جست‌وجوی استاد و پژوهشگر

John Eckمشاهده پروفایل

استاد

• Criminology
• Problem-Oriented Policing
• Crime Prevention
• +۳ مورد دیگر

John Eck is a Professor at the University of Cincinnati's Department of Criminology. He earned his Ph.D. in Criminology from the University of Maryland in 1994. Prior to academia, he spent 17 years as Research Director at the Police Executive Research Forum, focusing on police reform and problem-oriented policing strategies. His work emphasizes practical crime prevention solutions rooted in rigorous research, including the development of guides for law enforcement and community initiatives. Eck played a pivotal role in the Cincinnati Collaborative Agreement, addressing racial discrimination in policing, for which he received the 2016 Collaborative Agreement Award and the Ronald V. Clarke Award in 2016. His research interests span problem-oriented policing, crime analysis, environmental criminology, and police reform. He has authored and co-authored numerous books and articles, including Problem-Solving Detective and Mapping Crime: Understanding Hot Spots . Eck teaches courses on policing and crime prevention, contributing to both academic and practitioner communities. Eck's publications reflect a focus on crime prevention strategies, evaluation methods, and policy implementation. His work often bridges theoretical frameworks with real-world applications, such as using GIS and crime mapping to identify and address high-crime areas. He has served on the National Academy of Sciences panel on police research and policy, further highlighting his influence in shaping criminal justice practices. Awards: 2016 Collaborative Agreement Award 2016 Ronald V. Clarke Award Grants and Advising: Eck has contributed to projects funded by the U.S. Department of Justice and the Police Foundation, though specific grant details are not disclosed here. His advisory role in the Cincinnati Collaborative Agreement exemplifies his commitment to bridging academic research and community action. Labs/Teams: Affiliated with the University of Cincinnati Criminal Justice Research Center, focusing on empirical studies of crime prevention and policing strategies.

Keith Conradمشاهده پروفایل

دانشیار

• Number Theory
• Algebraic Number Theory
• Analytic Number Theory
• +۳ مورد دیگر

Keith Conrad is an Associate Professor in the Department of Mathematics at the University of Connecticut (UConn), part of the College of Liberal Arts and Sciences. His research focuses on Number Theory, particularly in areas such as algebraic and analytic number theory, prime numbers, arithmetic geometry, and modular forms. He has published extensively on topics like congruent numbers, prime specialization, and the Möbius function. His work integrates classical number theory with modern algebraic techniques, contributing to foundational understanding in the field. Conrad is actively involved in academic outreach, organizing and teaching at programs like the Ross Mathematics Program and PROMYS. He has delivered lectures on advanced topics such as L-functions, the Riemann Hypothesis, and the ABC conjecture. His expository papers and teaching materials emphasize clarity and accessibility, bridging gaps between complex mathematical concepts and broader audiences. Conrad's academic contributions include significant publications in journals like *Mathematics Magazine* and *Journal für die reine und angewandte Mathematik*, as well as expository works on modular forms, prime patterns, and historical aspects of representation theory. He maintains a comprehensive website with resources for students and researchers, including detailed lecture notes, problem sets, and links to mathematical tools and software.

Tor Söderströmمشاهده پروفایل

استاد

• Sports Science
• Educational Technology
• Athlete Development
• +۳ مورد دیگر

Tor Söderström is a Professor at the Department of Education at Umeå University. His research focuses on learning and development in sports, computer simulation training, and professional knowledge development in police education. He has contributed extensively to understanding talent identification in sports, particularly in Swedish football, and the efficacy of simulation-based training methodologies in law enforcement education. His research spans topics including athlete development trajectories, the impact of physiological testing on elite athlete performance, and the role of childhood athletic ability in long-term sports participation. Notable projects include a study on dropout processes in Swedish football talent systems and analyses of Swedish gym-goers' training patterns over two decades. Publications highlight interdisciplinary approaches, combining sports science, sociology, and educational technology. Recent work explores children’s rights in sports through scoping reviews and examines athlete retention strategies from adolescence into adulthood. His research often emphasizes practical applications in training design and policy development for both sport and professional education sectors. No scientific awards are explicitly mentioned in the provided texts. His work has involved collaborations with institutions like the Swedish Football Association and police education programs, focusing on scenario-based training methodologies and competency development in high-stakes professions.

Garth Alperمشاهده پروفایل

استاد

• Jazz
• Jazz Piano
• Popular Music
• +۳ مورد دیگر

Dr. Garth Alper is a Professor and Program Coordinator for Jazz Studies at the University of Louisiana at Lafayette's School of Music and Performing Arts. He holds a Doctor of Arts in Music Theory/Composition from the University of Northern Colorado, a Master of Arts in Piano Performance (Jazz Track) from New York University, and a Bachelor of Professional Studies in Jazz Studies from SUNY Empire State College. His research focuses on Jazz Piano, Jazz History, and Popular Music, with notable contributions to understanding improvisation techniques, postmodernism in music, and the cultural legacy of jazz icons like Duke Ellington. Dr. Alper has authored numerous articles in journals such as College Music Symposium , Rock Music Studies , and Jazz Perspectives , and guest-edited a special jazz issue of Popular Music and Society . His music compositions are featured on multiple CDs, including the acclaimed Spider’s Web (2022) and Stratus (2017). He has received significant grants and awards, including the BORSF Endowed Professorship and funding for jazz pedagogy and recording projects. Education: Doctor of Arts in Music Theory/Composition (University of Northern Colorado) Master of Arts in Piano Performance (Jazz Track, New York University) Bachelor of Professional Studies in Jazz Studies (SUNY Empire State College) Research Contributions: Includes analysis of jazz improvisation, postmodern music theory, and the sociocultural impact of jazz. He has authored encyclopedia entries on influential jazz musicians and contributed to critical discussions on popular music pedagogy. Teaching & Courses: Teaches Jazz Piano, Jazz Theory, Jazz History, Film Scoring, and directs the Jazz Combo program. Courses include MUS 312: Jazz Theory I and MUS 438: Film Scoring I . Grants & Recognition: Over $100K in grants for recording projects, multimedia facilities, and pedagogical initiatives. Holder of the Ruth Stodghill Girard BORSF Endowed Professorship since 2001. Labs/Teams: Coordinates the Jazz Studies program and collaborates on projects blending jazz with film scoring and modern media.

LEE Mong Liمشاهده پروفایل

استاد

• Data Management
• Data Cleaning
• Data Fusion
• +۵ مورد دیگر

LEE Mong Li is a Professor of Computer Science at the National University of Singapore (NUS) and serves as Director of the NUS Centre for Trusted Internet and Community. She holds a Ph.D., M.Sc., and B.Sc. (First Class Honours) in Computer Science from NUS, where she was awarded the IEEE Singapore Information Technology Gold Medal as the top Computer Science student in 1989. Her academic career includes a visiting fellowship at the University of Wisconsin-Madison (1999) and consultancy with QUIQ USA (2000). Her research spans Data Management, Spatio-temporal Databases, Biomedical Informatics, and Retinal Image Analysis . She has pioneered work in data cleaning, data fusion, and analysis of semistructured data, with applications in social media analytics and healthcare. Her recent publications demonstrate strong interdisciplinary focus, particularly in AI-driven medical diagnostics including diabetic retinopathy screening and chronic kidney disease detection from retinal images. She co-authored foundational books on 'Designing Semi-structured Database' and 'Temporal and Spatio-Temporal Data Mining'. Her 150+ publications in major database conferences and journals reflect leadership in both theoretical and applied research. Recent work shows significant emphasis on Medical AI applications (retinal analysis, kidney disease prediction) Temporal fact verification systems Misinformation detection in multimodal environments Privacy challenges in large language models Key honors include: Singapore's President Technology Award (2014) for co-inventing an AI system screening eye conditions IEEE Singapore Information Technology Gold Medal (1989) She actively contributes to government-funded multidisciplinary projects building practical deployable systems. Her leadership extends to program committees of prestigious database conferences and directing the NUS Centre for Trusted Internet and Community. She teaches BT5110 Data Management and Warehousing and has co-developed an AI system for diabetic retinopathy screening deployed in Singapore's national teleophthalmology program.

Kristin Longمشاهده پروفایل

دانشیار

• Pediatric Psychology
• Health Disparities
• Psychosocial Interventions
• +۳ مورد دیگر

Kristin Long is an Associate Professor at Boston University and Director of the Child & Family Health Laboratory. She holds a PhD in Clinical and Biological-Health Psychology from the University of Pittsburgh (2012), completed postdoctoral training at Brown University’s Alpert Medical School, and joined BU in 2014. Her research focuses on the interplay between pediatric medical conditions, family dynamics, and cultural contexts, with emphasis on autism, cancer, intellectual disability, and asthma. Key areas include health disparities in autism care, psychosocial interventions for families, and sibling adjustment in chronic illness contexts. Education: PhD, Clinical and Biological-Health Psychology, University of Pittsburgh (2012) Clinical Internship & Postdoctoral Fellowship, Alpert Medical School of Brown University/Rhode Island Hospital Research interests: Family-cultural influences on child health outcomes Health equity in autism diagnosis/treatment Development of psychosocial interventions Cultural adaptations in healthcare delivery Her work has led to over 50 publications, emphasizing qualitative and mixed-methods approaches to understanding family experiences in pediatric chronic illness. Notable contributions include frameworks for sibling psychosocial care and culturally responsive interventions. Lab & Collaborations: Directs the Child & Family Health Lab, fostering community-academic partnerships to address unmet needs in pediatric healthcare. Active in developing nationwide standards for sibling psychosocial support in oncology care.

Fatma Denizمشاهده پروفایل

استاد

• Computational Neuroscience
• Neuroscience of Language
• Cognitive Science
• +۳ مورد دیگر

Fatma Deniz is a Full Professor (W3) of Computer Science at Technische Universität Berlin, supported by the Berlin Equal Opportunities Program. She leads the Chair of Language and Communication in Biological and Artificial Systems, and is a member of the Berlin Bernstein Center for Computational Neuroscience. Her roles include membership in TU Berlin's Executive Board and the Berlin University Alliance Steering Committee. She holds a Ph.D. (Dr. rer. nat.) from TU Berlin and a Diploma in Computer Science from Technische Universität München, with research training at Caltech and postdoctoral work at UC Berkeley. Her research focuses on understanding neural mechanisms of language processing, integrating computational neuroscience, cognitive science, and artificial intelligence. Key areas include semantic representation dynamics, cross-modal neural alignment, and language learning in bilingual contexts. She has pioneered studies showing the brain's invariant semantic processing across reading and listening modalities. Her grants include an ERC Starting Grant (2023-2028) for studying language learning shifts and a NSF-BMBF CRCNS grant on bilingual representations. She co-edited The Practice of Reproducible Research: Case Studies in Data Science (UC Press, 2017) and contributed to foundational work on reproducible data science methodologies. She has advised projects in neuroimaging, AI ethics, and computational linguistics, and collaborates with institutions like UCSF and the German Academic Exchange Service. Her lab explores neural correlates of language through fMRI, MEG, and machine learning techniques.

Ye Wangمشاهده پروفایل

استادیار

• Political Methodology
• Comparative Politics
• Public Policy
• +۳ مورد دیگر

Ye Wang is an Assistant Professor in the Department of Political Science at the University of North Carolina at Chapel Hill since 2022. He previously held postdoctoral and predoctoral research positions at UC San Diego’s School of Global Policy and Strategy (2020–2022). His research bridges political methodology and comparative politics, focusing on statistical tools for policy spillover effects, research transparency, and social learning under non-democratic regimes. He also explores electoral dynamics in contentious political contexts. Ye earned a PhD in Political Science from New York University (2021), with a committee including Nathaniel Beck, Matthew Blackwell, Adam Przeworski, Cyrus Samii, and Joshua Tucker. He holds an MA in Economics from Peking University (2014) and a BS in Mathematics from Fudan University (2011). He withdrew voluntarily from a concurrent PhD in Economics at the University of Wisconsin-Madison (2014–2015). His research interests emphasize causal inference methodologies and their application to understanding political phenomena in non-democratic settings. He develops statistical techniques to address interference in temporal, spatial, and networked data, while also studying how protests and international tensions impact political systems and scientific collaboration. Recipient of the John T. Williams Dissertation Prize (2020), Chiang Ching-kuo doctoral fellowship (2020), and NYU’s MacCracken fellowship (2015–2020). In advising and teaching, Ye has served as a teaching assistant for courses in political methods, comparative politics, and quantitative methods at NYU and the City University of Hong Kong. He has also taught workshops on quantitative methods at Renmin University and contributed to academic seminars at institutions like Yale and Tsinghua. His programming skills include C++, R, Python, GIS, and Stata, complementing his work in methodological research.

Jay Pujaraمشاهده پروفایل

عضو هیئت علمی

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

Jay Pujara is a Research Associate Professor in the Department of Computer Science at the University of Southern California (USC), affiliated with the Viterbi School of Engineering and the Information Sciences Institute (ISI). He directs the Center on Knowledge Graphs and leads research in artificial intelligence, specializing in knowledge graph construction, scalable machine learning, and probabilistic models. Education : PhD in Computer Science (University of Maryland, 2016), MS and BS in Computer Science from Carnegie Mellon University (2005 and 2004), with minors in Robotics, Mathematical Sciences, and Logic & Computation. Research Interests : His work focuses on probabilistic models for dynamic data, knowledge graph construction, entity resolution, and applications in NLP and social network analysis. He emphasizes scalable algorithms and real-world impact in domains like finance, climate science, and healthcare. Awards : Includes the SWSA Ten-Year Award (2023), Best Paper Awards at IUI 2019 and ISWC 2013, and grants totaling over $9M from DARPA, NSF, and industry partners. Grants & Mentorship : Principal Investigator on projects like "Artificial Domain-Understanding and Collaborative Agency" (DARPA) and "Explainable and Robust AI Agents" (NSF). Mentored over 50 students in PhD, MS, and undergraduate programs, focusing on knowledge graphs, NLP, and machine learning. Labs & Teams : Leads ISI’s Knowledge Graph and Neurosymbolic AI teams, coordinating the Open Knowledge Network (OKN) and tools like KGTK. Active in academic service, including roles on PhD admissions committees and ISI’s Space Management Committee.

Mylene Lagardeمشاهده پروفایل

دانشیار

• Health Economics
• Global Health
• Healthcare Policy
• +۳ مورد دیگر

Dr. Mylene Lagarde is an Associate Professor of Health Economics and Deputy Head of Department (Research) at the London School of Economics and Political Science (LSE), Department of Health Policy. Her research focuses on applied economic analysis of healthcare decisions in low- and middle-income countries (LMICs), particularly provider behavior, healthcare demand, and health policy evaluation. She has conducted studies on topics such as health worker incentives, user fee removal policies, and the impact of performance-based financing. She holds affiliations with J-PAL and the University of Witwatersrand, South Africa. Her work combines quantitative methods, randomized experiments, and policy analysis to inform global health interventions. Educated in France and with field experience in Cameroon, Lagarde’s academic career includes roles at the London School of Hygiene and Tropical Medicine before joining LSE in 2016. She teaches advanced health economics courses, including MPhil/PhD programs in Health Economics and Policy, and modules on randomized evaluations of health programs. Her research has explored provider behavior in Senegal, Zambia, South Africa, and other LMICs, addressing challenges like antibiotic overprescription, healthcare quality under workload pressures, and equitable access to services. Key areas of focus include the role of pro-social preferences in healthcare workforce distribution, the effectiveness of group incentives for preventive care, and the framing effects of health policies. She has contributed to understanding how financial and non-financial incentives shape healthcare provider performance and patient choices, with implications for improving health system efficiency and equity globally.

David Eatonمشاهده پروفایل

استاد

• Induced Seismicity
• Microseismic Monitoring
• Distributed Acoustic Sensing
• +۲ مورد دیگر

David Eaton is a Professor and former NSERC/Chevron Industrial Research Chair in Microseismic System Dynamics at the University of Calgary's Department of Geoscience. He holds a PhD in Geophysics from the University of Calgary (1992) and has published the textbook 'Passive Seismic Monitoring of Induced Seismicity'. Educational Background: PhD Geophysics, University of Calgary, 1992 MSc Geophysics, University of Calgary, 1988 BSc Geology and Physics, Queen's University, 1984 His research focuses on induced seismicity characterization, microseismic monitoring technology development, distributed acoustic sensing applications, physics-informed machine learning approaches, and lithospheric structure analysis. Current projects investigate earthquake triggering mechanisms during hydraulic fracturing and geothermal energy development. Publications show consistent focus on induced seismicity source characterization, monitoring methodologies, and geophysical applications for energy resource development. Recent work integrates machine learning with seismic monitoring to understand geological controls on induced seismicity. Scientific Awards: NSERC Synergy Award for Innovation (2020) J. Tuzo Wilson Medal, Canadian Geophysical Union (2020) CSEG Distinguished Lecturer (2019) Schulich School of Engineering Distinguished Collaborator (2019) University of Calgary Great Supervisor Award (2016) He leads the CREATE-REDEVELOP program training future leaders in responsible resource development and directs the microseismic research laboratory.

• Organoid Engineering
• Systems Biology
• Developmental Biology
• +۳ مورد دیگر

Keisuke Ishihara is an Assistant Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research focuses on engineering human brain and cardiac organoids using genetic, chemical, and computational approaches to uncover novel regulatory mechanisms and physical principles underlying tissue development. His lab is located at Biomedical Science Tower 3, with an office in room 10020A. Dr. Ishihara holds a PhD in Systems Biology from Harvard University. His work bridges synthetic biology, developmental biology, and biophysics to address fundamental questions in organogenesis and cellular morphogenesis. Recent research highlights include studies on BMP-mediated neural tube patterning in organoids and the biophysical dynamics of microtubule assemblies in large cells. Publications from his lab emphasize interdisciplinary approaches to understand cell size scaling, mitotic spindle dynamics, and self-organization in synthetic tissues. His team has contributed to advancements in organoid technology, uncovering dormant genetic programs and physical principles governing tissue architecture. Laboratory activities are centered at the University of Pittsburgh, collaborating with the School of Medicine's computational and systems biology initiatives. For more details, visit his lab website linked below.

Karen Bandeen-Rocheمشاهده پروفایل

استاد

• Biostatistics
• Gerontology
• Aging
• +۱۴ مورد دیگر

Karen Bandeen-Roche is a Professor and the Hurley-Dorrier Professor and Chair of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, with joint affiliations in the School of Medicine and the School of Nursing. She is a leading expert in biostatistical methodology, particularly in latent variable models, longitudinal analysis, and multivariate survival methods applied to aging and gerontology. Her research focuses on developing statistical models for unobservable processes such as frailty, resilience, and functional status in older adults. She has made significant contributions to the measurement of aging-related constructs and has extensive collaborative work in ophthalmology and neurology. Her methodological work includes mixture models, measurement error correction, and latent class modeling. The recent publications highlight a strong trend in gerontological biostatistics, with a focus on frailty, dementia risk, resilience, and multisystem physiological responses in aging. Her work integrates complex data from observational cohorts and clinical studies, often employing innovative latent variable frameworks to address measurement challenges in health outcomes. Scientific Awards and Honors: Marvin Zelen Leadership Award in Statistical Science (2016) Fellow of the American Statistical Association (2001) Brookdale National Fellow (1997) Golden Apple Award for Excellence in Teaching (2010) Garland Clay Award (1999) Chair, NIH BMRD Study Section (2006–2008) President, Eastern North American Region, International Biometric Society (2011–2013) Executive Board, International Biometric Society (2015–2022) Board of Directors, National Institute of Statistical Sciences (2020–2023) Karen Bandeen-Roche has been deeply involved in advising and training the next generation of researchers. She co-directs a training program in Biostatistics and Epidemiology of Aging and has received multiple teaching and mentoring awards. She has served on numerous academic committees, including appointments and promotions, faculty senate, and ethics committees at Johns Hopkins. Her grants and collaborative research span aging, dementia, ophthalmology, and cardiovascular health, often supported by NIH and other federal agencies. She leads the Center on Aging and Health and is actively involved in interdisciplinary research initiatives that bridge biostatistics, medicine, and public health. Her lab and research team focus on developing and applying advanced statistical methods to understand the biological and social determinants of healthy aging.

• Auralisation
• Room Acoustics
• Building Acoustics
• +۷ مورد دیگر

Univ.-Prof. Dr. rer. nat. Michael Vorländer is a full Professor and Chair of Technical Acoustics at the Institute of Technical Acoustics (ITA), Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Germany. He has been the head of the institute since 1996 and is a leading figure in acoustics research and academic leadership. His extensive service includes being President of the European Acoustics Association (EAA), the International Commission for Acoustics (ICA), the German Acoustical Society (DEGA), and elected President of the Acoustical Society of America (ASA) for 2024–2027. Education: Diplom-Physiker, RWTH Aachen (1984); Dr. rer. nat., RWTH Aachen (1989); Dr.-Ing. habil., TU Dresden (1995) Professional Leadership: Pro-Dean (2007) and Dean (2009) of Faculty of Electrical Engineering and Information Technology, RWTH Aachen; Spokesperson of Professors, RWTH Aachen (2012) Editorial Roles: Editor-in-Chief, Acta Acustica (1998–2003); Editorial Board, Applied Acoustics (since 1996) Michael Vorländer's primary research interests lie in the fields of auralization, room acoustics, building acoustics, psychoacoustics, acoustic measurement technology, and virtual acoustics . His work integrates physical acoustics with human perception, focusing on the simulation and reproduction of sound fields in virtual environments. He leads research in binaural technology, electroacoustics, and auditory scene analysis, with applications in noise research and interactive virtual environments. His group is involved in the Priority Program SPP2236 - AUDICTIVE, focusing on auditory cognition in interactive virtual settings. While specific recent publications are not listed, his research output is extensive, as indicated by links to filtered publications. His body of work consistently bridges theoretical modeling, experimental validation, and practical application in architectural and virtual acoustics, contributing to both engineering standards and perceptual understanding. Michael Vorländer has received numerous scientific awards recognizing his contributions to acoustics, including the prestigious RWB Stephens Medal, W.C. Sabine Medal, and Rayleigh Medal . He is a Fellow of the Acoustical Society of America and holds honorary memberships and awards from acoustical societies in Europe and beyond. He advises doctoral students and leads a multidisciplinary research team at the ITA, fostering collaboration in areas like acoustic virtual reality and spatial audio. His leadership in international societies and editorial boards highlights his role in shaping the global acoustics community. He has been instrumental in advancing research infrastructure and academic collaboration in technical acoustics. The research at his institute is organized into key areas: Acoustic Virtual Reality and Auralization, Binaural Technology and Spatial Audio, Auditory Scene Analysis, Psychoacoustics and Noise Research, Electroacoustics, and Room Acoustics. These labs and teams work on projects ranging from fundamental auditory perception to applied engineering solutions for noise control and virtual sound environments.

• Autism Spectrum Disorders
• Child Psychiatry
• Developmental Disabilities
• +۸ مورد دیگر

Katarzyna Chawarska is the Emily Fraser Beede Professor of Child Psychiatry at Yale School of Medicine, with primary affiliation in the Child Study Center and secondary appointments in Pediatrics and Statistics. She is a leading expert in autism spectrum disorders (ASD), directing the NIH Autism Center of Excellence, the Social and Affective Neuroscience of Autism Program, and the Yale Toddler Developmental Disabilities Clinic. Education: PhD in Psychology, Yale University (2000) Post-Doctoral Fellowship, Yale University School of Medicine (2000) MS in Psychology, Yale University MPhil in Psychology, Yale University MA, Jagiellonian University (1986) Her research focuses on identifying early diagnostic markers and novel treatment targets in ASD, particularly in infants at risk due to familial, genetic, or perinatal factors. Her work integrates clinical assessment, neuroimaging, eye-tracking, and longitudinal design to understand the neurodevelopmental trajectories of autism. Her recent publications explore disrupted functional connectivity, atypical visual attention, social anhedonia, and familial recurrence in autism. She employs advanced methodologies including fMRI, eye movement dynamics, and machine learning to identify biomarkers. Her research spans developmental neuroscience, clinical psychology, genetics, and pediatric psychiatry, with strong emphasis on early detection and intervention. Scientific Awards: No specific awards mentioned in the provided text. Dr. Chawarska is the Principal Investigator on active clinical trials, including studies on emotional development in infants at risk for ASD and regulation of visual attention and emotion in autism. She mentors research through her lab and collaborates extensively with experts such as Fred Volkmar, James McPartland, and Frederick Shic. She leads the Chawarska Lab, which is part of the Center for Brain & Mind Health and the Wu Tsai Institute at Yale.