جست‌وجوی استاد و پژوهشگر

Takako Aikawaمشاهده پروفایل

مدرس ارشد

• Technology in language education
• Natural Language Processing (NLP)
• AI in language learning
• +۴ مورد دیگر

Takako Aikawa is a Senior Lecturer in Japanese at the Massachusetts Institute of Technology (MIT), where she leads the Japanese language curriculum and teaches across all proficiency levels. Her research focuses on integrating technology into language education, including virtual reality (VR) for immersive learning and AI-driven error correction in written Japanese. Prior to joining MIT in 2013, she held academic positions in Japan and the U.S., and contributed to Microsoft Research's work in machine translation and NLP. Education includes a PhD and MA from Ohio State University (U.S.) and a BA from Tsuda University (Japan). Her pedagogical interests emphasize corpus-based learning, AI applications in language education, and leveraging VR for kinesthetic learning experiences. She frequently presents at conferences on Japanese language pedagogy and has authored chapters in edited volumes such as ICT×日本語教育 and Digital Resources for Learning Japanese . Her technical work spans statistical machine translation systems, terminology consistency validation, and collaborative translation frameworks. She has pioneered projects like Pecha, an LLM-based language learning tool, and VR child avatars to enhance adult language acquisition. Current initiatives explore AI's role in identifying and correcting common learner errors in writing.

Claudio Silvaمشاهده پروفایل

استاد

• Visualization and Graphics
• Geometric Computing
• Data Science
• +۲ مورد دیگر

Claudio Silva is an Institute Professor of Computer Science and Engineering at NYU Tandon School of Engineering and Professor of Data Science at NYU Center for Data Science. He co-founded the Center for Urban Science and Progress (CUSP) and the Visualization, Imaging and Data Analysis (VIDA) Center. His academic journey includes a BS in mathematics from Universidade Federal do Ceará (1990) and PhD in computer science from SUNY Stony Brook (1996). Co-Director, VIDA Center Former Professor, University of Utah (2003-2011) Technology Consultant, MLB Advanced Media (2012-2017) Research Interests : At the intersection of visualization, geometric computing, and urban/sports analytics, his work includes: AR task guidance systems (ARGUS, HuBar) Urban data analysis (3D visualization, sidewalk mapping) LLM multimodal reasoning (POEM, BDIViz) Biomedical data tools (TopoMap++, T-Explainer) 2023-2025 Research Trends : Recent publications focus on neuroadaptive AR systems (AdaptiveCoPilot), LLM prompt optimization (POEM), explainable AI frameworks (T-Explainer), and urban data visualization (Urban Rhapsody). Collaborations span NYU, Northrop Grumman, and NSF/DARPA grants for projects like OSCUR and PTG. Scientific Honors : ACM Fellow (2024) IEEE Visualization Academy (2019) IEEE Technical Achievement Award (2014) Technology Emmy for Statcast (2018) His lab has developed open-source tools like ARGUS on GitHub and pioneered methods in fNIRS-based cognitive workload analysis for pilot training systems. Current projects include NASA-funded OpenSpace and NSF-backed OSCUR.

Hirokawa Takesمشاهده پروفایل

استاد

• Environmental Law
• Environmental Policy
• Land Use Planning
• +۳ مورد دیگر

Professor Hirokawa Takes is a faculty member at Albany Law School, specializing in environmental and natural resources law, land use planning, property law, and jurisprudence. He joined the institution in 2009 and emphasizes experiential learning, such as community-based projects and fieldwork with students. His research focuses on the intersection of ecology, ethics, economics, and law, particularly in sustainability, ecosystem services, and watershed management. Education: JD and MA from University of Connecticut LLM in Environmental and Natural Resources Law from Lewis & Clark Law School Professor Hirokawa’s scholarship includes editing books like Environmental Law and Contrasting Ideas of Nature (2014) and co-authoring Greening Local Government (2013). His recent work critiques and rethinks sustainability frameworks in the context of climate change, as seen in his co-edited volume Rethinking Sustainability to Meet the Climate Change Challenge (2015). His articles and books engage with legal and scientific communities to address environmental challenges through interdisciplinary approaches. Teaching and advising focus on hands-on learning: students have evaluated real development projects, participated in town hall negotiations, and engaged in ecological field studies. His work aligns with local and national efforts to integrate sustainability into legal and policy frameworks.

Sidney Benderمشاهده پروفایل

پژوهشگر

• Counterfactual Explanations
• Generative Models
• Deep Learning
• +۳ مورد دیگر

Sidney Bender is a Research Scientist at the IDA group of Technical University of Berlin and a doctoral researcher pursuing his PhD there. His work is supported by the BASLEARN collaboration between BASF and the IDA lab, focusing on applying state-of-the-art machine learning to address practical challenges in industry. He holds a B.Sc. (2018) and M.Sc. (2021) in Computer Science from the Karlsruhe Institute of Technology (KIT). His research centers on using deep generative models to create counterfactual explanations, enhancing model robustness against spurious correlations, and understanding neural network decision-making. His research interests include generative models (e.g., Diffusion Models, LLMs, VAEs, Normalizing Flows, GANs), counterfactual explanations, and model robustness. His recent work emphasizes aligning AI systems with human expectations through counterfactual analysis and knowledge distillation. His technical contributions include optimization algorithms like the MaxSat Tabu Search implemented in C++, showcasing his expertise in algorithmic development. While no formal awards are listed, his research bridges foundational AI theory with industrial applications through the BASLEARN initiative.

Lifang Heمشاهده پروفایل

دانشیار

• Machine Learning/Deep Learning
• Tensor Analysis
• Data Mining
• +۳ مورد دیگر

Lifang He is an Associate Professor in the Department of Computer Science & Engineering at Lehigh University. She holds a B.S. in Computational Mathematics from Northwest Normal University and a Ph.D. in Computer Science from South China University of Technology. Prior to joining Lehigh, she was a postdoctoral researcher at the University of Pennsylvania’s Perelman School of Medicine and Weill Cornell Medical College. Her research focuses on machine learning/deep learning, data mining, tensor analysis, and biomedical informatics. Notable projects include developing BiomedGPT, an AI model for real-time patient-focused insights, and contributions to structural brain imaging analysis and rare event prediction in materials science. Her work bridges computational methods with healthcare applications, emphasizing multi-modal data fusion and federated learning in medical contexts. Recent publications span topics like self-paced learning for sign language recognition, graph-based brain network analysis, and efficient large language models. She actively participates in symposiums on AI in healthcare and has collaborated on initiatives like the Mountaintop Campus’ interdisciplinary projects.

Christian Hänigمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۷ مورد دیگر

Prof. Dr. Christian Hänig is a Professor at the Department of Computer Science and Languages and a Temporary Lecturer at the Department of Electrical Engineering, Mechanical Engineering and Industrial Engineering at Anhalt University of Applied Sciences. He advises the Data Science (Full-Time Program) Master of Science degree and teaches courses such as Artificial Intelligence, Data Mining, and Deep Learning. His research focuses on Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Medical Imaging, Multimodal Document Processing, and Data Science. Recent work emphasizes applications in financial domains (e.g., German financial language models and corpus development) and agricultural sector benchmarking. Earlier research includes VR education analytics, unsupervised NLP techniques, and knowledge extraction from unstructured data. Key publications (2024) include developing benchmarks for Ukrainian language models, evaluating agricultural LLMs, and creating financial domain corpora. His contributions span over 20 years, addressing challenges in domain-specific NLP, clinical text mining, and industrial quality analysis. Prof. Hänig’s academic service includes roles as a degree program advisor and committee member. Office hours are Thursdays 4:30–6:00 PM (by appointment) at the Ratke Building, Room 23-114, Köthen campus.

Michael Kirkpatrickمشاهده پروفایل

استاد

• Computing & Professional Ethics
• Information Security & Privacy
• CS Education & Pedagogy
• +۱ مورد دیگر

Michael Kirkpatrick is a Professor of Computer Science at James Madison University (JMU), part of the College of Integrated Science & Engineering. He holds a Ph.D. from Purdue University (2011), M.S. from Michigan State University (2007), and B.A. from Indiana University (2001). His academic journey includes roles as Assistant Professor (2011–2017) and Associate Professor (2017–2024) before his current professorship. Kirkpatrick's research focuses on computing ethics, information security, CS education pedagogy, and computer systems. He teaches courses such as Computer Systems I-II, Societal and Ethical Issues in Computing, and Operating Systems. His scholarly work emphasizes integrating ethics into computing education, modern web development pedagogy, and security challenges in genetic data. Recent publications (2024) explore AI's impact on research ethics and transparent classroom practices. He has contributed to ACM ethics guidelines and pioneered interactive educational tools like OpenCSF. While no explicit awards are listed, his extensive contributions to curriculum design and ethics education highlight his academic influence. Kirkpatrick's teaching philosophy prioritizes active learning and interdisciplinary ethics integration. His courses use team-based learning and readiness assurance processes, with a focus on preparing students for professional conduct challenges. Though specific grants or labs aren't detailed, his work reflects a commitment to advancing both technical and ethical dimensions of computer science education.

George Dellisمشاهده پروفایل

استاد

• Public Law
• European Union Law
• Administrative Law
• +۵ مورد دیگر

George Dellis is a Professor of Public Law at the Athens Law Faculty, University of Athens, and Head of its LLM programs in Public Law. He concurrently serves as founding managing partner of 'Dellis and Partners' law firm and practices before the Supreme National and European Courts. His academic career spans teaching at institutions including Sciences-Po Paris and the University of Michigan Law School. Education: Graduated from Athens Law Faculty (1988), followed postgraduate studies at Université Paris II (France), and earned a PhD (1994) on administrative/criminal law intersections in sanctions. He taught at the European Institute of Public Administration (1994) and served as Référendaire at the European Court of Justice (1996-2000). Research focuses on public law domains including EU law, administrative sanctions, regulatory frameworks, and climate policy. His work bridges theoretical analysis with practical legal challenges, emphasizing institutional efficiency and legal modernization. Notable contributions explore Greek legal evolution, EU regulatory impacts, and economic analysis of public law systems. Awards: PhD awarded 'Very Honorable with Congratulations from the Jury' Professional Roles: Athens Bar Association member, legal advisor to European Courts Key Expertise: Climate change policy, independent regulators, administrative justice efficiency His publications span monographs and articles in Greek, English, and French, addressing topics from environmental law to EU federalization dynamics. Combines academic rigor with hands-on legal practice, influencing both scholarly discourse and practical legal strategy in Greece and beyond.

Aidong Zhangمشاهده پروفایل

استاد

• Bioinformatics
• Data Mining
• Multimedia Database Systems
• +۳ مورد دیگر

Aidong Zhang is a SUNY Distinguished Professor Emerita in the Department of Computer Science and Engineering at the University of Virginia. She served as Department Chair from 2009 to 2015. Her primary affiliations include the School of Engineering and Applied Sciences. Dr. Zhang's research focuses on Bioinformatics, Data Mining, and Multimedia Database Systems, with recent work emphasizing robust AI systems, healthcare applications, and interdisciplinary machine learning techniques. Education: PhD in Computer Science from Purdue University (1994). Her academic contributions have been recognized through prestigious awards including IEEE Fellow (202?), CSE Faculty Distinguished Teacher Award (2004), and NSF CAREER Award (1998). Research interests span causal inference, algorithmic fairness, biomedical data analysis, and federated learning. Notable projects include improving group robustness in AI models, developing explainable neural architectures for healthcare, and advancing multimodal data integration. Her work consistently bridges theoretical computer science with practical biomedical and clinical applications. Key awards and honors include: IEEE Fellow UB Exceptional Scholar-Sustained Achievement Award (2003) SUNY Chancellor's Research Recognition Award (2002) NSF CAREER Award (1998) Her recent publications (2023-2025) highlight advancements in spurious bias mitigation, interpretability of large language models, and federated learning frameworks. Collaborative work with medical researchers has produced innovations in Alzheimer’s risk prediction and clinical decision support systems.

• Criminal Law
• Drug Policy and Legislation
• Sentencing Reform
• +۳ مورد دیگر

Nicholas Burgess is a Lecturer in Law at the School of Business and Creative Industries, University of the West of Scotland. He holds an LLB (Hons) from the University of Aberdeen and an LLM (by Research) from the University of Glasgow. Previously, he taught at the University of Glasgow and worked at the Scottish Law Commission on projects like the Mental Element in Homicide and Damages for Personal Injury. He is a member of the Criminal Law Reform Now Network and Drugs Research Network Scotland. His research focuses on criminal law theory, drug policy, sentencing reform, and public health intersections with legal systems. Current projects include a PhD on 19th-21st century British drug law evolution and contributions to the Criminal Law Reform Now Network's drug sentencing reform initiative. Teaching spans Criminal Law, Advanced Criminal Law, Media Law, and International Criminal Law. His work aligns with UN SDG goals related to justice and health. Recent publications address stalking sentencing in Scotland, new psychoactive substances legal frameworks, and homicide law dynamics. Collaborations include the Scottish Sentencing Council on sexual offenses and stalking literature reviews. His memberships emphasize advancing criminal law reform and drug policy innovation.

Jeffrey Bauerمشاهده پروفایل

استاد مدعو

• Corporate Law
• Compliance
• Business and Corporate Law
• +۱ مورد دیگر

Jeffrey Bauer is an Adjunct Faculty member at the University of St. Thomas School of Law, concurrently serving as Partner & Founder of BLG PLLC. He holds a JD from Stetson University College of Law, an LLM from Georgetown University Law Center, and advanced degrees (MS and BS) from the University of Central Florida. His professional expertise aligns with corporate law and compliance disciplines. As of Summer and Fall 2025, he is not scheduled to teach courses. Bauer’s affiliation with the law school emphasizes practical legal education through adjunct contributions. Education: Stetson University College of Law – Juris Doctor (JD) Georgetown University Law Center – Master of Laws (LLM) University of Central Florida – Master of Science (MS) and Bachelor of Science (BS) His professional work with BLG PLLC likely informs his academic contributions, though specific research or advising activities are not detailed in the provided text. No academic awards or grants are explicitly mentioned.

Martin Chapmanمشاهده پروفایل

مدرس

• Health Informatics
• Healthcare Technology
• Data Science in Healthcare
• +۳ مورد دیگر

Martin Chapman is a Lecturer in Health Informatics at Population Health Sciences, focusing on healthcare technology, data-driven decision support systems, and phenotype library development. His work integrates computational methods with clinical practice to improve patient care and healthcare outcomes. He has contributed to projects involving stroke survivor self-management portals, phenotype standardization, and AI ethics in healthcare. Research Interests: Health Informatics Patient-Centered Digital Tools Computable Phenotyping Healthcare Data Standards Non-repudiation in AI Recent Research Trends: Recent work emphasizes phenotype library development (e.g., Health Data Research UK Phenotype Library), digital health portal design for stroke survivors, and ethical AI applications in healthcare. His publications often address cross-disciplinary challenges in integrating clinical data with computational methods. Awards: Best Paper Award at ICHI 2024 for co-designing a user-centered digital portal for stroke survivors. Grants & Projects (2022–2026): Developing AI solutions for pediatric health interventions (HDR UK) Phenomics and Prognostic Atlas (HDR UK) Improving stroke survivor outcomes using data-driven approaches (NIHR) Labs/Teams: Collaborates with multidisciplinary teams including HDR UK, Stroke Association, and NHS-funded initiatives focusing on healthcare innovation and data-driven solutions.

Michal Valkoمشاهده پروفایل

پژوهشگر

• Reinforcement Learning
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Roles & Affiliations: Michal Valko is the Chief Models Officer at a stealth startup, a tenured researcher at Inria (Inria Lille - Nord Europe), and a lecturer in the MVA Master program at École Normale Supérieure Paris-Saclay. He previously held roles including Principal Llama Engineer at Meta and Senior Staff Research Scientist at Google DeepMind. Education: Ph.D. in Machine Learning from the University of Pittsburgh (2011), Habilitation à Diriger des Recherches (HdR) from École Normale Supérieure Paris-Saclay (2016). Research Interests: Michal focuses on minimizing human supervision in AI systems, including deep reinforcement learning, bandit algorithms, self-supervised learning, and large language models (LLMs). His work emphasizes scalable test-time inference, fine-tuning, and alignment of LLMs. He also explores theoretical foundations of reinforcement learning and representation learning. Awards: Recipient of the Outstanding Paper Award at ICML 2023, Inria's Prime d'Excellence Scientifique (2014–2017 and 2018–2021), Homer Warner Best Paper Award (2010), and Google Best Paper Award (2010). Advising & Grants: Advised over 20 PhD and postdoctoral students, including notable alumni like Daniele Calandriello and Jean Tarbouriech. His research has been supported by grants from ANR (Extra-Learn, BOLD), Intel, and collaborative projects like EduBand with Carnegie Mellon. Labs & Teams: Co-founder of the SequeL team at Inria and a key contributor to the DeepMind Paris and Meta GenAI research groups. Active in organizing conferences like ICML, NeurIPS, and workshops on Graphs in Machine Learning.

Guo Yikeمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Data Science
• +۶ مورد دیگر

Guo Yike is the Provost of The Hong Kong University of Science and Technology (HKUST) and concurrently a Chair Professor in the Department of Computer Science and Engineering. He holds a PhD in Computational Logic from Imperial College London (1994) and a first-class honours degree in Computing Science from Tsinghua University (1985). His academic leadership roles include Director of the Data Science Institute at Imperial College London (2014–2020), Honorary Dean of Shanghai University's School of Computer Science (since 2020), and Vice President (Research and Development) at Hong Kong Baptist University (2020–2022). Research interests focus on machine learning, data mining, and large-scale applications in healthcare, finance, and environmental science. He pioneered informatics systems for biology, geophysics, and social media, emphasizing ethical AI and multimodal reasoning. Notable awards include Royal Academy of Engineering Fellowship (2018), ACM SIGMM Best Open Source Software Award (2017), and recognition as one of China's Top 10 Data Scientists (2016). Industry collaborations include leading startups like InforSense and TranSMART, working with GSK, Huawei, and BBC. Editorial roles include editor-in-chief of Annual Reviews of Data Sciences and deputy editor-in-chief of Machine Intelligence Research . His work bridges academia and industry, driving innovation in AI ethics, cloud computing, and interdisciplinary science.

Qiang Xuمشاهده پروفایل

مدرس ارشد

• Creep Damage Mechanics
• Computational Modeling
• Machine Learning
• +۵ مورد دیگر

Dr. Qiang Xu is a Senior Lecturer in Mechanical Engineering at the School of Computing and Engineering, University of Huddersfield. He is affiliated with the Centre for Precision Technologies and the Centre for Thermofluids, Energy Systems, and High-Performance Computing. Dr. Xu holds a PhD from the University of Birmingham (1997) and has extensive experience in creep damage mechanics, computational modeling, and machine learning applications. His research focuses on material degradation, software development, and interdisciplinary applications in engineering and education. Key research interests include creep cavitation modeling, multiaxial creep damage constitutive equations, and the integration of AI in teaching and learning. He has authored over 100 publications, including edited books and peer-reviewed articles in top journals. Dr. Xu has supervised 9 PhD students as main supervisor and actively contributes to the academic community through conference organization, grant reviews, and journal editing roles. Notable recognitions include top author status for influential papers in creep damage mechanics and over 42,000 reads on ResearchGate. His work aligns with UN Sustainable Development Goals related to innovation and sustainable industrialization. Professional activities include editorial roles for Science Progress and involvement in conferences like the International European Collaborative Creep Committee Conference. His contributions span industry collaborations with EPSRC, HSE, and EC-funded projects, emphasizing practical applications of theoretical research.