جست‌وجوی استاد و پژوهشگر

Kevin D. Ashleyمشاهده پروفایل

استاد

• Computational Social Science
• Artificial Intelligence
• Algorithms
• +۷ مورد دیگر

Kevin D. Ashley is a Professor of Law at the University of Pittsburgh School of Law. He is also a senior scientist at the Learning Research and Development Center and an adjunct professor of computer science at the University of Pittsburgh. His interdisciplinary work bridges artificial intelligence, legal analytics, and ethical reasoning. JD, Harvard Law School M.A. and PhD, University of Massachusetts BA, Princeton University His research focuses on computational modeling of legal reasoning , AI and ethics , legal text analytics , and case-based reasoning . He has pioneered AI applications for legal decision support, automated argumentation, and bias detection in legal corpora. Recent publications include studies on large language models in legal annotation, argument mining, and empirical legal analysis. His work has been supported by multiple National Science Foundation grants, emphasizing fairness in AI and access to justice. 2022 Codex Prize for Computational Law 2015 University of Massachusetts Outstanding Achievement Award 2002 AAAI Fellow for AI in Law contributions 2000 Chancellor’s Distinguished Research Award A former President of the International Association for Artificial Intelligence and Law, Ashley has held visiting roles at the University of Bologna, Stanford CodeX, and IBM Watson Research Center. He co-edits the journal Artificial Intelligence and Law and teaches courses on applied legal analytics.

• Distributed Computing
• Wireless Networks
• Distributed Systems
• +۴ مورد دیگر

Prof. Roger Wattenhofer is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland, and Deputy head of the Computer Engineering and Networks Lab. He holds a doctorate in Computer Science from ETH Zurich (1998) and has held positions at Brown University and Microsoft Research before returning to ETH. His research focuses on distributed computing, wireless networks, and algorithmic systems design, with contributions to Byzantine agreement protocols, blockchain technologies, and neural network architectures. He teaches courses such as Distributed Systems and Computational Thinking. Education: Ph.D. in Computer Science (ETH Zurich, 1998). Research interests include distributed systems, network algorithms, and the intersection of machine learning with distributed computing. His work spans both theoretical foundations and practical implementations, addressing challenges in fault tolerance, consensus mechanisms, and algorithmic efficiency. Recent publications explore topics like adversarial robustness in voting systems, privacy in reinforcement learning, and generative music models. He actively contributes to open-source frameworks and benchmarks for neural algorithmic reasoning.

• Nanoelectronic devices
• Integrated circuits
• AI hardware
• +۵ مورد دیگر

Haitong Li is an Assistant Professor in the School of Electrical and Computer Engineering at Purdue University's College of Engineering, joining the faculty in 2022. His research bridges nanoelectronic devices, integrated circuits, and nanotechnology-inspired AI hardware to address critical challenges in energy-efficient artificial intelligence systems. Education: Ph.D. in Electrical Engineering, Stanford University Research Interests: Dr. Li pioneers emerging memory technologies—particularly Resistive RAM (RRAM)—for in-memory computing and neuromorphic systems. His work focuses on 3D monolithic integration of RRAM and gain cell memory with CMOS to enable edge AI, with recent breakthroughs in hardware acceleration for large language models and sustainable computing. Key innovations include carbon footprint prediction for LLMs and zeroth-order fine-tuning techniques. Publication Trends: Dr. Li's 2023-2025 publications reveal a strategic shift toward sustainable AI hardware, emphasizing carbon-aware LLM inference and edge deployment. His research consistently targets data movement reduction through memory-centric architectures, spanning photonic accelerators, neuro-symbolic computing, and heterogeneous 3D integration. Awards: No scientific awards were documented in the provided sources. Advising and Grants: Current advisees and grant funding details were not specified in the available materials. Labs and Teams: Research group composition and laboratory facilities were not described in the source text.

Karthik R. Narasimhanمشاهده پروفایل

استاد

• Language Agents
• Reinforcement Learning
• Natural Language Processing
• +۳ مورد دیگر

Karthik R. Narasimhan is a Professor at Princeton University's School of Engineering and Applied Science in the Department of Computer Science. Previously, he earned his PhD from MIT under Regina Barzilay and served as a visiting research scientist at OpenAI during 2017-18. His research focuses on the intersection of language and decision-making, building autonomous agents that learn from both experience and human knowledge. His research spans multiple high-impact areas including language agents (Text-DQN, CALM, ReAct, Tree of Thoughts), reinforcement learning (h-DQN, Multi-Objective RL), and AI safety (Toxicity in ChatGPT, DataMUX). He has developed critical datasets and benchmarks such as WebShop, InterCode, SWE-bench, and SILG that have become standard evaluation tools in the field. Current work emphasizes agent capabilities, software engineering automation, and multimodal interaction. His publication trends show strong focus on practical agent deployment (SWE-agent, Tree of Thoughts), safety evaluation (Probing AI Safety), and efficiency improvements (DataMUX). Recent work increasingly addresses real-world challenges in software engineering, security, and human-AI collaboration through rigorous benchmarking. Co-author of foundational GPT (2018) paper Key developer of Text-DQN (2015), CALM (2020), ReAct (2022), Tree of Thoughts (2023) Creator of influential benchmarks: WebShop (2022), SWE-bench (2023), InterCode (2023) He actively advises students through Princeton's computer science program, with research supported by multiple grants focused on autonomous agent development and language-based decision systems. His GitHub repositories (nlp-datasets, text-world-player) demonstrate strong community engagement in open-source research tools. Current projects include advancing language agent capabilities through Reflexion (2023) and Tree of Thoughts (2023) frameworks while addressing critical safety and efficiency challenges.

Nathan Martinمشاهده پروفایل

دانشیار

• History of Music Theory
• Musical Form Analysis
• Jean-Philippe Rameau Studies
• +۳ مورد دیگر

Nathan Martin is an Associate Professor of Music Theory at the University of Michigan, School of Music, Theatre & Dance. He joined in 2015 after postdoctoral fellowships at Columbia, Harvard, Katholieke Universiteit Leuven, Hochschule für Musik Freiburg, and Yale. He holds a PhD from McGill University’s Schulich School of Music (2009). His research focuses on the history of music theory and musical form analysis, particularly the works of Jean-Philippe Rameau and their reception among Enlightenment thinkers like Jean-Jacques Rousseau. He integrates intellectual history with practical analytical methods, emphasizing both contextual and emic perspectives. Recent interests include adapting empirical social science and linguistics methods to study musical form. Key publications include articles on Rameau’s harmonic concepts, Rousseau’s musical writings, and global music theory history. His 2014 article on Rameau’s supposition/suspension theories earned the Society for Music Theory’s Outstanding Publication Award. He co-edited Formal Functions in Perspective (2015) and served as co-editor of Music Theory & Analysis until 2019. Professional highlights include the Edward T. Cone Membership at the Institute for Advanced Study (2018–2019) and a 2023 visiting researcher role at the Max Planck Institute for Empirical Aesthetics. His work bridges historical analysis with contemporary empirical approaches, fostering interdisciplinary dialogue in music theory.

Carlos G. Leviمشاهده پروفایل

استاد پژوهشی

• Structural Materials
• Thermal Barrier Coatings
• Ceramic Matrix Composites
• +۳ مورد دیگر

Carlos G. Levi is a Research Professor in the Department of Materials at the University of California, Santa Barbara (UCSB), part of the College of Engineering. He holds the additional title of Professor Emeritus. His research focuses on microstructure evolution in inorganic materials, particularly in the design of advanced coatings, composites, and alloys for extreme environments. He has contributed significantly to thermal barrier coatings, ceramic matrix composites, and high-temperature alloys for aerospace and energy applications. Education: Ph.D. in Metallurgical Engineering, University of Illinois at Urbana-Champaign (1981) M.Sc. in Metallurgical Engineering, University of Illinois at Urbana-Champaign (1977) Degree in Chemical Engineering, Universidad Autonoma de Nuevo Leon, Mexico (1972) Research Interests: Levi’s work addresses challenges in structural materials, including advanced thermal/environmental barrier coatings resistant to molten silicates, ceramic matrix composites, hypersonic materials, and high-temperature alloys such as multi-principal element alloys. His studies explore degradation mechanisms, phase stability under extreme conditions, and novel synthesis techniques like vapor-mediated melt infiltration. Awards and Honors: 2014 TMS Morris Cohen Award 2012 Fellow of the American Ceramic Society 2008 NIMS Award (shared) for breakthroughs in materials science for energy/environment 2004 DLR Wissenschaftspreis (collaborative paper) 2002 Alexander von Humboldt Research Prize Advising and Grants: No formal student advisees are listed, though his research group likely includes graduate students/postdocs. Grant details are not specified in the provided texts. Labs/Teams: Levi’s research is conducted within UCSB’s Materials Department, leveraging advanced characterization tools (e.g., TriBeam tomography) and computational modeling to study material behavior under extreme conditions.

• 3D Scene Understanding
• Natural Language Processing
• Embodied AI
• +۳ مورد دیگر

Angel Xuan Chang is an Associate Professor at Simon Fraser University's School of Computing Science, affiliated with labs including 3DLG, GrUVi, SFU NatLang, SFU AI/ML, and VINCI. He holds a Canada CIFAR AI Chair and was a TUM-IAS Hans Fischer Fellow (2018-2022). His research bridges natural language processing (NLP), 3D scene understanding, and embodied AI, focusing on language-grounded 3D generation and biodiversity monitoring via DNA barcodes. Recent work includes NuiScene (unbounded outdoor scene generation), ViGiL3D (3D visual grounding dataset), and CLIBD (vision-genomics biodiversity analysis). He advises students in projects like BIOSCAN-5M insect dataset and embodied AI navigation. His 2025 highlights include multiple ICCV and ICLR papers, workshops at ICML and CVPR, and a CRV invited talk. Education: Ph.D. in Computer Science from Stanford University (2014), advised by Chris Manning. Previous roles include visiting research scientist at Facebook AI Research and researcher at Eloquent Labs.

• Environmental Assessment
• Waste Management Systems
• Life Cycle Assessment (LCA)
• +۳ مورد دیگر

Anders Damgaard is an Associate Professor and Head of BSc studies at the Department of Environmental and Resource Engineering (DTU Sustain), Technical University of Denmark. His research focuses on environmental assessment methodologies, particularly Life Cycle Assessment (LCA), and their application to waste management systems, resource recovery, and policy development. He leads the development of LCA models like EASEWASTE/EASETECH and collaborates with institutions such as the Danish EPA and Nordic Council of Ministers. Key research areas include carbon footprints of waste treatment, textile waste composition, and additive impacts in plastics recycling. Education: Not explicitly stated in provided texts. Research Interests: Waste management optimization, circular economy frameworks, sustainable technologies, and policy-driven environmental assessments. His recent publications address topics such as carbon footprints of sewage sludge treatments, Nordic textile waste composition, and challenges in plastic additive inclusion in LCA studies. He supervises PhD students in projects involving lifecycle modeling, construction waste recycling, and consumer practices in circular economies. As part of DTU Sustain, he contributes to interdisciplinary teams advancing sustainable resource management and policy solutions.

• Digital Archaeology
• Computational Archaeology
• Machine Learning in Archaeology
• +۱۳ مورد دیگر

Karsten Lambers is Professor of Digital and Computational Archaeology at the Faculty of Archaeology, Leiden University, where he leads research and teaching in the application of computational methods to archaeological data. His work integrates machine learning, remote sensing, text mining, and citizen science to advance archaeological prospection and heritage management. He is affiliated with the Department of Archaeological Sciences and plays key roles in research groups and university-wide initiatives such as SAILS and ARCHON. His research interests span Digital Archaeology , Machine Learning in Archaeology , Remote Sensing , Geoarchaeology , and Human-Environment Interaction . He investigates how computational tools can extract meaningful archaeological information from large datasets, including LiDAR imagery and excavation reports. His fieldwork spans Central Europe and Latin America, with a focus on prehistoric landscapes and cultural heritage. The analysis of his recent publications reveals a strong trend toward automated detection using deep learning (e.g., R-CNN, WODAN), named entity recognition in archaeological texts (e.g., ArcheoBERTje), and citizen science integration for data validation. His work bridges archaeology with computer science, geomatics, and environmental science, emphasizing interdisciplinary collaboration and methodological rigor. His scientific awards include: Best Thesis Award (University of Zurich, 2005) EUROPA NOSTRA Award (2020, 2022) Membership in the German Archaeological Institute (since 2022) Lambers actively supervises students and leads major research projects such as ABMA, EXALT, and Heritage Quest. He has secured substantial research funding and collaborates widely with computer scientists, geophysicists, and palaeoecologists. His teaching includes digital methods, modeling, and simulation, often linked to ongoing research. He has also contributed to open educational resources and digital textbooks in archaeology. He leads or participates in several research labs and teams, including the Digital Archaeology Research Group (which he chairs), the Heritage Quest citizen science project, and interdisciplinary teams focusing on alpine terraces and Iraqi prospection. His work emphasizes the integration of digital tools into practical archaeological workflows, advocating for complementary human-computer strategies.

Megan Callowمشاهده پروفایل

استاد آموزشی

• Writing in the Disciplines
• Science Writing
• Rhetoric and Composition
• +۲ مورد دیگر

Megan Callow serves as an Associate Teaching Professor in the Department of English at the University of Washington, Seattle, and holds the position of Director of Writing for the campus. Since 2019, she has directed the Program for Writing Across Campus (PWAC), advancing writing instruction across academic disciplines. Her educational background includes: Bachelor of Arts in English from University of California, Berkeley (2003) Master of Arts in Liberal Arts from St. John's College (2006) Doctor of Philosophy in English Education from University of Maryland (2015) Dr. Callow specializes in Writing in the Disciplines (WID) and science writing, with deep expertise in rhetoric and composition, writing pedagogy, and faculty development for writing instruction. Her research examines how writing is taught and learned across scientific and technical fields, develops cross-disciplinary writing curricula, and explores online learning environments for writing education. She investigates genre theory, interdisciplinary writing practices, and science/technology writing integration. No scientific awards were documented in the source material. Information regarding graduate student advising or research grants was not provided in the available text. No dedicated research labs or collaborative teams were mentioned in the source documentation.

İBRAHİM DAĞILMAمشاهده پروفایل

مدرس

• Zaza Language and Literature
• Comparative Literature
• Folklore Studies
• +۳ مورد دیگر

İbrahim Dağılma is a Lecturer in Zaza Language and Literature at Bingöl University's Faculty of Arts and Sciences since 2013. He holds a Master's (2017) and PhD (2021) in Zaza Language and Literature from Bingöl University's Living Languages Institute. He previously served as a Turkish Language teacher in the Ministry of National Education and authored/co-authored Zazaki textbooks for grades 5-8 published by MEB between 2018-2019. He currently chairs the Zaza Language and Literature department and teaches courses like Modern Zaza Literature and Comparative Literary Analysis. Education: Bachelor's in Turkish Education, Dicle University (1997) Uncompleted Journalism studies at Istanbul University (2010) Master's and PhD in Zaza Studies (2017-2021) Research focuses on Zaza language preservation, modern literary movements, folklore documentation, and comparative studies between Zaza and other languages. He has published 11 books including 'Edebiyato Modern ê Zazaki' and 'Süleyman Hilmi Tunahan', and frequently presents at international conferences on topics like Zaza cultural identity and migration narratives. His recent academic work explores linguistic comparisons between Zaza and Farsi, analysis of traditional Zaza texts, and the role of folklore in educational materials. He has advised 18 undergraduate theses and participated in numerous thesis juries. His research has been published in refereed journals like Bingöl Araştırmalar Dergisi and The Journal of Mesopotamian Studies.

Reza Shokriمشاهده پروفایل

دانشیار

• Data Privacy
• Trustworthy Machine Learning
• Security
• +۷ مورد دیگر

Reza Shokri is a Dean's Chair Associate Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. His research lies at the intersection of data privacy, security, and trustworthy machine learning, with a focus on quantifying privacy risks and developing robust, fair, and interpretable models. PhD in Computer Science, EPFL His research interests center on data privacy and trustworthy machine learning , particularly in the context of deep learning and federated systems. He investigates how machine learning models memorize training data, leading to privacy leakage, and designs frameworks to audit and mitigate such risks. His work bridges theoretical guarantees with practical applications, emphasizing the trade-offs among privacy, fairness, robustness, and utility. His recent publications (2023–2025) reveal a strong trend in analyzing privacy in large language models (LLMs), membership inference attacks, federated learning, and fairness. These works are published in top venues such as NeurIPS, ICML, ICLR, CCS, and FAccT, highlighting his leadership in both AI and security communities. Notable scientific awards include: Asian Young Scientist Fellowship (2023) Intel Outstanding Researcher Award (2023) Best Paper Award, ACM FAccT (2023) IEEE S&P Test-of-Time Award (2021) Caspar Bowden Award for Privacy Enhancing Technologies (2018) NUS Presidential Young Professorship (2019–2023) VMware Early Career Faculty Award (2021) He has advised numerous PhD and Master’s students, many of whom have contributed to high-impact publications. He has also received research grants from major industry partners including Meta, Google, Intel, and VMware. He leads the Data Privacy and Trustworthy Machine Learning Lab at NUS and has served on program committees for top conferences such as IEEE S&P, ACM CCS, and FAccT, including co-chairing roles at HotPETs and Shadow PC of IEEE S&P. He has delivered tutorials at ICML and CCS on privacy auditing in machine learning. His lab focuses on developing tools and frameworks—such as the ML Privacy Meter—for assessing and improving the privacy properties of machine learning models, with applications in regulatory compliance and secure AI deployment.

Helen Abbottمشاهده پروفایل

استاد

• French Literature
• Musicology
• Digital Humanities
• +۶ مورد دیگر

Professor Helen Abbott is a Professor of Modern Languages at the University of Birmingham, serving as Pro-Vice-Chancellor and Head of the College of Arts and Law. Her research focuses on the intersection of French poetry, music, and digital methods, particularly the work of Baudelaire. She has led major grants, including the AHRC-funded Baudelaire Song Project (2015-2019), exploring musical adaptations of Baudelaire's poetry. Abbott holds a BA from Cambridge, MA and PhD from King’s College London. She has supervised numerous PhD students and authored books such as Baudelaire in Song: 1880-1930 (2017). Awards include AHRC Standard Grant (£594,000) and an Early Career Fellowship. Her work bridges academia and practice, collaborating with musicians and digital researchers. She advises on doctoral programs and cultural initiatives, emphasizing interdisciplinary and public engagement.

Martin Kernمشاهده پروفایل

استاد

• Ancient Chinese Literature
• Philology
• Early Chinese Poetry
• +۷ مورد دیگر

Martin Kern is the Joanna and Greg Zeluck ’84 P13 P18 Professor in Asian Studies at Princeton University. He specializes in ancient Chinese literature, philology, and textual studies, with a focus on poetry, ritual, and cultural memory. Kern co-edits T'oung Pao and directs the "International Center for the Study of Ancient Text Cultures" at Renmin University, Beijing. Education: Ph.D. in Sinology, Cologne University M.A. in Sinology, Cologne University His research spans early Chinese rhetoric, authorship debates, manuscript analysis, and the intersection of writing/orality. He has led Princeton's "Comparative Antiquity" initiative (2018–2022) and co-directs the Princeton-Venice Summer School in Classical Chinese. Recent publications include studies on the Classic of Poetry , Chuci , and Zuozhuan , emphasizing newly discovered manuscripts and their impact on understanding ancient Chinese textuality. His work often bridges philological rigor with comparative theoretical frameworks. Scientific Awards: Member of the American Philosophical Society President of the American Oriental Society (2023–2024) Kern's editorial roles include co-editing the monograph series Studies in the History of Chinese Texts and the Handbook of Oriental Studies: Section 4 China . He has held leadership positions in major academic initiatives on ancient China.

Justin Russell Greeneمشاهده پروفایل

مدرس ارشد

• Cinema Studies
• Media Studies
• Cultural Studies
• +۴ مورد دیگر

Justin Russell Greene serves as an Advanced Instructor in the Department of English within Virginia Tech's College of Liberal Arts and Human Sciences. With over 15 years of teaching experience across multiple institutions, he currently teaches courses in film, literature, and writing at Virginia Tech, where he has been employed since 2019. His academic journey spans various teaching positions at Virginia Tech, Hampden-Sydney College, Virginia Commonwealth University, and several community colleges. Greene earned his BA, MA, and PhD in English and Media, Art, and Text from Virginia Commonwealth University. His educational background reflects his interdisciplinary approach that bridges traditional literary studies with contemporary media and cultural analysis. He has also completed professional development certifications in Anti-Racist Teaching and Foundations of Online Teaching at Virginia Tech. His research focuses on the intersections of cinema, media, and cultural studies, with particular attention to authorship, celebrity, and gender performance. Greene examines how authors and celebrities construct their identities across various media platforms, exploring topics ranging from Quentin Tarantino's cinematic masculinity to Roxane Gay's digital presence. His work often analyzes the performative aspects of identity in contemporary culture, particularly through fashion, social media, and visual storytelling. Greene's scholarly output demonstrates a consistent focus on authorial identity construction across media platforms. His publications reveal a trajectory from examining literary authors' fashion choices to analyzing digital performances of identity on social media, and more recently to cinematic studies of directors like Quentin Tarantino and Jordan Peele. The evolution of his work reflects broader cultural shifts toward digital and visual media while maintaining a consistent theoretical framework centered on performance and identity construction. Joyce Gentry Smoot Award (2025) for Excellence in Teaching by an Instructor As an educator, Greene has served as a reader on graduate student capstones and has been actively involved in curriculum development and pedagogical innovation. He has participated in numerous professional development activities focused on writing instruction, anti-racist pedagogy, and the integration of AI in teaching. His teaching philosophy emphasizes building student confidence in writing abilities, recognizing diverse student backgrounds, and providing individualized feedback to help students develop their unique voices. Greene is currently working on projects examining Jordan Peele's Nope (2022) regarding point-of-view and gore, as well as speculative adaptations in contemporary US media. His research interests continue to evolve with cultural trends while maintaining his core focus on performance, identity, and media representation.