جست‌وجوی استاد و پژوهشگر

Roberto Martin-Martinمشاهده پروفایل

استادیار

• Robotics
• Computer Vision
• Machine Learning
• +۷ مورد دیگر

Roberto Martin-Martin is an Assistant Professor of Computer Science at the University of Texas at Austin, where he leads the Robot Interactive Intelligence (RobIN) Lab. His research bridges robotics, computer vision, and machine learning to enable robots to operate autonomously in human-centric environments like homes and offices. Previously, he was a Postdoctoral Scholar at the Stanford Vision and Learning Lab working with Fei-Fei Li and Silvio Savarese, and an AI Researcher at Salesforce AI. Education: Ph.D. and M.Sc. in Robotics from Technische Universität Berlin (TUB), advised by Professor Oliver Brock B.Sc. from Universidad Politécnica de Madrid Dr. Martin-Martin's research focuses on developing AI algorithms that combine reinforcement learning and imitation learning with advanced planning and control to address core challenges in robot perception. His work spans mobile and whole-body manipulation, dexterous and contact-rich interactions, and long-horizon tasks in unstructured environments. He takes inspiration from human cognition through psychology and cognitive science to develop solutions for skills ranging from simple pick-and-place operations to complex tasks like cooking and furniture assembly. His recent publications demonstrate a strong trend toward enabling robots to learn from human demonstrations, particularly through video, and to safely adapt these demonstrations to their own morphology. There's significant emphasis on mobile manipulation, bimanual tasks, and developing hardware that supports robust robot learning through trial and error. His work shows increasing integration of large language models and vision-language models to enhance robot understanding and task execution. Scientific Awards: RSS Pioneer (2020) Winner of Amazon Picking Challenge (2015) RSS Best Systems Paper Award (2016) ICRA Best Paper Award IROS Best Mechanism Award Amazon Faculty Award AAAI Young Faculty IJCAI Early Faculty Nominated for Best Paper at IROS (2014, 2017) Dr. Martin-Martin advises PhD students including Arpit Bahety, who is working on mobile manipulation and learning. He serves as Chair of the IEEE Technical Committee on Mobile Manipulation and is a co-founder of QueerInRobotics. His research is supported by industry partnerships and academic funding sources that enable his lab to develop both hardware and software innovations in robotics. He directs the Robot Interactive Intelligence (RobIN) Lab at UT Austin, which takes a holistic approach to robot intelligence, developing both the hardware (like the BaRiFlex gripper) and software frameworks necessary for robots to learn from interaction. The lab's research addresses the full pipeline from perception to action, with particular emphasis on learning from human demonstrations, safe exploration, and adapting to novel objects and environments.

Pranav Anandمشاهده پروفایل

استاد

• Semantics
• Pragmatics
• Syntax-Semantics Interface
• +۵ مورد دیگر

Pranav Anand is a Professor in the Department of Linguistics at the University of California, Santa Cruz (UCSC). He currently serves as the Faculty Director of the Humanities Institute at UCSC since July 2023. His research focuses on the interplay between context, interpretation, and grammatical perspective, particularly in areas like de re/de se contrasts, evaluative predication, and indexical shift. He has contributed to studies on narrative structures, evidential restrictions, and the syntax-semantics interface in sluicing. Dr. Anand has taught a variety of courses including Ling 119: Narratives , Ling 231: Semantics A , and special topics like Invented Languages: From Elvish to Esperanto . His work bridges theoretical linguistics with computational methods, evidenced by collaborations in projects such as the Santa Cruz sluicing dataset and analyses of political discourse in online commentary. His research has been published in journals like Linguistics and Philosophy , Language , and Discourse and Society , with a focus on semantics, pragmatics, and narrative linguistics. He has also contributed to computational linguistics initiatives, including the development of annotated corpora for sentiment analysis and argumentation studies. Dr. Anand's academic contributions span both theoretical exploration and applied computational linguistics, reflecting his interdisciplinary approach to understanding language structure and usage.

Yuriy Rogovchenkoمشاهده پروفایل

استاد

• Qualitative theory of differential equations
• Mathematical modeling in biology
• Perturbation methods
• +۲ مورد دیگر

Yuriy Rogovchenko is a Professor in the Department of Mathematical Sciences at the University of Agder. His research spans differential equations, mathematical modeling, and education innovation, with applications in biology, social sciences, and engineering. Rogovchenko has contributed extensively to mathematics education through projects like PLATINUM (Erasmus+ Strategic Partnership) and CPEA-ST-2019/10067 (Eurasia project). PhD in differential equations (Institute of Mathematics, Kyiv, 1987) Regular Associate at Abdus Salam ICTP, Trieste (2004-2011) Editor for 11 international journals Referee for over 70 journals Research Interests: Qualitative theory of differential equations, perturbation methods, mathematical modeling in interdisciplinary contexts. He focuses on enhancing conceptual understanding through inquiry-based learning and nonstandard problems. Publications: Recent works include advancements in linear system observability, parameter identification methods, and educational studies on exact differential equations. His collaborations with Svitlana Rogovchenko and Matthias Pätzold highlight applications in engineering and biology. Awards: Sørlandet kompetansefonds research award (2016).

Ruihong Huangمشاهده پروفایل

دانشیار

• Natural Language Processing (NLP)
• Information Extraction
• Machine Learning
• +۶ مورد دیگر

Ruihong Huang is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University, part of the College of Engineering. She holds a Ph.D. from the University of Utah (2014) and completed a postdoctoral fellowship at Stanford University. Her research focuses on Natural Language Processing (NLP) with emphasis on information extraction, event recognition, media bias analysis, and ethical AI applications. She teaches courses like Information Storage and Retrieval (CSCE 470), Natural Language Processing (CSCE 638), and has advised numerous PhD, Master’s, and undergraduate students. Key research contributions include work on event coreference resolution, discourse analysis, and detecting media bias through event relation graphs. Huang has developed benchmark datasets like UAL-Bench and EMONA, and her work spans applications in disaster management, fake news detection, and moral reasoning in LLMs. She is a recipient of the NSF CAREER Award and serves on program committees for top conferences like ACL and EMNLP. Her academic service includes roles as Area Chair for ACL 2024 and Senior Area Chair for EMNLP 2024. She maintains an active lab group focusing on NLP fundamentals and real-world applications, with projects involving propaganda identification, polarity calibration for opinion summarization, and multimodal dialog act classification. Huang has published over 80 papers in top-tier venues such as NAACL, EMNLP, ACL, and NeurIPS.

Ksana Blankمشاهده پروفایل

مدرس ارشد

• Russian Literature
• Stylistics
• Interdisciplinary Studies
• +۳ مورد دیگر

Ksana Blank is a Senior Lecturer at Princeton University’s Department of Slavic Languages and Literatures. She coordinates the Russian Language Program and directs the Princeton-in-Petersburg Program, fostering academic exchange and interdisciplinary research. With a PhD in Russian Literature (Columbia University, 1997) and a BA in French Philology (St. Petersburg State University, 1979), her academic career spans over two decades at Princeton, preceded by teaching roles at Hunter College and Middlebury College Russian Summer School. Education: PhD, Russian Literature, Columbia University (1997) BA, French Philology, St. Petersburg State University (1979) Her research centers on Russian literature, emphasizing stylistic analysis and interdisciplinary connections with music, visual arts, folklore, and religious philosophy. Notable works include studies on Dostoevsky’s dialectics, Gogol’s The Nose , and the interplay between Russian modernism and Western art movements. She has authored multiple books and articles, many translated into Russian, and has published in academic journals across Russia, Europe, and China. Recent publications explore Dostoevsky’s paradoxes, Gogol’s linguistic innovation, and the intersection of Russian literature with music (Shostakovich), art (Malevich), and philosophy. Her 2023 book Парадоксы классики expands traditional interpretations of classic works through interdisciplinary lenses, while her 2021 The Nose guide deciphers Gogol’s wordplay and its narrative function. Earlier works address Tolstoy’s spiritual crisis and Bakhtinian dialogism in Russian literary theory. While no scientific awards are listed, her contributions to pedagogy include advanced Russian language courses and graduate-level Tolstoy studies. She currently works on Leo Tolstoy’s The Prisoner of the Caucasus and teaches courses on Russian literature, spirituality, and translation.

William Yang Wangمشاهده پروفایل

استاد

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۹ مورد دیگر

William Yang Wang serves as the Mellichamp Professor of Artificial Intelligence at the University of California, Santa Barbara (2019-present). He directs the UCSB Center for Responsible Machine Learning, the Mind and Machine Intelligence Initiative, and the UCSB NLP Group. His research focuses on theoretical foundations and practical algorithms for AI, particularly in NLP, LLMs, and neuro-symbolic reasoning. PhD in Computer Science from Carnegie Mellon University Active in AI theory and applications (2016-present) Research interests span multiple AI domains, with special emphasis on NLP and responsible machine learning. He has pioneered datasets like HybridQA, TabFact, and VaTeX, enabling advancements in multi-hop QA, fact verification, and video-language tasks. His work combines statistical relational learning with modern deep learning paradigms. Recent publications center around multimodal reasoning, knowledge graph integration, and responsible AI development. He has received numerous accolades including the IEEE SPS Pierre-Simon Laplace Award (2024) and NSF CAREER Award (2021). Karen Sparck Jones Award (2022) DARPA Young Faculty Award (2018) IBM Faculty Award Mentoring 15+ PhD and postdoc researchers who now hold positions at Microsoft Research, Amazon, Meta GenAI, and academic institutions like Arizona and Rutgers. His lab maintains active collaborations with industry partners through initiatives like ChipAgents.ai, which he founded as CEO.

Rachel Rudingerمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning and Data Science
• AI and Robotics
• +۱ مورد دیگر

Rachel Rudinger is an Assistant Professor at the University of Maryland, affiliated with the Department of Computer Science and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Her research focuses on Natural Language Processing (NLP), Machine Learning, and AI ethics, particularly addressing sociocultural biases and fairness in large language models (LLMs). She holds a PhD from Johns Hopkins University (2019) and a B.S. from Yale University (2013). Rudinger's work explores equitable cultural alignment in AI systems, common ground misalignment in dialog systems, and the mutual influence of gender and occupation in LLMs. She received the NSF CAREER Award in 2024 for her project on robust, fair, and culturally aware commonsense reasoning. Her recent publications investigate empathy gaps in LLMs, synthetic data effectiveness in disaster response, and bias measurement techniques across domains. As an advisor, she guides seven PhD students including Christabel Acquaye and Haozhe An. Her research spans diverse topics from legal language analysis to maternal health question answering, reflecting her commitment to interdisciplinary AI ethics. She actively contributes to workshops on commonsense representation and serves as a reviewer for top conferences in NLP and AI.

Dylan Hadfield-Menellمشاهده پروفایل

استادیار

• AI Alignment
• Human-AI Interaction
• Reinforcement Learning
• +۳ مورد دیگر

Dylan Hadfield-Menell is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, holding the Bonnie and Marty (1964) Tenenbaum Career Development Professorship. His research focuses on AI alignment and human-AI interaction within MIT's School of Engineering. His research interests center on agent alignment problems in AI systems, particularly examining uncertainty in objective optimization for human-robot teams and societal oversight of machine learning systems. Key areas include the principal-agent alignment problem , assistance games frameworks , and robust preference learning that accounts for hidden contextual factors in reinforcement learning from human feedback. His recent publications reveal strong trends toward multi-agent cooperation , formal contract mechanisms for resolving social dilemmas, and advanced evaluation methodologies for AI safety. The research spans theoretical frameworks like open-universe assistance games while addressing practical challenges in language model alignment and cultural bias assessment. Scientific awards include: AI2050 Early Career Fellowship from Schmidt Futures Berkeley Fellowship NSF Graduate Research Fellowship C.V. Ramamoorthy Distinguished Research Award His work bridges theoretical computer science with real-world AI governance challenges, as demonstrated through MIT's participation in AI policy white papers. Current research directions include developing frameworks for transparent AI systems and addressing fundamental limitations in aligning recommender systems with human values through interdisciplinary synthesis.

Eugenia Rhoمشاهده پروفایل

استادیار

• Data Analytics
• Machine Learning
• Natural Language Processing
• +۵ مورد دیگر

Eugenia Rho is an Assistant Professor in the Department of Computer Science at Virginia Polytechnic Institute and State University (Virginia Tech), part of the College of Engineering. Her research focuses on data analytics, machine learning, natural language processing, and human-computer interaction, with particular emphasis on social media discourse, online identity dynamics, and ethical AI applications. Education includes a Ph.D. in Information and Computer Sciences from the University of California, Irvine (2020), and a B.A. in Political Science from Columbia University (2011). Her interdisciplinary background bridges computer science and social sciences. Research interests span AI-assisted communication tools, counterspeech strategies for online hate mitigation, and neurodivergent perspectives in technology design. Her work often integrates computational methods with social science theories to address real-world challenges such as bias detection, mental health support, and ethical AI deployment. Recent publications highlight themes like AI collaboration in writing, identity-driven online interactions, and the efficacy of counterspeech. Her projects frequently involve designing human-centered technologies that prioritize accessibility and ethical considerations. No scientific awards are explicitly mentioned in the provided text. She maintains an active Google Scholar profile and a personal homepage (URLs not provided in the text).

Mark Steedmanمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Combinatory Categorial Grammar
• +۲ مورد دیگر

Mark Steedman is Professor of Cognitive Science at the University of Edinburgh's School of Informatics, with adjunct appointment at University of Pennsylvania. His research spans computational linguistics, AI, and cognitive science, focusing on Combinatory Categorial Grammar (CCG) and its applications. His research examines: Combinatory Categorial Grammar parsing and semantics Language model capabilities and limitations Cross-linguistic semantic inference Brain modeling of language processing Recent publications analyze hallucination sources in large language models, cross-linguistic entailment graphs, and brain-computer parallels in structure-building. He develops computational models integrating symbolic and distributional approaches to semantics. Honors include ACL Lifetime Achievement Award (2018) and George E. Davis Medal (2001). He serves on editorial boards of major linguistics journals and has authored influential books including 'The Syntactic Process' and 'Taking Scope'.

• English Language Teacher Education (ELTE)
• Teacher Development
• Reflective Practice
• +۵ مورد دیگر

Steve Mann is a Professor in Applied Linguistics at the University of Warwick, where he has been affiliated since 2007. His work focuses on English Language Teacher Education (ELTE), teacher development, and qualitative research methodologies. He holds a PGCE from the University of Warwick (1984) and has extensive experience in ELT across Hong Kong, Japan, and Europe. Mann’s research group investigates reflective practice, teacher beliefs, mentoring, and technology integration in education. Notable contributions include co-editing the Routledge Handbook of English Language Teacher Education (2019) and pioneering studies on video-based teacher reflection. He has supervised numerous PhD students exploring aspects of teacher development, though he is currently not accepting new PhD candidates. Education: PGCE, University of Warwick (1984) Pre-service teaching in English and Drama in England (1980s) British Council Teaching Scheme in Hong Kong (1980s) Research Interests: Teacher education, reflective practice, qualitative interview methodologies, and the role of technology in professional development. His work emphasizes bridging theory and practice in ELT, particularly through collaborative dialogue and action research. Grants & Projects: Supporting Sustainable English Teacher Professional Development in Yunnan Province (British Council, 2022–2023) China Course Research: Postgraduate Curriculum Design (2019–2022) Video in Language Teacher Education (British Council, 2016–2018) Labs/Teams: Leads a research group focused on teacher development, mentoring, and blended learning strategies. Collaborates with institutions like the British Council on global teacher education initiatives.

Sara Hennessyمشاهده پروفایل

استاد

• Classroom Dialogue
• Digital Technology in Education
• Teacher Professional Development
• +۴ مورد دیگر

Sara Hennessy is a Professor of Educational Dialogue and Pedagogical Inquiry at the Faculty of Education, University of Cambridge , where she teaches and supervises Masters and doctoral students. She serves as Research Director of the £30m+ FCDO-funded EdTech Hub and leads the Cambridge Educational Dialogue Research (CEDiR) Group . Her research spans high- and low-income countries, focusing on classroom dialogue analysis, technology-mediated pedagogy, and teacher professional development. Education: BSc in Social Psychology (LSE), MA (Cantab), PhD in Psychology (UCL) Professional Memberships: American Educational Research Association (AERA), British Educational Research Association (BERA), European Association for Research into Learning and Instruction (EARLI) Research Interests: Hennessy’s work examines how digital technologies can enhance classroom dialogue and collaborative learning, particularly in sub-Saharan Africa. She developed the T-SEDA toolkit for classroom dialogue analysis, which underpins multimedia professional development resources. Her projects include Camtree (global practitioner research platform) and the EdTech Hub , investigating equitable uses of educational technology in low-income contexts. Publications: Her recent articles analyze mixed-methods approaches to classroom dialogue, technology’s role in Tanzanian teacher development, and linguistic considerations in resource localization. Earlier works focus on interactive whiteboards, OERs, and socio-cultural perspectives on technology integration. Scientific Awards: ESRC Research Fellowship (2007-2010): Consolidated practitioner-researcher collaboration methodologies Editorial Roles: Former editor of the British Journal of Educational Technology (2016-2024) and editorial board member of the International Journal of Science Education .

Muchao Yeمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• AI Safety
• +۷ مورد دیگر

Muchao Ye is an Assistant Professor in the Department of Computer Science at the University of Iowa. He earned his Ph.D. from Pennsylvania State University's College of Information Sciences and Technology in 2024 and a Bachelor of Engineering in Information Engineering from South China University of Technology. Ph.D., Information Sciences and Technology, Pennsylvania State University (2024) B.Eng., Information Engineering, South China University of Technology His research focuses on the intersection of Artificial Intelligence, Machine Learning, and AI Safety, particularly adversarial robustness in language models and vision-language models. He designs methods to enhance the security and reliability of deep learning systems for safety-critical applications like video surveillance and healthcare. Recent publications highlight adversarial robustness frameworks (e.g., UniT , PAT ), vision-language models for explainable video anomaly detection ( VERA ), and healthcare risk prediction techniques ( MedPath , MedRetriever ). His work appears in top venues such as NeurIPS, KDD, AAAI, ACL, and CVPR. Professional experience includes Applied Scientist internships at Amazon (2022–2023) and teaching roles at the University of Iowa and Pennsylvania State University. He serves as a reviewer for conferences like NeurIPS, ICML, and journals including IEEE TPAMI.

Benjamin Busamمشاهده پروفایل

پژوهشگر

• 3D Computer Vision
• Multi-Modal Sensor Fusion
• Collaborative Robotics
• +۶ مورد دیگر

Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .

Guofang Liمشاهده پروفایل

استاد

• Early bilingual development
• Family literacy
• Early literacy instruction
• +۲ مورد دیگر

Guofang Li is a Professor in the Department of Language and Literacy Education at the Faculty of Education, affiliated with the Centre for Early Childhood Education & Research (CECER). Her work centers on bilingual development and literacy education within multicultural contexts, particularly focusing on Chinese-Canadian communities. Her research interests include: Early bilingual development Family literacy practices Early literacy instruction methodologies Early education for minority learners Teacher education for multilingual classrooms Analysis of her 2021-2025 publications reveals a concentrated focus on Chinese-Canadian children's bilingual development, examining home literacy environments, digital technology impacts, and pandemic-related disruptions. She consistently advocates for equity-focused approaches in superdiverse educational settings, emphasizing translanguaging practices and critical perspectives on linguistic justice. Scientific Awards: No awards explicitly mentioned in source materials Advising and Grants: No specific student names or grant information provided in source materials Labs and Teams: Centre for Early Childhood Education & Research (CECER): An interdisciplinary hub facilitating collaborative research between academics, educators, and community partners focused on advancing evidence-based early childhood education practices through longitudinal studies and community-engaged projects.