جست‌وجوی استاد و پژوهشگر

Xuebin Weiمشاهده پروفایل

دانشیار

• Geographic Information Systems (GIS)
• Social Media Analysis
• Machine Learning
• +۴ مورد دیگر

Xuebin Wei is an Associate Professor of Geography at the College of Integrated Science & Engineering (CISE) at James Madison University (JMU). He holds a Ph.D. in Geography from the University of Georgia, complemented by advanced degrees in GIS and Urban Planning from Wuhan University and ITC at the University of Twente. Dr. Wei specializes in integrating geospatial technologies with social media analysis, machine learning, and cloud computing to address urban and environmental challenges. His research focuses on spatial-social networks, 3D urban modeling using LiDAR and aerial imagery, and applying social media data for disaster response and public health. Notable projects include the JMU Virtual 3D Campus and LBSocial initiative exploring geosocial data frameworks. Wei teaches courses in GIS, cloud computing (AWS), programming for data science, and machine learning. His publications span topics like election prediction using Twitter data, spatial analysis of climate phenomena (El Niño), and optimizing urban transit infrastructure. While no specific awards are listed, his work reflects interdisciplinary innovation at the intersection of geography, technology, and society. He advises students in CISE's data science and geospatial programs through courses like IA340 Data Mining and GEOG215 Cartography.

Richard Lewisمشاهده پروفایل

استاد

• Cognitive Science
• Linguistics
• Computational Linguistics
• +۵ مورد دیگر

Richard Lewis is the John R. Anderson Collegiate Professor of Psychology, Linguistics, and Cognitive Science at the University of Michigan. He directs the Weinberg Institute of Cognitive Science, a hub for interdisciplinary research. His work focuses on computational models of human cognition, particularly language processing architectures, and he co-founded the cognitive science undergraduate major at U-M. Lewis was honored as an Arthur F. Thurnau Professor (2021) for his transformative contributions to undergraduate education. Education: Ph.D., Carnegie Mellon University Research interests span cognitive neuroscience, psycholinguistics, and computational linguistics. His projects investigate how humans process sentences cross-linguistically and adapt predictive models during comprehension. Notable achievements include developing programs that integrate computer science, philosophy, and psychology to study the mind. His articles explore topics ranging from neural noise effects on decision-making to AI's capacity for analogical reasoning. Awards include the Thurnau Professorship, recognizing his dedication to student engagement and curriculum innovation. Lewis advises on interdisciplinary initiatives at the Weinberg Institute and collaborates on projects like icon array communication for public health. His work bridges theoretical models with empirical studies, emphasizing the computational foundations of human cognition.

• Nonparametric function and density estimation
• Shape-restricted inference
• Constrained regression models
• +۲ مورد دیگر

Mary C. Meyer is a Professor in the Department of Statistics at Colorado State University. Her research focuses on nonparametric function and density estimation, particularly under shape restrictions, with applications across ecological modeling, survey methodology, and statistical computing. Education: Ph.D. in Statistics from the University of Michigan (1996) Research Interests: Nonparametric function and density estimation Shape-restricted inference Constrained regression models Bayesian nonparametric methods Penalized isotonic regression Statistical software development Recent Publications show a focus on constrained regression splines, domain mean estimation, and applications in forest dynamics and survey methodology. She has developed several R packages including cgam and tools for cone projections. Grants: Funded by NSF grant DMS-0905656 for research on constrained optimization algorithms. Email Contacts: meyer@stat.colostate.edu and mmeyer@stat.uga.edu

Prasad Tadepalliمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۵ مورد دیگر

Prasad Tadepalli is a Professor in the School of Electrical Engineering and Computer Science at Oregon State University, serving as the AI Graduate Program Director. He is affiliated with the Collaborative Robotics and Intelligent Systems Institute. His expertise spans artificial intelligence, machine learning, reinforcement learning, and automated planning, with impactful contributions to explainable AI and natural language processing. Tadepalli holds a Ph.D. from Rutgers University and M.Tech/B.Tech degrees from Indian institutions. He has authored over 100 papers, organized international conferences, and received awards such as the AAAI Outstanding Paper Award (2013) and ICAPS Best Student Paper (2009). Education: Ph.D. (Rutgers University, 1990), M.Tech (IIT Madras, 1981), B.Tech (Regional Engineering College, 1979) His research focuses on advancing AI through techniques like relational planning, reinforcement learning, and interpretable models. Recent work includes integrating planning and RL for multiagent systems and developing explainable models via tree ensemble compression. His articles highlight contributions to time-series imputation, adversarial attacks on bandits, and chess rating estimation using CNN-LSTM networks. Awards: AAAI Outstanding Paper Award (2013), ICAPS Best Student Paper (2009) Tadepalli emphasizes independent thinking in students and has advised numerous researchers. His work bridges theoretical AI with practical applications, such as robotics and data-driven decision-making.

Xiaojun Yuanمشاهده پروفایل

دانشیار

• Human Computer Interaction
• Information Retrieval
• User Interface Design
• +۳ مورد دیگر

Xiaojun (Jenny) Yuan is an Associate Professor at the University at Albany, State University of New York, within the College of Emergency Preparedness, Homeland Security, and Cybersecurity. Her research focuses on Human-Computer Interaction (HCI) and Information Retrieval, emphasizing user interface design and human information behavior. She has secured grants from institutions like the Institute of Museum and Library Services and the New York State Education Department. Dr. Yuan holds a Ph.D. from Rutgers University and the Chinese Academy of Sciences, alongside advanced degrees in Statistics and Computer Science. She actively contributes to professional committees (e.g., ACM SIGIR, ASIS&T) and editorial boards, including the Aslib Journal of Information Management and Annual Review of Information Science and Technology . Her work addresses technology accessibility, pandemic response systems, and inclusive design for marginalized populations. Her research spans decades, with notable contributions to voice search optimization, cultural aspects of interface design, and technology adoption patterns during crises. Recent studies investigate algorithmic fairness, privacy concerns in aging populations, and pandemic-era educational technology. Dr. Yuan's interdisciplinary approach bridges computer science, sociology, and public health to tackle real-world challenges like health equity and emergency preparedness. Grants: Institute of Museum and Library Services, SUNY Seed Grant, NY State Education Department Editorial Roles: Aslib Journal of Information Management, Annual Review of Information Science and Technology Professional Memberships: ASIS&T, ACM, IEEE Her publications highlight trends in conversational search systems, gamified learning tools, and the societal impacts of AI. Ongoing research explores culturally responsive keyboard designs and pandemic data visualization for underrepresented groups.

Mark T. W. Ebbertمشاهده پروفایل

دانشیار

• Alzheimer's Disease
• Neurodegenerative Disorders
• Genetics
• +۵ مورد دیگر

Mark T. W. Ebbert, PhD, is an Associate Professor at the University of Kentucky's Sanders-Brown Center on Aging, where he leads the Ebbert Lab. His work focuses on developing biomarkers for neurodegenerative diseases, particularly Alzheimer's disease (AD), leveraging cutting-edge genomic and transcriptomic techniques. He co-leads efforts in the Alzheimer's Disease Research Center's Biomarker Core, aiming to integrate neuroimaging, fluid biomarkers, and genomic data for precision medicine applications. Key research interests include analyzing genetic variants, long-read sequencing for disease resilience, and understanding inflammation's role in neurodegeneration. He has presented at high-profile venues like the Markesbery Symposium, discussing topics such as using long-read sequencing to identify AD biomarkers. His lab has produced over 55 publications, with a focus on resolving genomic 'dark regions' and improving biomarker accuracy through innovative methods like RNApysoforms visualization tools. Collaborating with interdisciplinary teams, Dr. Ebbert explores the interplay between genetics, epigenetics, and environmental factors in neurodegenerative diseases. His work bridges basic science and clinical translation, emphasizing the importance of genomic data integration for advancing AD diagnosis and treatment strategies.

Chia-Fang (Christina) Chungمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Health Informatics
• Personal Informatics
• +۷ مورد دیگر

Chia-Fang (Christina) Chung is an Associate Professor in Computational Media at the University of California, Santa Cruz. Her research bridges Human-Computer Interaction (HCI) and health/well-being, focusing on ubiquitous computing and personal informatics to enhance relationships, motivate health behavior, and support clinical care. Previously, she served as an Assistant Professor in Informatics at Indiana University Bloomington. Her academic journey includes a Ph.D. in Human-Centered Design and Engineering from the University of Washington under advisor Sean Munson, and an MBA/BBA in Information Management from National Taiwan University. Education: Ph.D. in Human-Centered Design and Engineering, University of Washington MBA and BBA in Information Management, National Taiwan University Christina's research explores technology's role in family wellness, chronic disease management, and patient-provider collaboration. Key projects include Supporting Healthy Eating in Families (NSF-funded), Sharing Lifelog Data with Healthcare Experts (AHRQ-funded), and Adoption of Blood Pressure Kiosks with UW Medicine. Her work emphasizes contextual inquiry, mixed-methods studies, and translational tools for societal resilience. Scientific Awards: BEST PAPER AWARD (TOP 1%) at CHI 2024 BEST PAPER HONORABLE MENTION (TOP 5%) at DIS 2018 BEST WORK-IN-PROGRESS AWARD at DIS 2023 Christina collaborates with institutions like Robert Wood Johnson Foundation and Reos Partners. Her students include Seung Wan Ha, Chun Han Wang, and Yu-Ling Chou. She holds patents for lifestyle progression models and health management frameworks, with media coverage in KION News and CNN.

Erin R Ottmarمشاهده پروفایل

دانشیار

• Mathematics Education
• Educational Psychology
• Perceptual Learning
• +۲ مورد دیگر

Dr. Erin R. Ottmar is an Associate Professor of Psychology and Learning Sciences at Worcester Polytechnic Institute (WPI), affiliated with the Department of Social Science & Policy Studies. She directs the MAPLE (Math Abstraction Play Learning Embodiment) Lab, focusing on educational technology and mathematics cognition. She holds a BA in Psychology and Elementary Education from the University of Richmond (2005) and a PhD in Educational Psychology: Applied Developmental Science from the University of Virginia (2011). Her postdoctoral training was completed at the University of Richmond. Her research integrates educational, cognitive, and developmental psychology to design interventions improving mathematics teaching/learning. Key projects include developing dynamic educational technologies like From Here to There and Graspable Math that embed perceptual learning and gesture-based interaction. Her current work examines how cognitive and non-cognitive pathways combine to enhance K-12 mathematics education, using classroom observations, longitudinal data, and multi-level modeling. Publications demonstrate consistent focus on: Perceptual learning mechanisms in mathematics Educational technology efficacy Classroom implementation studies Game-based learning analytics Cognitive factors in mathematical reasoning Awards include: NSF CAREER Award (2022) Sigma Xi Outstanding Junior Faculty Researcher Award (2022) AERA Early Career Fellow (2016) She actively mentors graduate/undergraduate students in the LST program and Psychology department. Major grants include NSF funding for projects on perceptual cues in algebra learning ($668K) and AI-supported teacher tools. She emphasizes interdisciplinary collaboration and real-world applications in her lab.

Anuj Sharmaمشاهده پروفایل

استاد

• Big Data Analytics in Transportation
• Data-Driven Decision Making
• Traffic Signal Systems
• +۳ مورد دیگر

Dr. Anuj Sharma is a Professor in the Department of Civil, Construction, and Environmental Engineering at Iowa State University, serving as Co-Director of the REACTOR Lab and Director of FAST-TrAC. He holds affiliations with InTrans, CTRE, and REACTOR, and is CEO of ETALYC Inc. His research focuses on big data analytics, traffic signal systems, and real-time transportation decision-making. Education: PhD in Civil Engineering, Purdue University, 2008 MS in Civil Engineering, Texas A&M University, 2004 BE in Civil Engineering, Regional Engineering College, Rourkela, India, 2001 Research Interests: Dr. Sharma’s work leverages big data to improve transportation systems, including real-time analytics, traffic signal optimization, and smart rural infrastructure. His lab, REACTOR, integrates multiple data streams for policy and operational decisions. Publications: His recent work spans driver behavior analysis, autonomous systems, and traffic safety, with a focus on data-driven solutions. Notable projects include congestion modeling and pandemic-era traffic adaptations. Awards: Social Analytics Strategic Network (SASNet) Fellow, 2016 Outstanding Reviewer (Journal of Transportation Engineering), 2014 Pikarsky Award for PhD Dissertation, 2008 Grants & Projects: Secured over $13M in funding for 32+ projects, including work on adaptive traffic control, AI-driven data analysis, and rural safety. Active roles in TRB committees and journal reviewing highlight his leadership in the field. Labs & Teams: Leadership at REACTOR Lab drives innovations in transportation data management and real-time systems, collaborating with agencies like Iowa DOT.

Tyanna J. Buieمشاهده پروفایل

دانشیار

• Printmaking
• Public Art
• Community Engagement
• +۳ مورد دیگر

Tyanna J. Buie is an Associate Professor at the Rhode Island School of Design (RISD) , specializing in Printmaking . She holds an MFA from the University of Wisconsin–Madison and a BA from Western Illinois University. 2012 Mary L. Nohl Fellowship 2015 Joan Mitchell Painters & Sculptors Grant 2019 Kresge Artist Fellowship 2020 Fellowship.art award 2023 Ruth Arts/Mary L. Nohl Alumni Award Buie's research explores community identity through printmaking , public installations , and urban design . Her work bridges residential neighborhoods (e.g., Harambee and Riverwest) with visual storytelling , often incorporating graffiti and archival materials . Recent projects like "Revisionist History" (2024) and "Streetlights" (2015) highlight her focus on memory , social cohesion , and identity politics . Her exhibitions and public works span institutions such as the Highpoint Center for Printmaking , Detroit Institute of Arts , and Joan Mitchell Center . Collaborative grants from the Greater Milwaukee Foundation , Kresge Foundation , and Milwaukee Arts Board underscore her commitment to community-driven art . Buie’s work appears in collections like the Stanley Museum of Art and publications including Hyperallergic and New American Paintings .

Sean C. Rifeمشاهده پروفایل

استاد

• Moral and Political Psychology
• Metascience
• Sociology of Science
• +۵ مورد دیگر

Sean C. Rife is Professor of Psychology at Murray State University, co-founder of scite.ai, and Head of Academic Relations at Research Solutions, Inc. His work focuses on moral/political psychology, metascience, and AI's role in research evaluation. PhD in Psychology (Kent State University, 2014) MA in Sociology (East Tennessee State University, 2009) MA in Experimental Psychology (East Tennessee State University, 2008) BS in Psychology (North Georgia College and State University, 2005) His research explores ideology-personality connections, social media's influence on moral expression, and AI-driven tools to quantify scientific progress. He advocates for open science practices and has led large-scale replication efforts across multiple countries. Key projects include scite (AI-enhanced citation analysis), statcheck implementation, and TAPAS text similarity analysis. He has developed tools like psyLex and liwcR for linguistic analysis and research evaluation. Recent publications focus on terror-management theory validation, political orientation's impact on pandemic perception, and AI applications for citation classification. His work intersects psychology, data science, and academic technology development. Contact: Office: 209 Wells Hall, Murray State University Email: srife1@murraystate.edu, srife@researchsolutions.com Phone: 270-809-4404

Jonathan Lazarمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Digital Accessibility
• Disability Rights and Policy
• +۴ مورد دیگر

Dr. Jonathan Lazar is a Professor in the College of Information Studies (iSchool) at the University of Maryland, where he serves as Executive Director of the Maryland Initiative for Digital Accessibility (MIDA) and core faculty in the Human-Computer Interaction Lab (HCIL). He previously held a professorship at Towson University, where he founded the Universal Usability Lab and directed the information systems program. His work bridges human-computer interaction (HCI), disability rights, and legal policy to advance digital accessibility for marginalized populations, particularly blind users, individuals with cognitive impairments, and people with Down syndrome. Education: LL.M. (Disability Rights Law, University of Pennsylvania), Ph.D. (Information Systems, UMBC), M.S. (Information Systems, UMBC), B.B.A. (Management Information Systems, Loyola University Maryland). Research Focus: Dr. Lazar's work emphasizes ICT accessibility in developing countries, non-visual modalities for blind users, ballot accessibility for voters with disabilities, and legal frameworks to enforce accessibility standards. He has authored/co-authored 17 books and over 200 peer-reviewed articles, with notable contributions on accessible data visualization, automated accessibility testing, and the intersection of law and technology. Awards: Includes the ACM SIGACCESS Outstanding Contribution Award (2020), ACM SIGCHI Social Impact Award (2016), and multiple University System of Maryland Board of Regents Awards. His research has influenced U.S. federal regulations, including airline website accessibility mandates following his work on discriminatory pricing for blind travelers. Professional Service: Serves on the executive board of the Friends of the Maryland Library for the Blind, co-chairs the Cambridge Workshop on Universal Access and Assistive Technology (CWUAAT), and advises government agencies on accessibility policy. He advocates for inclusive design in public libraries, voting systems, and educational technologies. Labs & Projects: Leads the Trace R&D Center's legacy work on accessibility, co-designs health IT tools with individuals with Down syndrome, and develops tools like FormA11y for PDF accessibility remediation. His research emphasizes translating academic findings into actionable policies and practices.

• Cryo-electron microscopy/tomography
• Cell motility
• Cellular energy metabolism
• +۳ مورد دیگر

Jack Zhang is an Assistant Professor in the Department of Molecular Biophysics and Biochemistry at Yale School of Medicine. His research focuses on developing advanced cryo-electron microscopy/tomography (cryo-EM/ET) methods to investigate dynamic molecular machines in cellular contexts, particularly mechanisms of cell motility and energy metabolism. PhD in Biophysics from Institute of Biophysics (CAS) Postdoctoral work at MRC Laboratory of Molecular Biology Joined Yale faculty in 2019 Research interests include: Mechanistic analysis of dynein motor proteins Structural studies of mitochondrial respiratory supercomplexes Cytoskeletal repair mechanisms via Abl2-tubulin interactions Environmental signal response in mastigoneme assembly Allostery in microtubule transport activation Recent publications demonstrate expertise in: High-resolution in situ structural biology Tomographic analysis of cellular machines Mechanochemical cycle mapping Male infertility structural pathology Contact: jack.zhang@yale.edu

Xue Linمشاهده پروفایل

دانشیار

• Robust and Secure Machine Learning
• Deep Learning on the Edge
• Cyber-Physical Systems
• +۳ مورد دیگر

Xue Lin is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University, with a courtesy appointment in Khoury College of Computer Science. She joined Northeastern in 2017 and holds a PhD from the University of Southern California (2016) and a bachelor’s from Tsinghua University. Her research focuses on robust and secure machine learning, deep learning on edge devices, and cyber-physical systems. She leads the High Energy-Efficiency & Performance System Lab, which develops efficient algorithms and systems for applications like autonomous vehicles and medical AI. Dr. Lin’s work is supported by NSF, DARPA, and the U.S. Department of Transportation, among others. Notable achievements include a $1M DARPA grant for adversarial diagnosis systems, a 1st Place ISLPED 2020 Design Contest win, and multiple best paper awards. She has advised students such as Kaidi Xu (PhD’21), Mengshu, and Siyue, who have contributed to impactful projects like adversarial T-shirt attacks and FPGA-based DNN accelerators. Her research also addresses security in autonomous systems and inclusive design challenges for older and visually impaired passengers. Key grants include NSF CPS Small Awards, SaTC Medium Awards, and collaborations with institutions like the University of Maine and Michigan State University. Awards include the 2024 Faculty Fellow Award and recognition in Stanford’s top 2% cited scientists. Her lab’s projects span secure autonomous systems, energy-efficient inference frameworks (e.g., GRIM), and robust neural network verification techniques.

Jason Criderمشاهده پروفایل

استادیار

• Digital Rhetoric
• Disability Studies
• Digital Humanities
• +۵ مورد دیگر

Jason Crider is an Assistant Professor in the English Department at Texas A&M University. He specializes in digital rhetoric, disability studies, and environmental communication. His work examines the intersection of mixed-reality technologies, prosthetic media, and ecological discourse through a posthumanist lens. Crider holds a PhD from the University of Florida and has published extensively on augmented reality (AR) rhetorics, mobile media, and media ecology. His research explores how emerging technologies reshape human-environment relationships and bodily experiences. His publications analyze topics like AR's algorithmic persuasion mechanisms, Pokémon Go's ecological representations, and Disney's memorial tourism through AR. His writing frequently addresses ethical implications of digital media in disability and environmental contexts. Crider's research areas include digital humanities, critical AI studies, technical writing, and medical rhetoric. He has contributed to journals like Computers and Composition, ISLE, and Kairos, focusing on media's role in shaping contemporary cultural narratives.