime and Cybersecurity, Volunteering and Academic Skills, and oversees dissertations across undergraduate and postgraduate levels. Nancy actively publishes in journals and conferences, addressing topics such as smart device forensics, IoT threat mitigation, and machine learning applications in detecting social biases. Her work bridges technical and psychological aspects of digital forensics, emphasizing practical training for professionals and ethical considerations in data sharing. Nancy’s expertise spans hybrid systems, forensic tool development, and formal methods for investigation processes.

• Computer Science
• Data Mining
• Database Systems
• +۷ مورد دیگر

Yi Chen is a Professor at the MT School of Management and Director of the Center for Big Data at New Jersey Institute of Technology (NJIT). His research focuses on database systems, information retrieval, XML processing, privacy/security, and healthcare informatics. He has led numerous NSF-funded projects, including studies on privacy interventions in online publishing ecosystems and meta-information analysis in semi-structured data. Key contributions include work on counter-ad-blocking strategies, GDPR compliance frameworks, and machine learning models for healthcare prediction. He has published over 100 articles in top venues and holds an h-index of 24 with 1,947 citations. Notable awards include recognition in the Japanese Economic Review. Research interests combine computational methods with real-world applications, particularly in privacy-preserving systems, medical data analytics, and workflow optimization. Recent projects explore the impact of transparency frameworks in digital advertising and biomarker extraction using sentiment analysis techniques. His work bridges theoretical advancements with practical solutions for industry challenges. Grants: 11 federal grants including NSF projects on workflow mining, ad-blocking dynamics, and student research initiatives. Lab: Center for Big Data at NJIT, focusing on large-scale data challenges. Publications span key areas like ad viewability prediction, XML search engines (XSeek), and healthcare forum analysis. Collaborations include work on privacy frameworks and optimizing ad auction mechanisms.

Miranda Mourbyمشاهده پروفایل

پژوهشگر

• Privacy Law
• Data Protection
• Healthcare Law
• +۵ مورد دیگر

Miranda Mourby is a Researcher in Law at the Centre for Health, Law and Emerging Technologies (HeLEX) within the University of Oxford's Social Sciences Division. She focuses on privacy, data protection, and governance in health and life sciences research, with particular expertise in biomodifying technologies and regulatory frameworks. Co-chair of the Social Science Division's Research Staff Forum, she advocates for fixed-term researchers' interests. Previously a barrister specializing in NHS regulatory law, Mourby joined HeLEX in 2017 as part of the Administrative Data Research Network. Her work bridges legal, ethical, and policy challenges in healthcare innovation, including GDPR compliance, machine learning transparency, and secondary data use. She collaborates with institutions like Imperial College London and leads projects such as BrainBioLink and EU-STANDS4PM. Her teaching spans Oxford's Civil Law (BCL) program on health data regulation and graduate-level genomic data governance. She also lectures on property law at the University of Sheffield and summer school topics like bio-modifying technologies. Key research themes include adaptive societal governance for biomedical innovations and ethical tensions between data protection and public interest research. Mourby's publications address cutting-edge issues like synthetic data regulation, patent governance in biotechnology, and pandemic-era NHS data management. Her work emphasizes interdisciplinary collaboration to navigate evolving legal landscapes while protecting individual rights in rapidly advancing technological contexts.

• Digital Law
• Ethical Agency
• Generative AI
• +۴ مورد دیگر

Professor Sylvie Delacroix holds the Inaugural Jeff Price Chair in Digital Law at King’s College London’s Dickson Poon School of Law and directs the Centre for Data Futures. She is also a visiting professor at Tohoku University. Her work bridges law, ethics, and technology, focusing on data governance, AI’s societal impact, and ethical agency. Key research areas include data trusts, machine learning interpretability, and uncertainty communication in LLMs. She has been awarded the Leverhulme Prize and the Montgomery Fellowship. Her grants include funding from the Patrick J. McGovern Foundation, Wellcome Trust, and others. She supervises PhD students in AI ethics and legal theory, and her interdisciplinary projects include KingsCAT, a social media analysis tool. Recent events she co-organized include discussions on AI in education and medical care. Her book Habitual Ethics? explores non-deliberative foundations of ethical agency. Research Interests: Agency, habit, and ethical decision-making; data ecosystems and generative AI sustainability; participatory infrastructure; legal frameworks for emerging technologies. Awards: Leverhulme Prize (2020), Montgomery Fellowship (2025). Grants: Patrick J. McGovern Foundation, Wellcome Trust, Omidyar Network, etc. Active in policy initiatives, including the Public Policy Commission on algorithms in justice systems. Leads the Data Trusts Initiative, promoting bottom-up data empowerment mechanisms. Teams/Labs: Centre for Data Futures, KingsCAT project. Collaborates across disciplines on AI ethics and legal tech.

Pascual Garcia Perezمشاهده پروفایل

پژوهشگر

• Food Technology
• Nutrition
• Metabolomics
• +۶ مورد دیگر

Pascual Garcia Perez is an Investigador Ramón y Cajal at the University of Murcia, affiliated with the Faculty of Veterinary Medicine and the Department of Food Technology, Nutrition and Bromatology. He leads research in the Nutrición, Biotecnología Alimentaria y Aspectos Legales (Biofun) group, with prior involvement in the Plants Biofactory research group. His doctoral degree from the Universidad de Vigo (2021) focused on phytochemical valorization of Bryophyllum spp. using biotechnological and machine learning tools. His research emphasizes metabolomics, plant biochemistry, and the application of advanced analytical techniques to study bioactive compounds in medicinal plants, food systems, and agricultural crops. Key themes include plant stress responses, food authenticity, and the bioavailability of nutrients in microgreens and fermented foods. Collaborative projects explore sustainable agriculture practices and the industrial exploitation of underutilized plant species. Recent work highlights multi-omics approaches to elucidate metabolic pathways under abiotic stresses, the development of biocontrol strategies for crop diseases, and the optimization of extraction methods for phytochemicals. His publications reflect a strong focus on integrating computational tools with experimental data to predict metabolic outcomes and enhance food quality. Although no formal academic awards are listed, his extensive publication record and prestigious Ramón y Cajal position underscore his contributions to food and agricultural sciences. His advisory roles and research mentorship are reflected in his doctoral training under Dr. Pedro Pablo Gallego Veigas.

Angela Almela Sanchez-Lafuenteمشاهده پروفایل

دانشیار

• Forensic Linguistics
• Computational Linguistics
• Corpus Linguistics
• +۴ مورد دیگر

Angela Almela Sanchez-Lafuente is an Associate Professor in the Department of English Philology at the University of Murcia's Faculty of Arts and Humanities. She is affiliated with the LACELL research group (Linguistics Applied to Computing, Language Teaching and Lexicography). She earned her PhD from the University of Murcia in 2012 with a thesis on linguistic deception analysis in English and Spanish. Her research focuses on computational linguistics, forensic linguistics, and corpus-based studies of deception detection, political discourse, and medical text analysis. She has developed tools like Umutextstats for linguistic feature extraction and contributed to projects like AIInFunds for financial sector NLP applications. Her academic background includes extensive work in forensic linguistics, including studies on corpus applications in legal contexts and error analysis in specialized texts. She has published widely on NLP applications for sentiment analysis, political ideology detection, and cross-lingual machine learning. Her research often bridges computational methods with sociocultural issues, such as analyzing migrant representation in judicial decisions. Key areas of expertise include: forensic text analysis, transformer model applications, multilingual NLP, and developing linguistic tools for financial/economic monitoring. She has supervised research projects involving AI-driven platforms for financial information analysis and participated in international NLP competitions like IberLEF and SemEval.