جست‌وجوی استاد و پژوهشگر

Benjamin S. Baumerمشاهده پروفایل

استاد

• Data Science
• Sports Analytics
• Network Science
• +۵ مورد دیگر

Benjamin S. Baumer is a Professor in the Statistical & Data Sciences program at Smith College , where he has been teaching since 2012. He previously served as the first full-time Statistical Analyst for the New York Mets from 2004 to 2012, pioneering data-driven approaches in baseball operations. Education: Ph.D. in Mathematics, The Graduate Center of the City University of New York (2012) M.A. in Mathematics, University of California, San Diego B.A. in Mathematics, Wesleyan University His research spans multiple domains: Sports Analytics (sabermetrics, player evaluation, game simulation) Data Science Education (curriculum development, reproducible analysis tools) Network Science (graph theory, complex systems) Statistical Computing (R programming, tidyverse workflows) Recent publications highlight: Advancements in reproducible analysis (infer package, 'Fertile' framework) Educational innovations in team-based data science and ethics integration Tools for election data (fec16 package) and collaborative learning (Slack applications) Scientific Recognition: 2016 Contemporary Baseball Analysis Award (SABR) 2019 Waller Education Award (ASA) 2019 Significant Contributor Award (ASA Section on Statistics in Sports) Accredited Professional Statistician™ since 2014 (American Statistical Association) He co-organizes the annual ASA Five College DataFest and contributes to expanding data science pathways for community college students.

• ADHD research
• Psychosocial treatments for children
• School-home behavioral interventions
• +۶ مورد دیگر

Linda Pfiffner, PhD is a Professor in Residence at the University of California, San Francisco (UCSF) in the Department of Psychiatry within the School of Medicine. She serves as Director of the Hyperactivity, Attention and Learning Problems (HALP) Program at UCSF Weill Institute for Neurosciences. Prior to joining UCSF in 2001, she held academic appointments at UC Irvine and the University of Chicago. Dr. Pfiffner received her BA in Psychology from UCLA in 1981 and her PhD in Clinical Psychology from the State University of New York at Stony Brook in 1987. She also completed Diversity, Equity and Inclusion Champion Training at UCSF in 2021. Her research focuses on developing and evaluating collaborative school-home psychosocial treatments for children with ADHD, particularly the inattentive presentation. She has pioneered several evidence-based interventions including the Child Life and Attention Skills (CLAS) Program and the Collaborative Life Skills Program (CLS), which have been evaluated through rigorous randomized controlled trials. Her work integrates behavioral interventions with digital health technologies to improve accessibility and implementation in school settings. Dr. Pfiffner's recent publication portfolio demonstrates a strong emphasis on implementation science, cross-cultural adaptation of interventions (particularly in Mexico), digital health tools for ADHD treatment, and understanding factors that influence treatment adherence and outcomes. Her research increasingly incorporates technology-enhanced approaches and examines cultural and familial factors that impact intervention effectiveness. 2012 CHADD Hall of Fame Award 2009 CHADD ADHD and Family Issues Award 2004 CHADD Innovative Program of the Year Award President, Past President of International Society for Research in Child and Adolescent Psychopathology (2017-2021) Dr. Pfiffner serves as Director of the Clifford Attkisson Clinical Services Research Training Program, an NIMH-funded T32 that supports postdoctoral scholars pursuing careers in mental health services research. Her research has been continuously funded for over 25 years through multiple grants from NIMH and the Institute of Education Sciences (IES), including several current projects extending through 2028-2029 that focus on digital health solutions, cross-cultural implementation, and remote training for school mental health providers. She leads the Hyperactivity, Attention and Learning Problems (HALP) Program and has developed several evidence-based interventions including the Child Life and Attention Skills (CLAS) Program and the Collaborative Life Skills Program (CLS). Her current work focuses on adapting these interventions through digital platforms to increase accessibility and implementation in school settings across diverse cultural contexts.

Stephanie S Cemanمشاهده پروفایل

استاد

• Neurobiology
• Protein-Nucleic Acid Interactions
• Regulation of Gene Expression
• +۵ مورد دیگر

Stephanie S Ceman is a Professor at the University of Illinois with multiple appointments across the institution. She holds professorial positions in the Department of Cell and Developmental Biology, Biomedical and Translational Sciences, Neuroscience Program, and Beckman Institute for Advanced Science and Technology, while also serving as an Affiliate of the Carl R. Woese Institute for Genomic Biology. Dr. Ceman's educational background includes: B.S. in Bacteriology from the University of Wisconsin-Madison Ph.D. in Genetics from the University of Wisconsin-Madison Postdoctoral fellow at the University of Chicago Postdoctoral fellow at Emory University Her research focuses on neurobiology, protein-nucleic acid interactions, and regulation of gene expression , with particular emphasis on neurological and behavioral disorders. Dr. Ceman investigates the molecular basis of disease, post-translational modifications, and RNA-protein interactions, with MOV10 RNA helicase as a central subject of her research. Her work demonstrates that MOV10 is essential for embryonic development and neuronal branching, functioning as a cofactor for both the microRNA pathway protein AGO2 and Fragile X protein FMRP. Analysis of Dr. Ceman's publication record shows a consistent research trajectory centered on RNA helicase MOV10 and its critical role in neuronal function. Her recent work explores how MOV10 binds to RNA G-quadruplexes to modulate AGO2 association with MicroRNA Recognition Elements, using engineered mouse lines to investigate MOV10's impact on brain development and behavior. This research bridges molecular neuroscience, RNA biology, and neurological disorder mechanisms. Dr. Ceman has been recognized for excellence in instruction, as noted in university press releases highlighting award recipients for teaching excellence. Dr. Ceman actively mentors students and researchers in her laboratory, teaching courses including MCB 474 (Genetic Disorders & Counseling) and MCB 493 (Special Topics in Molecular and Cell Biology). Her research program has produced 44 scholarly outputs, demonstrating sustained productivity in her field. Her laboratory employs advanced techniques including individual nucleotide Crosslinking Immunoprecipitation (iCLIP) to map MOV10's interactions with neuronal mRNAs. Current research directions include investigating how MOV10 phosphorylation regulates its RNA unwinding activity and how MOV10 influences dendrite development through Dicer1 regulation.

Jonathan Weinerمشاهده پروفایل

استاد

• Health Services Research
• Health Care Policy Analysis
• Population Health Informatics
• +۷ مورد دیگر

Jonathan Weiner is a Professor in the Department of Health Policy and Management at Johns Hopkins University's Bloomberg School of Public Health. He also holds affiliations with the School of Medicine and serves as a key researcher at the Center for Health Services and Outcomes Research (CHSOR) and the Center for Population Health Information Technology (CPHIT). DrPH from Johns Hopkins University (1981) Former Director of JHU Health Services Research & Policy PhD Program (1999-2013) Past President of Bloomberg School's Faculty Senate (2003-2004) Professor Weiner's research spans health services research, health policy analysis, and health informatics with specific expertise in electronic health records, quality of care assessment, case-mix and risk-adjustment methodologies, primary/ambulatory care delivery, population health management, managed care systems, health workforce planning, and international health care comparisons. His work bridges the gap between health information technology and practical population health applications. Analysis of his recent publications (2017-2025) shows a strong focus on health equity, predictive modeling, social determinants of health, and the application of health information technology to improve population health outcomes. His work increasingly addresses algorithmic bias in healthcare predictive models, digital health equity frameworks, and innovative approaches to social needs assessment through electronic health records. Academy Health Impact Award (2015) for R&D with greatest impact on health and health care Atlantic Fellow in Public Policy (awarded by British Government, 1999) Fellow of AcademyHealth (formerly Academy for Health Services Research and Policy) Member of Medicare Coverage Advisory Committee (2004-2009) Member of National Blue Cross/Shield Research Advisory Committee (2003-2006) Professor Weiner has served on numerous quality and health IT expert panels at the National Quality Forum (NQF), National Committee for Quality Assurance (NCQA), and Centers for Medicare & Medicaid Services (CMS). He has been a frequent guest and commentator on national and local NPR radio shows and local PBS Television, translating complex health policy issues for broader audiences. His research has been consistently productive, with publication records spanning from 1979 through 2025, demonstrating sustained scholarly contribution to the field. He leads significant research projects including the Johns Hopkins ACG® System for case-mix and predictive modeling, development of measures for care coordination using electronic health records, and studies on health outcomes of bariatric surgery in individuals with type 2 diabetes. His work has established him as a leading expert in population health informatics and health services research methodology.

• Gait analysis (kinematics and kinetics)
• Osteoarthritis
• Longitudinal Data Analysis
• +۵ مورد دیگر

Dr. Nikae te Moller is an Assistant Professor at the Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University. Her research focuses on equine musculoskeletal health , combining gait analysis (kinematics/kinetics), osteoarthritis progression in equine joints, and longitudinal data analysis . She employs advanced techniques like facial electromyography (fEMG) and R programming for statistical analysis, with applications in science communication (e.g., public dance demonstrations of joint dynamics). Expertise in equine cartilage injury models (blunt vs. sharp lesions) Developed equine carpal groove model for osteoarthritis studies Innovator in optical coherence tomography (OCT) and near-infrared spectroscopy for cartilage assessment Recent publications (2024-2023) emphasize quantitative MRI , micro-CT , and infrared spectroscopy for early detection of cartilage defects. Her work bridges regenerative medicine and equine locomotion , with collaborations across biomedical engineering (e.g., 3D T1 relaxation time studies) and veterinary science. Awards include the Public Engagement Seed Fund . Current projects involve objective pain quantification and biomechanical response to treadmill exercise in horses.

Ewelina Smoktunowiczمشاهده پروفایل

استاد

• Occupational Health Psychology
• E-Health Interventions
• Stress Management
• +۷ مورد دیگر

Prof. Ewelina Smoktunowicz is a faculty member at SWPS University, serving as Head of StresLab: Stress Research Center and Head of the Department of New Technologies in Social Applications within the Faculty of Design in Warsaw. She specializes in designing and evaluating internet-based interventions for occupational health, with a focus on psychological resources like self-efficacy and social support in stress management across work and personal life. Her research spans e-health, digital mental health, and work-life balance. She leads projects including SMILE: Supporting Mental Health in Young People Med-Stres: Online Stress Management for Medical Professionals Med-Stres SOS: Emergency Psychological Support for Healthcare Workers Not Just Work: Expanding JD-R Model to Life Resources E-COMPARED: European Comparative Research on Online Depression Scientific awards include the Minister of Science Scholarship and Bekker Program for outstanding researchers. She has secured grants from the National Science Center (NCN) , National Center for Research and Development (NCBR) , and the European Commission . As Coordinator of E-health: Internet Interventions specialization in the Psychology and Computer Science Program, she bridges psychology and technology to enhance intervention effectiveness. Her lab, StresLab , focuses on stress dynamics across professions and life domains.

• Probabilistic machine learning
• Bayesian experimental design
• Causal inference
• +۴ مورد دیگر

Desi R. Ivanova is a research fellow at the University of Oxford's Department of Statistics under the Florence Nightingale Bicentennial Fellowship. Her work bridges probabilistic machine learning, Bayesian experimental design, and LLM evaluation frameworks. She holds a DPhil in Statistics from Oxford's StatML CDT program (2020-2024) and an MMORSE in Mathematics from University of Warwick (2011-2016) with Erasmus exchange at LMU Munich. Research spans causal machine learning and uncertainty quantification Developed CO-BED and Step-DAD frameworks Focus on LLM evaluation methodology and calibration Expert in real-time adaptive experimental systems Her publications demonstrate expertise in Bayesian self-consistency methods, neural data compression, and privacy-preserving dataset merging. Key contributions include improving amortized inference efficiency and developing gradient-based causal experimental designs. Current work emphasizes rigorous statistical evaluation of language models, advocating for appropriate uncertainty quantification when analyzing performance across small datasets. She critiques CLT-based methods for LLM evaluation and proposes more robust frequentist and Bayesian alternatives.

Venu Akuthotaمشاهده پروفایل

استاد

• Spine Disorders
• Sports Medicine
• Pain Medicine
• +۳ مورد دیگر

Dr. Venu Akuthota serves as Professor and Chair of Physical Medicine and Rehabilitation at the University of Colorado, holding the CU Medicine Endowed Chair in PM&R while directing the Spine Center at University of Colorado Hospital. Board-certified in sports medicine, electrodiagnostic medicine, pain medicine, and physical medicine and rehabilitation, he maintains clinical practices at UCHealth Spine Center and Cherry Creek Medical Center. His educational background includes: MD from Northeastern Ohio Universities Colleges of Medicine and Pharmacy (1994) BS from Northeastern Ohio Universities College of Medicine (1991) Internship, Residency, and Fellowship at McGaw Medical Center of Northwestern University Program (1995-1999) Dr. Akuthota's research centers on spine disorders with emphasis on spinal stenosis, low back/neck pain mechanisms, and functional outcomes following interventions. His clinical expertise spans sports medicine (particularly running injuries), interventional pain procedures, and preventive rehabilitation strategies. As team physician for University of Colorado and Denver sports programs, he integrates athletic performance with spine health. Analysis of his recent publications reveals dominant focus on spine intervention safety, steroid injection protocols, and telemedicine applications for spine care. Key trends include adrenal function monitoring in injection therapy, regenerative medicine applications, and interdisciplinary approaches to low back pain management through evidence-based frameworks. His scientific recognition includes: Multiple-year recipient of 5280 "Top Doc" award Dr. Akuthota has secured significant research funding for studies on lumbar radiculopathy outcomes, epidural injection efficacy, MRI utility in spinal decision-making, and patient-reported outcome correlations. He actively mentors trainees through the Department of Physical Medicine and Rehabilitation while leading multidisciplinary teams at the Spine Center. He directs comprehensive spine programs at University of Colorado Hospital and Cherry Creek Medical Center, serving as medical director of the Spine Center while collaborating with orthopedic, neurosurgical, and rehabilitation specialists to advance integrated spine care models.

Alfonso Valdesogo Roblesمشاهده پروفایل

دانشیار

• Econometrics
• Financial Econometrics
• Dependency Models
• +۲ مورد دیگر

Alfonso Valdesogo Robles is an Associate Professor in the Department of Applied Economics at the University of the Balearic Islands (UIB), holding a PhD from Université Catholique de Louvain with visiting appointments at University of Luxembourg, Universidad Carlos III de Madrid, Universidade Federal Fluminense, and Université de Cergy-Pontoise. His academic credentials include: PhD in Economics, Université Catholique de Louvain His research specializes in econometric modeling of financial systems, with emphasis on dependency structures and time-series analysis in volatile markets. He develops advanced statistical frameworks for financial risk assessment and economic forecasting, bridging theoretical econometrics with real-world financial applications. A member of UIB's Econometrics and Data Science (ECD) Consolidated R+D+I Group, he teaches core quantitative courses including Econometrics and Macroeconometrics across Business Administration, Economics, and Tourism programs. His pedagogical approach integrates computational methods with empirical economic analysis, supervising master's theses on tourism economics and financial modeling.

Eugenio Miguel Isern Riutortمشاهده پروفایل

مدرس ارشد

• Microelectronics
• Integrated Circuit Testing
• Sensor Design
• +۵ مورد دیگر

Dr. Eugenio Miguel Isern Riutort serves as a Senior Lecturer in the Department of Electronic Technology within the School of Industrial Engineering and Construction at the University of the Balearic Islands (UIB). His academic profile shows active engagement across multiple degree programs including Automation and Industrial Electronic Engineering, Telematics Engineering, and the Master's Degree in Industrial Engineering, where he teaches core courses in Analogue Electronics, Electronic Instrumentation, and related subjects. Beginning his research career in January 1991 with a pre-doctoral scholarship from the Ministry of Education and Science at the Polytechnic University of Catalonia, Dr. Isern Riutort has established three primary research domains. His foundational work focuses on test and verification methodologies for integrated circuits, where he has developed techniques for fault detection through current consumption analysis (both static IDDQ and dynamic IDDT). This research has evolved to address challenges posed by technological parameter variations in modern microelectronics, leading to innovations in predictive testing, oscillation-based testing, and auto-tuning techniques. A second research stream involves designing radiation sensors using standard MOS integrated circuits, with recent work focusing on floating gate MOS transistors that produce outputs proportional to total ionizing dose. Most recently, he has been developing non-conventional computing methodologies accelerated in hardware to enable artificial intelligence applications for massive and highly complex problems. His publication record demonstrates consistent scholarly output across these domains, with particular emphasis on practical applications of theoretical concepts in microelectronics testing and sensor design. The articles reflect a progression from fundamental circuit testing techniques to specialized applications in radiation detection and, most recently, hardware acceleration for AI systems. His work bridges theoretical foundations with experimental validation, as evidenced by his focus on both fault modeling and sensor design with experimental measurements. Dr. Isern Riutort actively supervises Final Degree Projects and Master's Theses in Automation and Industrial Electronic Engineering while teaching across multiple programs. His teaching portfolio spans from foundational Analogue Electronics courses to advanced Electronic Instrumentation Systems, demonstrating comprehensive expertise across the electronics curriculum. He maintains a personal academic website (personal.uib.eu/eugeni.isern) and has established research profiles across major academic networks including ORCID, ResearcherID, Scopus, and Dialnet. As a member of the Electronic Engineering (GEE) Consolidated R+D+I Group at UIB, he participates in a collaborative research framework that supports his work in electronics and related technologies. His office is located in room F107 on the first floor of the Mateu Orfila i Rotger building (Physics building) at the university.

Aurélien Garivierمشاهده پروفایل

استاد

• Machine Learning
• Statistics
• Sequential Decision Making
• +۵ مورد دیگر

Aurélien Garivier is a Professor at Ecole Normale Supérieure de Lyon , affiliated with the UMPA and LIP laboratories. He serves as Deputy Director of UMPA and leads the Master 2 Fundamental Computer Science program at ENS Lyon. His research and academic activities span multiple domains within Machine Learning , Statistics , and Sequential Decision Problems . Local chair of COLT 2025 in Lyon Co-organizer of workshops on Graph Representation Learning and Reinforcement Learning Former director of the Department of Mathematics at the Faculty of Science and Engineering (2016-2018) He has contributed to comparative studies of programming languages for statistical tasks, such as the Baum-Welch algorithm speed analysis in R/Python/Matlab, and co-authored the Perfect Simulation of Processes with Long Memory (2015), which introduced CIAFTP algorithms for stationary processes with transition kernels. His leadership extends to organizing educational initiatives like the UT3-INSA-UT1 Big Data Challenges and Enter the World of AI exhibition. He is also co-host of the SciDoLySE group (Data Science in Lyon and Saint-Etienne).

Marek Omelkaمشاهده پروفایل

دانشیار

• Asymptotic Statistics
• Nonparametric Statistics
• Copula Models
• +۱۰ مورد دیگر

Assoc. Prof. Marek Omelka is a faculty member at the Department of Probability and Mathematical Statistics , Faculty of Mathematics and Physics, Charles University in Prague. His research focuses on copula models, dependence modeling, and nonparametric statistical methods with applications in multivariate analysis, permutation tests, and conditional copula structures. Current teaching: NMST424 Mathematical Statistics 3 and JEM019 Statistical Methods for Data Analysis Research interests: Asymptotic statistics, copula estimation, permutation methods, multivariate association, and functional data depth His recent publications analyze copula parameter estimation, covariate effects in conditional models, and multivariate tail coefficients, with implementations in R. The PMSE program he guarantees connects theoretical statistics with real-world applications in data science, finance, and medical studies.

• Atmospheric sciences
• Climate change science
• Geology
• +۳ مورد دیگر

Sebastian Hoch is an Adjunct Associate Professor in Atmospheric Sciences at the University of Utah. His research focuses on boundary layer processes in complex terrain , particularly examining radiation and surface energy balance effects on boundary layer evolution and terrain-driven flows. Education: PhD in Natural Sciences (Earth Science) from ETH Zurich (2006) Languages: German His research integrates atmospheric sciences , climate change science , and geophysics , with specific emphasis on pollution monitoring , mountain meteorology , and fog dynamics . Recent publications analyze freezing fog microphysics, coastal fog formation mechanisms, and complex terrain wind energy potential using WRF-COAMPS modeling. Grant-funded projects include: COLD FOG AMONGST COMPLEX TERRAIN (CFACT) 2021-2025 RED BUTTE AIR EXCHANGE STUDY 2019-2020 OWENS LAKE LIDAR STUDY 2018 MODELING FOR FASMEE 2018-2021 MATERHORN program 2011-2017 As educator, he has taught Experiential Learning II and Mountain Weather & Climate courses (2023-2024). His work combines extensive field measurements with high-resolution modeling to address atmospheric boundary layer dynamics in complex environments.

Iuliia Alievaمشاهده پروفایل

پژوهشگر

• Social Sciences
• Data Science
• Computer Science
• +۶ مورد دیگر

Dr. Iuliia Alieva serves as a postdoctoral researcher at the Department of Computational Social Science within the Institute of Social Sciences at the University of Stuttgart. Her interdisciplinary work integrates computational methodologies with social science inquiry to analyze digital information ecosystems, with particular emphasis on geopolitical conflict zones and societal crises. Her research portfolio spans critical domains including: Computational Social Science Network Science and Analysis Disinformation and Propaganda Research Social Media Analytics Journalistic Framing Mechanisms Political Communication Dynamics Analysis of her 2021-2024 publications reveals concentrated investigation into Russian information operations on Twitter, especially regarding Ukraine invasion narratives. Her methodological approach consistently combines network analysis, natural language processing, and mixed-methods frameworks to dissect propaganda architectures, anti-war counter-narratives, and media coverage patterns across geopolitical events. Collaborative work with Kathleen Carley's research group forms the backbone of her empirical investigations. Dr. Alieva demonstrates active academic engagement through scheduled 2025 teaching appointments for courses on mis/disinformation and AI-society interactions. No scientific awards or formal student advisement relationships were documented in source materials. Her research emerges from collaborative computational social science teams applying network science to contemporary challenges including election integrity, pandemic communication, and state-sponsored information warfare.

Pamela H Scottمشاهده پروفایل

مدرس ارشد

• Molecular Biology
• Signal Transduction
• Bioscience Education
• +۵ مورد دیگر

Dr. Pamela H Scott is a Senior Lecturer in Molecular Biosciences at the School of Life Sciences, University of Glasgow. Her career spans both research and education, with a focus on pedagogical innovation in bioscience teaching. Her research interests include: E-Learning : Developing digital tools like the Molecular Methods App and Prime It DNA Game . Feedback and Assessment : Pioneering audio feedback systems and self-directed learning strategies. Bioscience Education : Bridging practical biology with theoretical understanding through active learning. RNA Polymerase III Transcription : Early work on signaling pathways in cancer and diabetes. Recent articles highlight her shift to educational technology, including VR by-proxy for experiential learning and digital tools for microbiology teaching. Her scientific awards include a Wellcome Trust Career Development Fellowship and Research Fellowship. She serves as Course Coordinator for Level 2 – Fundamental Topics in Biology and Level 3 – Molecular Methods , and collaborates nationally on pedagogical research. She also leads outreach projects, mentoring students in primary/secondary schools and organizing STEM events at Glasgow Science Centre.