جست‌وجوی استاد و پژوهشگر

Oleg Petrenkoمشاهده پروفایل

دانشیار

• Strategic Management
• Entrepreneurship
• Executive Psychology
• +۳ مورد دیگر

Oleg Petrenko is an Associate Professor of Management and the Rath Chair in Strategic Management at the Michael F. Price College of Business, University of Oklahoma. He holds a Ph.D. from Oklahoma State University and focuses on the micro-foundations of strategy in large corporations and new ventures, particularly the psychological influences of executives and entrepreneurs on strategic decision-making and firm performance. His research bridges leadership psychology and organizational strategy, aiming to enhance leadership effectiveness. Prior to OU, he taught at the University of Arkansas and Texas Tech University. His work has been published in over 20 peer-reviewed articles, emphasizing topics like CEO personality traits (e.g., Machiavellianism, narcissism), venture capital dynamics, and standardized research methodologies. He is a proponent of replicable research practices and has contributed to frameworks like the SMART Tool for management research. His scholarship frequently addresses power dynamics in entrepreneurial ecosystems, leadership succession, and the interplay between personal attributes and corporate outcomes. Notable themes include the impact of executive agreeableness on costs, the role of language style in investor pitches, and the behavioral foundations of strategic action.

Vera Schmittمشاهده پروفایل

استادیار

• Natural Language Processing
• Artificial Intelligence
• Human-Computer Interaction
• +۶ مورد دیگر

Dr. Vera Schmitt is an Assistant Professor and leads the XplaiNLP research group at the Quality and Usability Lab (Q&U) of Technische Universität Berlin. She established the XplaiNLP group in 2023 through third-party funding and focuses on NLP, AI explainability, HCI, and legal aspects of AI systems, particularly in disinformation detection and medical data processing. She holds a BA in Political and Administrative Sciences from the University of Konstanz, a Master's in Data Science from Leuphana University Lüneburg, and a PhD from TU Berlin on data protection economics. Her research spans NLP (misinformation detection, text anonymization), data synthesis (medical records), XAI (natural language explanations), HCI (collaborative AI systems), and usable privacy (economic perspectives of privacy). She has secured over €4.1 million in third-party funding, including the €1.4 million BMBF grant for her AI junior research group. Current projects include VERANDA (medical data anonymization), NEWS-POLYGRAPH (disinformation), and FakeXplain (AI fact-checking). Her work emphasizes ethical AI alignment with regulations like the AI Act and GDPR. Teaching includes seminars on usable privacy, AI ethics, and advanced statistics. She collaborates with institutions like DFKI’s SLT group and has published extensively on topics ranging from privacy nudges to multimodal fake news detection.

Veronika Solopovaمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Social Media Analysis
• AI Ethics
• +۶ مورد دیگر

Veronika Solopova is a researcher at the Quality and Usability Lab, TU Berlin, specializing in natural language processing and AI ethics. Her work focuses on automated content moderation, disinformation detection, and computational analysis of social media phenomena like hate speech, propaganda, and incel movements. She holds a Dr.rer.nat from Free University of Berlin (2024) with research on hybrid AI systems for content analysis. Previously, she completed master’s studies at Sorbonne Nouvelle University and a visiting fellowship at University of Potsdam. Key projects include BMBF-funded PetraKIP (teacher training feedback system) and noFake’s CORRECTIV platform for citizen journalism fact-checking. She has received prestigious awards including the Elsa von Neumann Scholarship (2020) and Truth to Justice Fellowship (2024). Her teaching roles include advanced AI ethics and machine learning courses at FU Berlin, with workshops on LLMs for non-technical audiences. Research areas span multimodal disinformation detection (combining video/text/image analysis), explainable AI (XAI) for lay users, and computational studies of marginalized online groups. Current work emphasizes AI policy frameworks for Germany/Ukraine contexts and developing RAG systems for fact-checking. She collaborates with the German Research Center for Artificial Intelligence (DFKI) Speech and Language Technology Group.

Yapeng Tianمشاهده پروفایل

استادیار

• Computer Vision
• Computer Audition
• Machine Learning
• +۵ مورد دیگر

Yapeng Tian is an Assistant Professor in the Computer Science Department at the University of Texas at Dallas, leading the Computer Vision and Multimodal Computing (CVMC) Lab. He holds a PhD from the University of Rochester and Master's/Bachelor's degrees from Tsinghua and Xidian Universities. His research focuses on multimodal AI, audio-visual perception, and applications in accessibility and healthcare. He has organized workshops at ICCV 2025 (CV4A11y, MCL, KnowledgeMR) and serves on program committees for top conferences like NeurIPS, CVPR, and ICLR. Education: PhD (University of Rochester), MEng (Tsinghua), BEng (Xidian). Visiting scholar at SIAT, internships at Adobe and Meta. Research emphasizes unified audio-visual systems, generative AI, and assistive technologies. Key projects include CookAR (AR for low-vision users), AV-NeRF (audio-visual scene synthesis), and MRI super-resolution. His work has been recognized with awards including AAAI New Faculty Highlights and Amazon Research Award. Teaching includes courses on Computer Vision and Introduction to Computer Vision at UTD. Supervised over 20 students, with notable alumni advancing to roles at universities and tech companies.

John Dickersonمشاهده پروفایل

استاد

• AI and Robotics
• Machine Learning and Data Science
• Databases and Big Data
• +۴ مورد دیگر

John Dickerson is a tenured Professor of Computer Science at the University of Maryland, with a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS). He focuses on AI, machine learning, and algorithmic fairness, with applications in healthcare, market design, and societal impact. His research integrates computational economics, stochastic optimization, and game theory. Education: Ph.D. (Carnegie Mellon University, 2016), B.Sc. (University of Maryland, 2008). Affiliations: AMSC program, Human-Computer Interaction Lab (HCIL), Maryland Transportation Institute (MTI). Research Interests: Fair clustering algorithms, algorithmic fairness in hiring and admissions, robust AI systems, kidney exchange optimization, and AI for social good. His work emphasizes ethical considerations and societal impact, including projects on health literacy apps and reducing bias in face recognition systems. Articles Trends: Recent publications address fairness in machine learning, counterfactual explanations, robust clustering, and AI governance strategies. Key themes include aligning AI with human values, mitigating bias in algorithms, and deploying ethical systems in real-world scenarios. Scientific Awards: 2020 UMD Graduate Faculty Mentor of the Year, 2019 NSF CAREER Award, 2019 Google Faculty Research Award. His mentorship has been pivotal in students' achievements, such as the Philip Merrill Presidential Scholar recognition. Grants & Labs: Supported by NSF, NIH, DARPA, and industry partnerships. Co-founded Arthur, an AI monitoring firm, and co-directs the Cornell-Maryland-Max Planck PhD program. Active in organ allocation policy through UNOS and blood donation initiatives.

• Artificial Intelligence
• Software Development
• Large Language Models
• +۴ مورد دیگر

Kai-Kristian Kemell is a Research Fellow in the Computing Sciences department, focusing on interdisciplinary research at the intersection of Artificial Intelligence, Software Engineering, and Ethical AI. His work explores practical applications of Large Language Models (LLMs), autonomous agents in software development, and regulatory frameworks like the EU AI Act. Research Interests : His primary areas include AI-driven software development tools, ethical implementation of AI systems, multi-agent systems for code refactoring, and systematic literature reviews on trustworthiness in LLMs. He investigates how LLMs can automate tasks like microservice generation from API definitions and assist early-stage software startups through prompt engineering. Collaborations : Active collaborations include projects with researchers like Prof. Petri Abrahamsson, focusing on topics such as RAG systems, AI ethics governance, and hybrid work practices in software engineering. His work bridges theoretical AI concepts with practical industrial applications. Publications : His 2025 publications emphasize autonomous software development agents, EU AI Act critiques, and ethical alignment strategies for LLM-based systems. Earlier work (2023–2024) addresses AI ethics implementation via user stories, hybrid work impacts, and MLOps challenges. Awards : No specific scientific awards mentioned in the provided texts. Grants & Labs : No explicit details on grants or affiliated labs, but his research frequently involves collaborative projects with industry and academic partners.

Namchul Shinمشاهده پروفایل

استاد

• IT Value
• Environmental Sustainability
• Open Data
• +۲ مورد دیگر

Namchul Shin is a Professor of Information Systems at the Seidenberg School of Computer Science and Information Systems, Pace University . He received his PhD in Management (MIS) from the University of California, Irvine (1997), MBA from the University of Toledo (1988), and BA in Linguistics from Seoul National University (1985). Research Interests: IT Value, Environmental Sustainability, Open Data, Geographic Information Systems (GIS), and Nonprofit Organizations Academic Leadership: Co-founder of SIGGIS (AIS Special Interest Group on Geographic Information Systems) Professional Roles: Associate Editor of Journal of Electronic Commerce Research, Editorial Board Member of Business Process Management Journal Recent Publications focus on GIS integration in sustainability research, smartphone environmental impacts, and nonprofit digital strategies. His work has appeared in Communications of AIS , Stanford Social Innovation Review , and Negotiation Journal . He organized minitracks/workshops at HICSS, AMCIS, and other conferences. Honors: Faculty Fellow, Wilson Center for Social Entrepreneurship (2013–2014, 2017–2018, 2021–2022) Faculty Fellow, Office of the Provost (2012–2014) Excellence in Research Award, Seidenberg School (2001) Professional Service: Reviewer and committee member for AIS, ICIS, ECIS, and journals like Decision Support Systems . Active in curriculum development for GIS and location analytics courses.

Jiatao Guمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Jiatao Gu is an Assistant Professor in the Department of Computer and Information Science (CIS) at the University of Pennsylvania, with a planned start in Fall 2025. He also works as a part-time Staff Research Scientist at Apple (MLR) and previously served as a full-time Research Scientist at Meta AI (FAIR Labs). His academic journey includes a Ph.D. in Electrical and Electronic Engineering (2018) from the University of Hong Kong under Prof. Victor O.K. Li, and a B.Eng. in Electronic Engineering (2014) from Tsinghua University.

Sanja Golijaninمشاهده پروفایل

استادیار

• Administrative Law
• State Administration
• Administrative Procedures
• +۴ مورد دیگر

Assistant Professor Sanja Golijanin, LLD, is affiliated with the Faculty of Law at the University of East Sarajevo , where she teaches courses in Administrative Law, including Substantive and Procedural Parts, as well as Judicial Control of Administration. She has worked at the university since 2005 and was elected assistant professor in 2020 for the field of administrative law and administration. Education Graduated from Faculty of Law, University of East Sarajevo (2003) LLM, Faculty of Law, Belgrade University (2008), thesis: Ombudsman Doctoral thesis: Judicial Control of Acts of State Administration (University of Kragujevac, 2019) Her research focuses on Administrative Law , with emphasis on judicial oversight of state administration, procedural reforms, and intersections between administrative and private international law. Recent publications analyze topics like asylum procedures, administrative contracts, and constitutional control mechanisms. She has authored 20 academic papers and is proficient in English and Russian. Her consulting hours are aligned with lecture and exam periods.

Shan Hongjunمشاهده پروفایل

استاد

• Maritime Law
• International Maritime Law
• Transportation Policy
• +۳ مورد دیگر

Dr. Shan Hongjun is the current President and Professor at Dalian Maritime University (DMU), China. He also serves as an International Executive Board Member of the International Association of Maritime Universities (IAMU). His academic journey includes a Bachelor's degree from DMU (1991), a Master of Law in Maritime Law from DMU (1998), an LLM from Tulane University (2005), and a PhD in Law from Tulane University (2007). Prior to his presidency, he held roles such as Dean of DMU's Law School, Vice President of DMU (since 2013), and Deputy Director General of China’s Ministry of Transport’s International Cooperation Department (2017–2023). His expertise spans maritime law, international maritime policy, and governance, with a focus on legal frameworks shaping global maritime transportation. Education: Bachelor's Degree, Dalian Maritime University (1991) Master of Law (Maritime Law specialization), Dalian Maritime University (1998) LLM, Tulane University (2005) PhD in Law, Tulane University (2007) Research Interests: Dr. Shan’s work centers on maritime legal systems, international maritime regulatory frameworks, and policy analysis. He explores challenges posed by emerging technologies (e.g., autonomous ships) to maritime law, sustainable maritime practices, and cross-border governance in shipping industries. His contributions aim to align legal standards with contemporary maritime operational and environmental demands. Professional Roles: President of Dalian Maritime University (June 2023–present) Vice President of Dalian Maritime University (September 2013–June 2023) Deputy Director General, International Cooperation Department, China’s Ministry of Transport (June 2017–June 2023)

Peter Drahosمشاهده پروفایل

استاد

• Intellectual Property Law
• Climate Change Governance
• Energy Policy
• +۴ مورد دیگر

Peter Drahos is a Professor in Law at The Australian National University (ANU) and holds the Chair in Intellectual Property at the University of London. He directs the Centre for Governance of Knowledge & Development and specializes in intellectual property law, climate governance, and regulatory theory. His work bridges legal systems, international negotiations, and policy design. Education: LLB/BA (Hons) from University of Adelaide, Grad Dip in Legal Practice (University of South Australia), LLM (Hons) (University of Sydney), PhD (ANU) Key Roles: Director of Centre for Governance of Knowledge & Development, Co-lead on ARC-funded project on Global Energy Governance Research focuses on climate-energy-trade linkages, IP's role in global governance, and regulatory responses to emerging technologies. Notable projects include analyzing China's energy transition pathways and the interplay between TRIPS agreements and climate policy. Publications emphasize ethical dimensions of IP, regulatory frameworks for green finance, and lessons from patent systems for climate negotiations. Collaborates widely with international organizations and governments on policy reforms. Current projects explore how trade regimes can align with climate goals and assess institutional challenges in managing energy transitions globally.

Jason D. Leeمشاهده پروفایل

دانشیار

• Machine Learning Theory
• Deep Learning Foundations
• Optimization
• +۳ مورد دیگر

Jason D. Lee is an Associate Professor in the Department of Electrical Engineering and Computer Sciences and the Department of Statistics at the University of California, Berkeley. Prior to joining Berkeley, he was an Associate Professor at Princeton University and a Research Scientist at Google DeepMind. His academic journey includes a PhD from Stanford University under the supervision of Trevor Hastie and Jonathan Taylor, followed by postdoctoral work at UC Berkeley with Michael Jordan. Dr. Lee's research focuses on the theoretical foundations of artificial intelligence, with particular emphasis on: Machine Learning Theory and Optimization Foundations of Deep Learning Representation Learning Deep Reinforcement Learning Statistical Learning Theory His recent publications reveal a strong focus on understanding the theoretical properties of modern machine learning systems, particularly large language models and deep neural networks. There's a clear trend toward analyzing scaling laws, optimization dynamics, and the theoretical foundations of transformer architectures. His work bridges rigorous mathematical analysis with practical machine learning applications. Dr. Lee has received numerous prestigious awards for his research contributions: Samsung AI Researcher of the Year Award (2023) NSF Career Award (2022) ONR Young Investigator Award (2021) Sloan Research Fellowship in Computer Science (2019) NeurIPS Best Student Paper Award (2016) Finalist for Best Paper Prize for Young Researchers in Continuous Optimization Princeton Commendation for Outstanding Teaching (ECE538B) Dr. Lee actively mentors PhD students and postdoctoral scholars, with a current research group focusing on theoretical aspects of machine learning. His lab, part of the Berkeley Artificial Intelligence Research Lab (BAIR) and the Center for the Theoretical Foundations of Learning, Inference, Information, Intelligence, Mathematics and Microeconomics at Berkeley (CLIMB), receives funding from various sources including NSF, ONR, and industry partnerships. He regularly teaches advanced courses on machine learning theory and optimization. Dr. Lee's research group operates within the Berkeley Artificial Intelligence Research Lab (BAIR) and collaborates closely with researchers across multiple institutions. His team focuses on developing theoretical frameworks to understand modern machine learning systems, with particular emphasis on deep learning and reinforcement learning algorithms.

• Artificial Intelligence
• Data Mining
• Natural Language Processing
• +۵ مورد دیگر

Ee-Peng Lim is a Professor at the School of Information Systems, Singapore Management University. His research spans artificial intelligence, data mining, natural language processing, and computer vision, with applications in healthcare, education, finance, and food computing. He leads projects developing AI systems for behavioral counseling, educational analytics, and multimodal food recognition. Research Interests: Dr. Lim's work focuses on conversational AI for mental health interventions, educational data mining for student performance prediction, food computing for nutrition analysis, and multimodal learning frameworks. His recent projects leverage large language models for complex reasoning tasks and develop robust computer vision systems for real-world applications. Publication Trends: Recent articles (2024-2025) show strong emphasis on multimodal AI systems, large language model applications in behavioral science and healthcare, educational analytics, and advanced food computing techniques. His work increasingly integrates cognitive science principles with deep learning architectures. Leadership: Dr. Lim collaborates extensively with international researchers and has co-organized academic workshops including the International Workshop on Talent and Management Computing (TMC) at KDD.

• Insurance Law
• Fundamental Human Rights
• Contract Law
• +۳ مورد دیگر

María del Val Bolivar Oñoro is a Lecturer and researcher affiliated with the NOVA School of Law at Nova University Lisbon and the Centro de Investigação e Desenvolvimento sobre Direito e Sociedade (CEDIS) . She was born in 1991 in Alcalá de Henares, Spain, and holds a Dual PhD (University of Alcalá – Maynooth University) in Insurance Law and Human Rights. Education: BA in Law (2014, University of Alcalá, Spain) LLM in Torts (2017, Rey Juan Carlos University, Spain) Dual PhD (2021, University of Alcalá and Maynooth University) Her research focuses on Insurance Law , Human Rights , and their intersections with Equality and Discrimination in contractual frameworks. Recent work explores the insurance sector's alignment with the Sustainable Development Goals (ESG) and health rights, particularly for marginalized communities like HIV-positive individuals. Her publications are concentrated in Insurance Law, with a thematic emphasis on sustainability , anti-discrimination , and technological/financial innovation . She actively engages in academic events, including presentations on disability and insurance practices. Scientific Awards: Margarita Salas Postdoctoral Fellow (funded by Spanish Government, NextGenerationEU, and University of Alcala) María del Val Bolivar Oñoro is part of the CEDIS research network , contributing to law-and-society discourse through interdisciplinary collaborations and publications.

• Natural Language Processing
• Biomedical Informatics
• Medical Text Simplification
• +۴ مورد دیگر

Byron C. Wallace is a prominent researcher in Natural Language Processing with a focus on biomedical and clinical applications . His work spans model distillation, factuality evaluation, and medical text simplification. Key contributions include developing methods for tracing teacher models in distillation and creating benchmarks like FactPICO and RedHOT. Research interests include LLM interpretability , medical evidence synthesis , and cross-modal alignment in clinical NLP His recent publications analyze syntactic template repetition in LLMs, token erasure effects , and definition-augmented biomedical NER Wallace's work has advanced zero-shot summarization techniques, pharmacovigilance automation , and patient data privacy analysis in clinical models. Current projects explore chain-of-thought distillation , multilingual medical simplification , and interpretable feature extraction from EHR data. Key collaborators include researchers from institutions like Allen Institute for AI, MIT, and various biomedical NLP teams. His methodological innovations in instance attribution , data augmentation , and counterfactual reasoning have influenced modern NLP research paradigms.