جست‌وجوی استاد و پژوهشگر

Lianne Lefsrudمشاهده پروفایل

دانشیار

• Risk Management
• Sustainability
• Organizational Theory
• +۵ مورد دیگر

Lianne Lefsrud serves as Associate Professor and Risk, Innovation, and Sustainability Chair (RISC) in the Department of Chemical and Materials Engineering at the University of Alberta's Faculty of Engineering. Her interdisciplinary research bridges engineering, social sciences, and policy to transform risk management practices across energy, mining, construction, and railroading industries, directly influencing regulations, building codes, and industry operations for sustainable development. Her academic credentials include: BSc in Civil Engineering (Cooperative Program), University of Alberta (1994) MSc in Interdisciplinary Civil & Environmental Engineering and Sociology, University of Alberta (1996) PhD in Strategic Management and Organization, Alberta School of Business (2014) Dr. Lefsrud's research centers on risk management frameworks for sustainability challenges. She examines hazard identification, social license to operate, and technology adoption drivers in high-hazard industries, with emphasis on prospective risk assessment (e.g., hydrogen infrastructure design) and retrospective analysis (e.g., microplastic pollution impacts). Her work integrates circular economy principles into energy systems while addressing unintended consequences across UN Sustainable Development Goals. Recent publications (2024-2025) demonstrate heavy focus on machine learning applications for rail and construction safety, hydrogen infrastructure risk analysis, and science denial mitigation. Key patterns show cross-industry adaptation of AI for incident prediction, regulatory gap analysis for emerging energy systems, and socio-technical approaches to reconcile sustainability goals with operational realities. Scientific recognition includes: Erb Post-Doctoral Fellowship (University of Michigan) Dow Sustainability Research Fellowship (Ross School of Business) Dr. Lefsrud mentors graduate students through industry-integrated projects like her Sustainable Design course where teams generated patents and city solutions. Her research secures Alberta Innovates funding with 1:4 industrial-to-federal matching, collaborating with Suncor, Transport Canada, and Canadian Standards Association. Grants target practical implementations including railcar inspection systems and hydrogen safety protocols. She co-founded Insight Risk Systems and leads the Lefsrud Lab, prioritizing inclusive teams with under-represented groups (women, Indigenous, LGBTQ2S+, neurodiverse) to tackle 'wicked problems' in sustainability. The lab leverages interdisciplinary partnerships across engineering, computer science, psychology, and environmental sociology for real-world risk management solutions.

Catherine Crockfordمشاهده پروفایل

استاد پژوهشی

• Primate Behavior
• Social Cognition
• Vocal Communication
• +۴ مورد دیگر

Dr. Catherine Crockford is Research Professor and Director of the Ape Social Mind Lab at the Max Planck Institute for Evolutionary Anthropology, affiliated with the Department of Human Behavior, Ecology and Culture. She co-directs the Tai Chimpanzee Project in Ivory Coast, studying habituated chimpanzee groups and sooty mangabeys. Her research examines primate social cognition, communication evolution, and neuroethology through behavioral observations, hormone sampling, and neuroimaging. Key interests include: Evolution of social bonding and cooperation mechanisms Maternal effects on offspring development Vocal communication and combinatorial signaling Neurobiological bases of social behavior Her publications demonstrate consistent focus on chimpanzee vocal combinatorics, stress physiology, social learning, and comparative neuroanatomy, often integrating field data with endocrine and imaging methodologies. She leads an ERC project investigating early-life influences on social skills and supervises 8 PhD students researching primate communication, social dynamics, and energetics. Laboratory infrastructure supports field endocrinology and collaborative neuroimaging studies.

Kenneth M. Andersonمشاهده پروفایل

استاد

• Software Engineering
• Crisis Informatics
• Human-Computer Interaction
• +۳ مورد دیگر

Professor Kenneth M. Anderson is Chair of the Department of Computer Science and holds the Palmer Endowed Chair at the University of Colorado Boulder's College of Engineering & Applied Science. He co-directs Project EPIC, a $4M NSF-funded initiative on social media use during mass emergencies, and serves as Co-Director of the Center for Software and Society. Ph.D. in Computer Science, University of California, Irvine (1997) Joined CU Boulder in 1998; tenured in 2005 Former Associate Dean for Education (2016-2019) Former Associate Chair (2010-2013) His research bridges software engineering, crisis informatics, and human-computer interaction. Current projects focus on large-scale social media analytics, crisis response systems, and software architecture for data-intensive environments. Recent publications explore multilingual social media analysis (ML-EPIC), bug fix patterns in software development (FIXR), and collaborative big data platforms. Themes include disaster risk communication, data modeling challenges, and asynchronous analysis tools. ATLAS Fellow (2010) As department chair, he spearheaded initiatives for inclusivity, including creating a Bachelor of Arts in Computer Science and establishing the NSF Broadening Participation in Computing plan. He oversees major academic reforms and departmental operations.

Debswapna Bhattacharyaمشاهده پروفایل

دانشیار

• Computational Biology
• Bioinformatics
• Machine Learning
• +۵ مورد دیگر

Debswapna Bhattacharya is an Associate Professor in the Department of Computer Science at Virginia Tech. Her research focuses on computational biology, bioinformatics, and machine learning with applications in structural biology. She holds a Ph.D. from the University of Missouri-Columbia (2016) and previously served as an Assistant Professor at Auburn University (2017–2021). Her work develops AI-driven methods for biomolecular modeling, including RNA and protein structure prediction, quality assessment, and refinement. Notable contributions include software tools like lociPARSE, RNAbpFlow, and EquiPNAS. She has received prestigious awards such as the NSF CAREER Award (2020) and NIH MIRA Award (2020). Teaching includes courses on machine learning and AI in molecular modeling. Her lab collaborates on NIH-funded projects (R35GM138146) and NSF initiatives (DBI2208679). Recent work emphasizes equivariant neural networks and transformer-based models for biomolecular analysis.

Guoquan Huangمشاهده پروفایل

استادیار

• Robotics
• Computer Vision
• Robot Learning
• +۵ مورد دیگر

Guoquan Huang is an Assistant Professor in the Department of Mechanical Engineering at the University of Delaware. He holds a B.Eng. in Automation from the University of Science and Technology, Beijing (2002), and M.Sc. and Ph.D. degrees in Robotics from the University of Minnesota (2009 and 2012). Prior to his current role, he was a Postdoctoral Associate at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on robotics, computer vision, and autonomous systems, emphasizing probabilistic perception, estimation, and control for ground, aerial, and underwater vehicles. He leads the development of the OpenVINS platform for visual-inertial estimation and has contributed to advancements in SLAM (Simultaneous Localization and Mapping), sensor fusion, and multi-robot coordination. Education: B.Eng in Automation (Electrical Engineering), University of Science and Technology, Beijing, 2002 M.Sc. in Robotics, University of Minnesota, Twin Cities, 2009 Ph.D. in Robotics, University of Minnesota, Twin Cities, 2012 His research interests span robotics, computer vision, and autonomous systems , with a focus on: Visual-inertial navigation and SLAM Sensor fusion (LiDAR, IMU, camera) Autonomous vehicle control and safety Multi-robot cooperative localization His recent publications (2023–2025) emphasize robust algorithms for navigation in GPS-denied environments, real-time sensor calibration, and dataset development for aerial visual localization. He has pioneered techniques like decoupled error-state estimation and consistent parallel frameworks for SLAM. Labs/Teams: Leads the development of the OpenVINS research platform, focusing on visual-inertial state estimation. Collaborates on projects involving human-swarm interactions and resilient ground vehicle navigation.

• Model-based Systems Engineering
• Safety-Critical Systems
• Systems Engineering
• +۳ مورد دیگر

Dr. Siyuan Ji is a Reader in Model-based Systems Engineering (MBSE) at Loughborough University, serving as Deputy Head of the Manufacturing, Systems & Management Academic Community and Deputy Director of the Doctoral Training Centre in MBSE. He previously held a Senior Lecturer position in Systems Engineering at the University of York, where he led the MSc Programme in Safety-Critical Systems Engineering. His academic journey includes a PhD and MSc in Physics from the University of Nottingham, followed by research roles in model-based systems engineering at Loughborough University. His research focuses on advancing model-based techniques for systems engineering, particularly in safety-critical systems, formal methods, and complex system design. He has contributed to areas such as hazard management (e.g., BSafeML framework), response time analysis in real-time systems, and model synchronization for requirements engineering. His work bridges theoretical foundations with practical applications in automotive systems, embedded software, and educational technology. Dr. Ji holds the title of Fellow of the Higher Education Academy and has published extensively on topics ranging from quantum technology reporting to conversational tutoring systems. His research emphasizes interdisciplinary collaboration, evident in projects like the EPSRC-funded analysis of vehicles as complex systems. He actively contributes to both academic and industrial advancements in systems engineering methodologies and education innovation. His professional roles include managing doctoral training programs, overseeing academic communities, and advancing systems engineering education. Collaborations span industry partnerships and international academic networks, reflecting his commitment to impactful research and training the next generation of systems engineers.

Froukje Sleeswijk Visserمشاهده پروفایل

دانشیار

• Service Design
• Public Service Design
• Empathy-Centric Design
• +۳ مورد دیگر

Dr. Froukje Sleeswijk Visser is an Associate Professor in Service Design at Delft University of Technology's Industrial Design Engineering department, part of the Human-Centered Design group. She works part-time and focuses on public service design, empathy-driven methodologies, and co-design approaches. Her research emphasizes societal challenges, user participation, and empathic design practices. She advises ContextQueen, a consultancy firm, and collaborates on projects like MyFutures Lab (winner of the 2018 Hans Sauer Award). Education: PhD in Design Engineering (2009, TU Delft), Master’s in Industrial Design Engineering (Delft). Key roles include teaching courses like 'Contextmapping Skills' and 'Human-Centered Design and Beyond'. Research projects involve Innovation in Services, Empathic Future Visions, and Bubble Games exploring empathy design. Publications span over 50 peer-reviewed works since 2003, focusing on empathic design frameworks, service design deliverables, and collaborative research impacts. She advocates for bridging design research and industry practice, with notable contributions to contextmapping and empathic method taxonomies. Labs/Studios: Active in StudioLab (cross-pollination of research/education) and MyFutures (tools for personal future planning). Current projects explore VR for empathy-building and interdisciplinary design labels.

Sharad Mehrotraمشاهده پروفایل

استاد

• Data Management
• Distributed Systems
• Database as a Service
• +۷ مورد دیگر

Sharad Mehrotra is a Distinguished Professor at the University of California, Irvine (UCI), leading the Center for Emergency Response Technologies (CERT) and directing the NSF-funded RESCUE project. He previously served at the University of Illinois, Urbana-Champaign, and holds a Ph.D. from the University of Texas at Austin (1993). His research focuses on data management, IoT systems, privacy-preserving technologies, and smart spaces, with contributions to frameworks like TIPPERS and MARS. Education: Ph.D., Computer Science, University of Texas at Austin, 1993 Research Interests: His work bridges database systems, security, and IoT, emphasizing privacy in smart environments. Notable projects include sentient space technologies for disaster response, cryptographic methods for encrypted data queries, and semantic IoT integration. Recent efforts address privacy in multi-owner data systems and resilient community water infrastructure. Awards & Recognition: ACM Fellow (2024) SIGMOD Best Paper (2001), DASFAA Best Paper (2004) NAVWAR Innovation Award (2021) Outstanding Graduate Mentor (2005) Grants & Leadership: As RESCUE PI, he managed $12.5M NSF funding, developing crisis-response software deployed by emergency agencies. Collaborations include the Cal-IT2 institute (UCSD/UCI) and the US Navy’s TIPPERS platform. He co-leads initiatives like the NSF Civic Innovation Challenge for disaster resilience in aging communities. Labs & Teams: Directs UCI’s Information Systems Group and CERT, fostering interdisciplinary research with 60+ members. His teams produce open-source tools (e.g., SEMIoTIC, PrivacySphere) and engage in global partnerships via Fulbright Visiting Scholar programs.

Prithviraj Ammanabroluمشاهده پروفایل

استادیار

• Natural Language Processing
• Reinforcement Learning
• Artificial Intelligence
• +۵ مورد دیگر

Prithviraj Ammanabrolu is an Assistant Professor at the University of California, San Diego (UCSD) , affiliated with the Department of Computer Science and Engineering . He leads the PEARLS Lab (Pragmatically Exploring Agents with Reinforced LanguageS) and collaborates with Nvidia as a Research Scientist. Research Focus: Bridging Machine Learning (particularly Reinforcement Learning ) with Natural Language Processing to create trustworthy and responsible language-based AI agents . Key Themes: Contextual language understanding, neurosymbolic world modeling, human preference alignment via feedback, and AI in grounded environments . Before joining UCSD in 2024, he worked on the Mosaic team at the Allen Institute for AI and as a Research Scientist at MosaicML (acquired by Databricks) . His work intersects Cognitive Science and AI scalability . Education: PhD in Computer Science from the Georgia Institute of Technology , advised by Professor Mark Riedl at the Entertainment Intelligence Lab . Projects: RL4LMs, ScienceWorld, Q-BERT, WorldGeneration, and LLMFoundry for Databricks foundation models.

J. Elliott Casalمشاهده پروفایل

استادیار

• Applied Linguistics
• Corpus Linguistics
• Corpus-based Language Teaching
• +۷ مورد دیگر

J. Elliott Casal serves as an Assistant Professor in the Department of English at the University of Memphis, where his research centers on applied linguistics with emphases in corpus linguistics, discipline-specific writing, and genre-based language pedagogy. His work bridges theoretical frameworks with practical applications for language teaching and academic literacy development across diverse disciplinary contexts. His academic credentials include: Ph.D. (2016-2020) from Pennsylvania State University M.A. (2012-2014) from Ohio University B.A. (2004-2008) from Ohio University Casal's research investigates functional linguistic conventions in professional communication, development of discipline-specific literacies, and corpus tool integration in language education. His scholarship critically examines syntactic complexity, phraseological patterns, and academic literacy across disciplines through both quantitative corpus analysis and qualitative assessments of learner agency, creativity, and intentionality in writing development. Analysis of his 15 most recent publications (2019-2024) reveals consistent focus on corpus-driven methodologies applied to academic writing across STEM and humanities disciplines. Key trends include syntactic complexity development in L2 legal writing, AI-writing detection ethics, frame-based formulaic features in academic genres, and cross-disciplinary variation in research article structures, demonstrating evolving applications of corpus linguistics to contemporary language education challenges.

Min Liuمشاهده پروفایل

استاد

• Lean Construction
• Digital Twin Design
• Data Mining
• +۵ مورد دیگر

Dr. Min Liu is a Professor and the Abdallah H. Yabroudi Endowed Professor in Sustainable Civil Infrastructure at Syracuse University, where she directs the Syracuse University Infrastructure Institute. She holds a Ph.D. in Engineering Project Management from UC Berkeley, and prior degrees from National University of Singapore and Xi’an University of Architecture and Technology. Her research focuses on integrating human and engineering aspects in construction planning, with emphasis on Lean Construction, Digital Twin design, and machine learning applications. She has published over 50 articles in top-tier journals and won prestigious awards such as the 2021 ASCE Thomas Fitch Rowland Award. Dr. Liu advises numerous graduate students and postdocs, offering positions in Construction Engineering and Management. Her lab develops innovative approaches for infrastructure project delivery, worker mental health, and bridge preservation strategies. Education: Ph.D. in Engineering Project Management, UC Berkeley (2007) MSCE, Xi’an University of Architecture and Technology (1997) MSc in Building Science, National University of Singapore (2001) BSc in Civil Engineering, Qingdao University of Technology (1994) Research Highlights: Large language models for construction planning reliability Ontology-based knowledge systems for construction methods Lean techniques for worker mental health improvement Socioeconomic analysis of bridge preservation strategies Awards: 2021 ASCE Thomas Fitch Rowland Award Multiple Best Paper Awards (2017-2018) "Thank a Teacher" awards (2011-2018) Her advising record includes notable students like Chuanni He (2023 Chinese Government Award) and Gongfan Chen (2022 Three-Minute Thesis Award). Current opportunities include Ph.D. financial support and postdoc positions. Dr. Liu’s work appears in journals like ASCE Journal of Management in Engineering and Engineering, Construction and Architectural Management.

Eoin Delaneyمشاهده پروفایل

مدرس

• Explainable AI
• Trustworthy AI
• Computer Vision
• +۶ مورد دیگر

Eoin Delaney is a Lecturer in the School of Computer Science and Statistics at Trinity College Dublin (as of Spring 2025). Previously, he was a Postdoctoral Researcher at the Oxford Internet Institute (OII), University of Oxford (October 2023 – March 2025), focusing on Trustworthiness Auditing in AI. His research spans Explainable AI, algorithmic fairness, computer vision, and sustainable AI applications. He holds a PhD from University College Dublin (UCD), advised by Dr. Derek Greene and Prof. Mark T. Keane, where he developed counterfactual explanations for time series and image data. His work bridges technical AI research with societal impact, including collaborations with Accenture Labs and the VistaMilk SFI Research Centre. Key achievements include developing the OxonFair toolkit (accepted to NeurIPS 2024), winning the 2022 AI Ireland Award for Best Application of AI in a Student Project, and authoring papers in top venues like NeurIPS, AIJ, and IJCAI. He is actively involved in academic service, serving on program committees for FAccT 2025 and AAAI workshops. Eoin has supervised students at the University of Oxford and organizes workshops on AI accountability, such as the Auditing Accountability in Trustworthy Artificial Intelligence in personalized medicine. His teaching and outreach efforts include promoting STEM education through initiatives like an educational website for children, emphasizing cryptography and probability. He continues to explore fairness in AI systems, user-centric explanations, and scalable machine learning frameworks (PyTorch, TensorFlow).

• Primary Science Education
• Early Years Science
• Teacher Professional Learning
• +۲ مورد دیگر

Associate Professor Christine Preston at the University of Sydney's Faculty of Education and Social Work specializes in primary science education with a focus on early childhood development. She maintains active classroom experience through her kindergarten science teaching and leads research on science diagrams, toy-based learning, and teacher professional development. Her work integrates embodied learning and representational pedagogies to enhance conceptual understanding in STEM subjects. Dr. Preston's research examines innovative approaches including citizen science integration, digital technologies, and adaptive curriculum design. She currently lectures in primary science and technology education, while supervising doctoral candidates exploring computational thinking and marine biology education. Her scholarly contributions emphasize practical classroom applications and teacher support resources. Award recognition includes multiple Excellence in Teaching awards (2007, 2016) and the 2001 NSW Quality Teaching Award. She maintains active membership in international science education associations including ASTA, ESERA, and NSTA, serving on editorial boards for science education journals.

Adam Albrightمشاهده پروفایل

استاد

• Phonology
• Morphology
• Language Acquisition
• +۴ مورد دیگر

Adam Albright is a Professor of Linguistics at the Massachusetts Institute of Technology (MIT). His research focuses on phonology, morphology, language acquisition, and computational linguistics. Education Ph.D. in Linguistics, UCLA, 2002. Dissertation: "The identification of bases in morphological paradigms" M.A. in Linguistics, UCLA, 1998. Thesis: "Phonological subregularities in productive and unproductive inflectional classes: Evidence from Italian" B.A. in Linguistics and Religious Studies, Cornell University, 1996. Senior Thesis: "The history of stress in Welsh, and the analysis of historical change in OT" Research Interests Albright's main research projects include: Experimental testing and computational modeling of gradient phonotactic well-formedness Investigating the organization of paradigms (base selection and learning) Testing the psychological reality of morphological processes via Wug tests Understanding paradigm gaps Computational modeling of historical change Collaboration with Bruce Hayes on learning algorithms He also has interests in Yiddish and Lakhota phonology and morphology, and the history of stress in Welsh. Teaching He has taught courses at MIT and UC Santa Cruz, including: Advanced Phonology Language Acquisition Sound Change and Phonological Theory Modeling Phonological Learning Language Change Computational Morphology & Phonology Collaborations Albright collaborates with Bruce Hayes (UCLA) on computational modeling of phonological and morphological learning. Contact Email: albright@mit.edu Office: 32-D830, MIT Mailing Address: MIT Linguistics and Philosophy, 77 Massachusetts Avenue, 32-D808, Cambridge, MA 02139, USA

George Hripcsakمشاهده پروفایل

استاد

• Biomedical Informatics
• Electronic Health Records (EHRs)
• Data Mining
• +۴ مورد دیگر

George Hripcsak is the Vivian Beaumont Allen Professor of Biomedical Informatics and Director of Medical Informatics Services at New York-Presbyterian Hospital, Columbia University. He holds affiliations with the Vagelos College of Physicians and Surgeons and the Data Science Institute (DSI). His expertise spans clinical informatics, electronic health records (EHRs), and medical knowledge representation standards. Hripcsak earned degrees in chemistry, medicine, and biostatistics, and is a board-certified internist. Research focuses on leveraging EHR data for clinical research and patient safety through data mining and causal inference techniques. Notable contributions include the Arden Syntax (a national standard for medical knowledge representation) and leadership in the Observational Health Data Sciences and Informatics (OHDSI) network. He chairs the AMIA Standards Committee and has advised federal health informatics policies under HIPAA. His academic awards include Fellowships in the American College of Medical Informatics (1995) and New York Academy of Medicine. Current projects emphasize federated learning, genomic risk prediction, and large-scale real-world evidence analysis through initiatives like LEGEND-T2DM and All of Us Research Program. Educations: MD, Biostatistics, Chemistry Labs/Teams: OHDSI, DSI, Medical Informatics Services Grants & Funding: Not explicitly listed in provided texts