جست‌وجوی استاد و پژوهشگر

• Language Understanding
• Spoken Language Processing
• Dialogue Systems
• +۳ مورد دیگر

Dr. Dilek Hakkani-Tür is a Professor at the Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign. Her primary research focuses on language understanding, spoken language processing, and dialogue systems, with a recent emphasis on large language models (LLMs) and their applications in conversational AI. She has led collaborative efforts in dialog system technology challenges, including DSTC9, and has published extensively in top venues such as ACL, EMNLP, and IEEE SLT. Education: Implied via affiliation and research focus (PhD in Computer Science or related field) Her work bridges theoretical advancements and practical implementations in areas like dialogue state tracking, user preference alignment, and code debugging via LLMs. Collaborations span industry and academia, addressing challenges in human-AI interaction and multimodal dialogue systems. Recent projects include leveraging LLMs for individual preference alignment in conversations, confidence estimation in dialogue systems, and Socratic code debugging frameworks. These contributions highlight her role in advancing conversational AI's technical and applied dimensions.

Jennifer Xuمشاهده پروفایل

استاد

• Business Intelligence
• Big Data
• FinTech
• +۸ مورد دیگر

Jennifer Xu is a Professor of Computer Information Systems at Bentley University, holding a PhD from the University of Arizona. Her research focuses on Business Intelligence, Big Data, FinTech, and Health Informatics, with over 100 publications across Information Systems, Healthcare, and Blockchain domains. Senior Editor: Journal of the Association for Information Systems (JAIS) Associate Editor: Decision Support Systems (DSS), Communications of the AIS (CAIS) Key Contributions: Social network analysis, data mining, and AI ethics applications Her scholarly work spans NLP in healthcare , blockchain auditing , social good data science , and AI education . Recent publications highlight ensemble language models for financial analysis, collaborative healthcare error prevention, and blockchain's impact on accounting. Professor Xu's editorial roles and over two decades of research in systems analysis and social network dynamics reflect her leadership in Information Systems. She has consulted on FinTech and machine learning applications, with a focus on bridging business and technology through AI.

• Condensed Matter Physics
• Computational Materials Science
• Artificial Intelligence in Materials Discovery
• +۱۱ مورد دیگر

Aldo H. Romero is the Eberly Family Distinguished Professor of Physics and Astronomy at West Virginia University, where he serves as Director of Research Computing . His research integrates computational materials science, artificial intelligence, and high-performance computing to advance understanding of condensed matter systems, including strongly correlated materials, 2D materials, and magnetic compounds. Education : Ph.D. in Physics and Chemistry from University of California, San Diego (1998) Awards : Eberly Family Distinguished Professorship Romero’s group specializes in Density Functional Theory (DFT) , Dynamical Mean Field Theory (DMFT) , and machine learning for materials discovery. They develop open-source tools like PyProcar , MechElastic , and ABINIT , focusing on properties such as electronic structure, elastic behavior, and magnetic interactions. Recent work explores chiral materials , AI-driven optimization , and high-throughput computational methods for material design. Key trends in publications include studies on chiral symmetry in kagome lattices, machine learning for material properties, symmetry-based structure prediction, and DFT+DMFT analysis of correlated systems. Collaborations span Germany, France, China, Spain, and Italy, with applications in energy storage, quantum technologies, and spintronics. Scientific contributions encompass: Development of Fireball and ABINIT codes Machine learning for Hubbard U parameter optimization Chiral material discovery via symmetry arguments Pioneering work on 2D Rashba systems Labs and teams include: AI WVU Discussion Group (founded by Romero) West Virginia University Computational Materials Group Collaborative efforts with international institutions Grants and proposals highlight initiatives like the NSF & NVIDIA Open Multimodal AI Infrastructure (OMAI) program and Spencer Foundation support for AI in education. The group works with over 20 graduate students and 4 postdoctoral researchers, emphasizing interdisciplinary training and global collaboration.

Marianna Safronovaمشاهده پروفایل

استاد

• Quantum Metrology
• Dark Matter Searches
• Atomic Clocks
• +۷ مورد دیگر

Marianna Safronova is a Professor in the Department of Physics & Astronomy at the University of Delaware, affiliated with the College of Arts & Sciences. She leads the Safronova Group, which focuses on quantum metrology, dark matter searches, and precision atomic calculations. Her work spans quantum sensors for space applications, atomic clock development, and fundamental physics tests. Education details are not explicitly provided, but her extensive contributions suggest advanced training in theoretical atomic physics. Her research emphasizes high-precision atomic data via the Atomic Data Portal, collaborations on the Thorium Nuclear Clock project (ERC Synergy Grant), and NSF-funded quantum sensing algorithms. Key research areas include: quantum sensors for dark matter detection, Coulomb-crystal clocks, space-based quantum technologies, and applications of neural networks in atomic physics. She co-organizes the 2025 Bad Honnef Physics School on quantum metrology for new physics searches. Labs/Teams: Safronova Group, Q-SEnSE Institute, Thorium Nuclear Clock collaboration. Current projects involve space mission proposals for dark matter detection and development of next-generation atomic clocks.

• Construction Engineering and Management
• Data Analytics
• Artificial Intelligence (AI)
• +۶ مورد دیگر

Professor Nora El-Gohary is a faculty member in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. She holds the title of CEE Excellence Faculty Fellow and has held academic positions including Assistant Professor (2009–2017), Associate Professor (2017–2023), and full Professor (2023–present). Her professional experience includes roles at the University of Manitoba and Hyundai Engineering & Construction Co. Ltd. Education: B.Sc. Construction Engineering, American University in Cairo (1999) M.Sc. Construction Engineering, American University in Cairo (2002) Ph.D. Civil Engineering, University of Toronto (2008) Research focuses on data analytics, AI, and BIM for sustainable infrastructure. Key areas include: Automated compliance checking using NLP Machine learning for energy consumption prediction Human-centered systems for construction management Awards include the NSF CAREER Award (2013), NCSA Fellow (2018), and 2025 ASCE Computing in Civil Engineering Award. She has led over 100 research projects funded by agencies like NSF and Illinois Department of Transportation. Editorial roles include Co-Editor-in-Chief of the ASCE Journal of Computing in Civil Engineering (2024–present) and Associate Editor (2012–2023). Active in professional societies such as TRB and ASCE.

Ron Mangunمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Visual Attention
• Neural Mechanisms of Attention
• +۳ مورد دیگر

Ron Mangun is a Professor of Psychology and Neurology at the University of California, Davis, and co-director of the Center for Mind and Brain . His work bridges cognitive neuroscience, attentional mechanisms, and the interplay between free will and neural processes. Mangun has significantly shaped neuroscience education through his co-authored textbook, Cognitive Neuroscience: The Biology of the Mind , which has sold over 150,000 copies across five editions. 2024 Award for Education in Neuroscience Fulbright US Distinguished Scholar (2024-2025) Mangun's research focuses on visual attention , neural oscillations , and predictive cognitive processes , often integrating EEG-fMRI for high-resolution neural mapping. His recent work explores alpha oscillations, rhythmic environmental sampling, and the ventral attention network's role in reorienting attention. His scientific awards include: 2024 Award for Education in Neuroscience Fulbright US Distinguished Scholar (2024-2025) Mangun has mentored numerous trainees globally through the Summer Institute in Cognitive Neuroscience , a program funded by NIMH, NIDA, and the Kavli Foundation. His research is supported by the National Science Foundation , focusing on attention and free will.

Roozbeh Kianiمشاهده پروفایل

استاد

• Decision Making
• Neuroscience
• Psychology
• +۵ مورد دیگر

Roozbeh Kiani is a Professor of Neural Science and Psychology at New York University's College of Arts and Science. His research focuses on decision-making processes and their neural underpinnings, combining electrophysiological recordings, fMRI, and computational modeling. He holds a Ph.D. from the University of Washington (2009) and leads a lab studying perceptual and mnemonic decision mechanisms. Key areas include neural integration of sensory evidence, confidence estimation, and the role of prefrontal and parietal cortices. Education: Ph.D. in Neuroscience, University of Washington (2009). Research emphasizes understanding how the brain integrates information to form decisions, with applications to cognitive disorders. His lab employs advanced techniques like single-neuron recordings and causal manipulation of neural circuits to dissect decision dynamics. Current projects explore hierarchical decision-making, neural representations of choice confidence, and the impact of perturbations on circuit function. Students advised include Isabella Rischall (PhD student) and Chenghao Zhou (Master’s student). Collaborations span computational neuroscience, biomedical engineering, and cognitive psychology. Publications highlight topics like recurrent neural circuit compensation (2024), functional causal flow predictions (2023), and Bayesian models of perceptual confidence (2021). His work bridges cellular mechanisms with behavioral outcomes, aiming to inform treatments for cognitive impairments.

Quan Wangمشاهده پروفایل

پژوهشگر

• Computational Biology
• Genomics
• Bioinformatics
• +۴ مورد دیگر

Quan Wang, Ph.D., is a Researcher in the Department of Molecular Physiology and Biophysics at Vanderbilt University School of Medicine. His work focuses on integrating computational methods with genomic data to address challenges in cancer biology, neurodegenerative diseases, and precision medicine. Key tools developed include REMR for RNA editing analysis, DeepIRES for mRNA site prediction, and TMBserval for tumor mutation burden modeling. Research interests center on multi-omics integration, epigenetic regulation, and applying machine learning to drug discovery and disease gene prioritization. He has contributed to studies on glioma stem cells, Alzheimer’s drug repurposing, and schizophrenia risk gene prediction. Publications highlight advancements in genomic data analysis, including Bayesian frameworks for multi-omics integration and tools like DRAMS for sample quality control. Collaborative efforts span computational biology, cancer genomics, and systems biology, with applications in personalized therapy and disease biomarker identification. No awards or grants are explicitly listed in the provided text. Advising roles and student mentorship details are not specified here.

Andrew McGregorمشاهده پروفایل

استاد

• Theoretical Computer Science
• Algorithms
• Data Streams
• +۵ مورد دیگر

Andrew McGregor is a Professor in the Department of Computer Science at the University of Massachusetts Amherst, affiliated with the Manning College of Information and Computer Sciences. He is a core member of the Theory Group and directs the TRIPODS Institute for Theoretical Foundations of Data Science. His research focuses on algorithms for massive data sets, data streams, and information theory, with applications in clustering, approximation algorithms, and coding theory. Education: PhD, Computer Science, University of Pennsylvania (2007) MEng, Computer Science, University of Pennsylvania (2002) BA, Mathematics, University of Cambridge (2000) Research Interests: Design and analysis of algorithms for data streams and massive datasets Clustering algorithms and approximation techniques Coding theory and information-theoretic approaches Algorithmic fairness and combinatorial optimization Recent Article Trends: Advances in streaming algorithms for dynamic graphs and parameterized complexity Graph reconstruction and allocation problems under noisy conditions Quantum communication and scheduling policies for satellite networks Entropy estimation and probabilistic methods in data analysis Awards: NSF CAREER Award (2010) ACM PODS Test-of-Time Award (2020) Lilly Teaching Fellowship (2012) Outstanding Teacher Award (2016) Grants & Labs: Director, TRIPODS Institute for Theoretical Foundations of Data Science Collaborations with Microsoft Research and UCSD's Information Theory & Applications Center Active in Center for Data Science and Theoretical Computer Science Group Future Work: Expanding research on quantum algorithms, scalable causal inference, and fair data diversification techniques.

Keriayn Smithمشاهده پروفایل

دانشیار

• Non-coding RNA
• Genetics
• Epigenetics
• +۴ مورد دیگر

Keriayn Smith, PhD, is an Associate Professor in the Department of Genetics at the University of North Carolina School of Medicine and holds a concurrent appointment as an Associate Professor in the School of Data Science and Society. Her research focuses on non-coding RNAs, particularly long noncoding RNAs (lncRNAs), exploring their roles in cell identity, developmental processes, and disease mechanisms. She has received significant grants, including an NSF award ($665,786) for studying lncRNA functions in yeast and mammalian cells, and a Hypothesis Fund Seed Grant for investigating noncoding RNAs' roles in cell identity. Dr. Smith’s work emphasizes translational applications, such as leveraging lncRNA insights for regenerative medicine and personalized therapies. She leads initiatives like the RNA Discovery Center at UNC Lineberger Comprehensive Cancer Center, promoting diversity in RNA research. Notably, she chairs the Society for Scientific Advancement (SOSA), advocating for STEM accessibility in underserved regions and underrepresented groups. Her grants include a UNC Idea Grant for studying the oncogenic role of lncRNA Cyrano in neuroblastoma and supplemental funding during the pandemic to explore lncRNA roles in stem cell maintenance. Recent articles highlight her contributions to understanding lncRNA networks, epigenetic regulation, and interdisciplinary collaborations in genomics. Awards include the Junior Faculty Development Award from the UNC Provost’s Office, recognizing her project on comparative transcriptomics in ozone-exposure models. Dr. Smith’s research bridges basic science with clinical impact, addressing systemic risks to health through innovative, high-risk projects.

Marc H Gershowمشاهده پروفایل

دانشیار

• Neuroscience
• Neurophysiology
• Sensory Systems
• +۳ مورد دیگر

Marc H Gershow is an Associate Professor and Director of Undergraduate Studies for Physics at New York University's College of Arts and Science. His research focuses on understanding sensory processing and decision-making in model organisms like Drosophila larvae and C. elegans. He develops advanced microscopy techniques, including CRASH2p and 3D tracking two-photon imaging, to study neural activity in freely behaving animals. His work bridges neuroscience, physics, and engineering to uncover how organisms integrate sensory information with learned and innate behaviors. Education & Background While specific educational details are not explicitly listed, his research trajectory suggests a strong background in biophysics and neuroscience. His lab homepage indicates ongoing projects in olfactory circuits, sensory integration, and neurophysiological imaging. Research Interests Gershow's lab investigates neural mechanisms underlying navigation, olfactory learning, and decision-making. Key areas include: Olfactory circuits in Drosophila larvae and C. elegans Development of closed-loop imaging systems (e.g., CRASH2p) Multi-neuronal recording in unrestrained animals Integration of learned and innate sensory valences Awards & Recognition NSF CAREER Award (2015) NIH Director's New Innovator Award (2015) Lab & Collaborations His lab integrates engineering and biology, with a focus on creating tools for real-time neural activity analysis. Collaborations likely span physics, neuroscience, and computational biology. The lab homepage provides further details on ongoing projects and publications.

Michael Shahمشاهده پروفایل

مدرس ارشد

• Computer Science Education
• Software Visualization Tools
• Performance Analysis
• +۳ مورد دیگر

Michael Shah is a Senior Lecturer of Computer Science at Yale University's School of Engineering & Applied Science. His research focuses on software visualization tools, performance analysis frameworks, and innovative computing education methodologies. He has contributed to fields such as parallel computing, GPU execution visualization, and asynchronous programming patterns. Dr. Shah's work bridges technical software development with educational applications, including curriculum design for introductory graphics courses and teaching assistant training programs. His research emphasizes practical tool development for debugging and performance optimization in both academic and industry contexts. Notable projects include the Daisen GPU visualization framework, DrAsync for JavaScript anti-pattern detection, and the Iceberg static analysis tool for Java concurrency issues. His publications span topics from procedural content generation in games to runtime performance bug mitigation strategies.

Tyler Calkinمشاهده پروفایل

دانشیار

• Art and Technology
• Digital Media
• Virtual Reality
• +۷ مورد دیگر

Tyler Calkin is an Associate Professor and Head of Digital Media at the University of Nevada, Reno within the Department of Art, Art History and Design. He received his MFA in Art and Integrated Media from the California Institute of the Arts in 2011 and his BA in Art from Whitman College in 2009 (with Minor in English, Magna Cum Laude). Prior to joining UNR, he taught in the Program in Art and Technology and The Center for Integrated Media at CalArts, where he developed an experimental VR lab. Calkin's interdisciplinary practice spans objects, performance, video, augmented and virtual reality, machine learning, and motion capture, often in recursive combinations. His research focuses on artificial intelligence and machine learning, human-robot interaction, 3D modeling and fabrication with motion capture, and XR interactivity and social experience. He constructs interactive and immersive propositions for interpersonal experience, responding to current developments in consumer technologies and pandemic-era tech practices. His recent body of work demonstrates a strong focus on virtual reality, motion capture, and digital fabrication, with numerous international exhibitions including venues in Berlin, London, Venice, Beijing, Kathmandu, Seoul, Mexico, New York, and Los Angeles. His 2022 work 'Agreement Collapse' explores climate change through a gravity simulation featuring a pink mocap model in a blue cloudy sky, commenting on international climate accords. His publications and presentations reveal an ongoing exploration of digital interfaces, social interactions in virtual spaces, and the philosophical implications of emerging technologies. Calkin teaches critical theory and experimental practices in video, immersive and interactive media, and digital fabrication. His teaching emphasizes critical discourse and experimental approaches to creative coding, performance, and game design. As Area Head of Digital Media, he leads curriculum development in emerging digital art forms and technologies.

Gursimran Waliaمشاهده پروفایل

استاد

• Software Engineering Education
• Programming Pedagogy
• Requirements Engineering
• +۷ مورد دیگر

Dr. Gursimran Walia serves as Professor and Associate Dean for Academic Affairs in the School of Computer and Cyber Sciences at the University of Georgia. Their academic background includes a Ph.D. and Master of Science in Computer Science from Mississippi State University (2009 and 2006). They hold administrative roles in both the Department of Computer & Cyber Sciences and The Graduate School. Dr. Walia's academic contributions span multiple institutions and interdisciplinary initiatives. Educational Background Ph.D., Computer Science, Mississippi State University (2009) M.S.C., Computer Science, Mississippi State University (2006) Research Focus Dr. Walia's work centers on software engineering education, programming pedagogy, and human factors in software development. They develop novel tools like the Testing Tutor platform and Non-intrusive Classroom Attention Tracking System (NiCATS) . Their research emphasizes improving student learning outcomes through active learning strategies, gamification, and AI-driven education technologies. Key themes include: Software requirements engineering and error taxonomy development Classroom attention tracking using machine learning and eye-tracking Curriculum design for software testing and database systems Addressing industry-education gaps in CS graduate preparedness Professional Service Dr. Walia actively contributes to academic service through: Curriculum development initiatives Educational research funding proposals Reviewing for conferences and journals in software engineering education Innovation & Labs Their work involves: Designing cyberlearning environments for CS education Developing the WReSTT (Web-based Repository of Software Testing Tutorials) Advancing NiCATS classroom monitoring systems

Qun Liمشاهده پروفایل

استاد

• Edge Computing
• Operating Systems
• Distributed Systems
• +۳ مورد دیگر

Qun Li is a Professor of Computer Science at the College of William and Mary, leading the Edge Computing Laboratory. He holds an IEEE Fellow distinction and has served as Graduate Director (2010-2011). His research focuses on edge computing, operating systems, distributed systems, and security & privacy, with over 100 publications in top venues like ACM CCS, ICSE, and NSDI. Li has advised numerous PhD students, including Zhengrui Qin and Ed Novak, who now hold academic positions. He chairs conferences including ACM/IEEE Symposium on Edge Computing (SEC'22) and has editorial roles at IEEE Internet Computing and Transactions on Computers. Key awards include an NSF Career Award. His work emphasizes building prototype systems and addressing real-world challenges in edge computing and quantum networks. Education: PhD from Dartmouth College under Daniela Rus Research interests span edge computing architecture, secure deep learning, federated learning, and quantum computing applications. His Edge Computing Group explores scalable solutions for distributed systems and privacy-preserving technologies. Recent publications (2022-2024) focus on quantum networks, federated learning robustness, and privacy-preserving algorithms. A notable trend is integrating quantum computing with edge systems for enhanced security and efficiency. Awards: NSF Career Award (year unspecified), IEEE Fellow (year unspecified) Advised students have transitioned to academia and industry roles, reflecting Li's mentorship impact. Active in conference organization, he has led program committees for ACM SEC and IEEE ICDCS, while steering editorial boards in computer networks and systems. Current projects include quantum network routing and Byzantine-tolerant federated learning.