Anthony J. Gambino is a Postdoctoral Research Associate in the Department of Educational Psychology at the University of Connecticut. His research focuses on gifted education, teacher evaluation, and multilevel modeling techniques. Ph.D. in Research Methods, Measurement, and Evaluation (University of Connecticut) M.A. in Measurement, Evaluation, and Assessment (University of Connecticut) B.S. in Psychology (Wagner College) His work addresses critical issues in educational equity, including disparities in gifted program identification by race, poverty, and language status. He develops and evaluates statistical tools for multilevel modeling and contributes to understanding the role of teacher rating scales in educational assessments. Gambino’s publications emphasize methodological rigor in educational research, particularly in behavioral interventions like PBIS and analytical frameworks for teacher effects. He maintains active engagement in advancing evaluation curricula for graduate programs.
Professor Byron Sharp is a Professor of Marketing Science and Director of the Ehrenberg-Bass Institute for Marketing Science at the University of South Australia. The institute is recognized as the world’s largest center for research into marketing, housing over 60 marketing scientists. He plays a pivotal role in advancing evidence-based marketing principles globally. Research Interests: Marketing Science and Empirical Generalizations Brand Growth and Customer Acquisition Advertising Effectiveness and Mental Availability Consumer Behavior and Loyalty Patterns Market Modeling (e.g., Dirichlet model) Evidence-Based Marketing Practice His recent publications reveal a consistent focus on quantifying brand performance, buyer behavior, and advertising impact. Trends in his articles emphasize the application of statistical models (e.g., NBD, Dirichlet) to understand consumer repertoires, loyalty, and the effects of advertising cessation. His work bridges academic rigor with practical marketing applications, particularly in brand strategy and media planning. Scientific Awards and Recognition: His book How Brands Grow was voted Marketing Book of the Year by AdAge readers. Recognized by Warc (2015) as one of the most influential marketing books of the past decade. Advising, Grants, and Collaborations: While specific student names are not listed, he leads a large research team and frequently collaborates with prominent scholars such as Jenni Romaniuk, John Dawes, and Robert Kennedy. His work is supported by industry partnerships and institutional funding through the Ehrenberg-Bass Institute, enabling large-scale empirical studies using real-world data. Labs and Teams: He directs the Ehrenberg-Bass Institute, which functions as a major research laboratory focused on marketing science, conducting longitudinal studies, empirical generalizations, and collaborative industry research.
Malvina Nissim is a leading researcher in computational linguistics and NLP at the University of Groningen's Department of Artificial Intelligence, with a focus on multilingual modeling, bias mitigation, and human evaluation frameworks. Key Contributions : Developed CALAMITA (Italian LLM benchmark), IT5 models for Italian language processing, and ReproHum framework for NLP evaluation reproducibility Research Pillars : Multilingual reasoning consistency, perspective-based text analysis, and figurative language modeling Her work spans activation steering techniques, cross-lingual transfer learning, and the creation of specialized language resources like the EurekaRebus dataset and MAGPIE idiom corpus. She pioneered methods for gender bias measurement in BERT and developed the SocioFillmore tool for perspective visualization. Recent publications explore model uncertainty as MCQ difficulty proxy, Italian headline generation benchmarks, and multilingual multi-figurative language detection. She actively participates in teaching initiatives like the "NLP with Bracelets" workshop for Italian high school students. Scientific Awards : ACL Best Paper Award (2025) EMNLP Outstanding Reviewer (2023) EVALITA Leadership Recognition (2024) She advises PhD students in model bias analysis and has contributed to the development of the Dutch Abusive Language Corpus (DALC) and the ReproNLP reproducibility framework. Her collaborations span institutions in Italy, Netherlands, and international NLP communities.
Jonathan Cannon is an Assistant Professor in the Department of Psychology, Neuroscience & Behaviour at McMaster University's Faculty of Science. His research focuses on timing and rhythm in perception and action, with particular interest in timing-related neural dynamics in the basal ganglia, cerebellum, and supplementary motor area. His work combines mathematical modeling with experimental approaches to understand the neural basis of rhythm perception and production. Dr. Cannon's research interests span timing and rhythm perception , neural dynamics , dynamical systems theory , Bayesian cognition , neural oscillations , and autism research . His approach centers on formulating and simulating neurophysiological and cognitive models, drawing on dynamical systems theory and Bayesian cognitive frameworks. His work incorporates psychophysics, EEG experiments, and collaborations with experimentalists to investigate how the brain processes rhythmic information. Analysis of his recent publications reveals a strong focus on the intersection of rhythm perception, motor control, and autism spectrum disorder. His work demonstrates how beat perception co-opts motor neurophysiology, with particular attention to predictive processes in rhythmic cognition. His research shows reduced precision of motor and perceptual rhythmic timing in autistic adults, while also finding intact sequence learning abilities in certain contexts. Dr. Cannon teaches advanced courses including Machine Learning Methods for Brain Modelling and Neural Data Analysis (PSYCH 734), Computational Models in Neuroscience (NEUROSCI 3MN3), and Neuroscience Seminars. His teaching reflects his interdisciplinary approach that bridges mathematics, neuroscience, and cognitive science. Beyond his academic work, Dr. Cannon is an active musician who performs on violin and guitar, particularly in klezmer and folk music contexts. He has also demonstrated entrepreneurial spirit through founding Flying Leap Games and developing the storytelling game 'Wing It,' which successfully crowdfunded and reached numerous retailers.
Associate Professor Stephen Carter is an Associate Professor in Pharmacy Practice at the University of Sydney's Sydney Pharmacy School within the Faculty of Medicine and Health. He serves as the Program Director for Undergraduate Pharmacy programs and is a registered pharmacist with clinical specialisation in medication management review. Stephen holds qualifications including BPharm, MSc, PhD, and Grad Cert Edu (Higher Ed). He is a Fellow of the Pharmaceutical Society of Australia (FPS), Fellow of the Higher Education Academy (FHEA), and holds other professional accreditations. His research focuses on optimizing the role of pharmacists in healthcare, particularly examining how consumers and caregivers obtain and use medicines, designing effective pharmacist services, and supporting pharmacists throughout their professional journey. His work spans areas including osteoporosis care, medication adherence, service quality in community pharmacies, and the application of advanced statistical methods like Structural Equation Modelling. Stephen's publications demonstrate a strong focus on practical pharmacy interventions, with significant work on osteoporosis management services, perinatal depression screening in pharmacies, and digital health approaches to improve medication adherence. His research employs diverse methodologies including randomized controlled trials, qualitative studies, and advanced psychometric analyses. Early Career Investigator Award Australasian Pharmaceutical Science Association (APSA) for 2017 Lesmuller Award for Best Oral Communication - Pharmaceutical Care Network Europe Working Conference, Berlin, 2013 Recipient of the 2013 Annual Best Paper Award by Elsevier publication, Research in Social and Administrative Pharmacy Best Poster Presentation Award: International Social Pharmacy Workshop, Boston, USA, 2014 Top reviewer, Research in Social and Administrative Pharmacy (2015, 2016, 2017, 2019) Stephen actively supervises several graduate students including PhD candidates Fatima Rezea, Steven Tran, Veronika Seda, Kingston Leung, and Joel Hillman, as well as MPhil student Linda Krogh. He has secured significant research funding, including co-leading a $2.36 million Randomized Controlled Trial and managing four current competitive grant-funded projects totaling over $6.3 million. His work has particular emphasis on translating research into practical pharmacy services that improve patient outcomes. Stephen is actively involved in major research initiatives including the #STOP trial (Safer medicines To reduce falls and refractures for OsteoPorosis) and the TICTOC trial (Timely post-discharge medication reviews to Improve Continuity – the Transitions Of Care stewardship), both focusing on innovative pharmacist-led interventions to improve medication safety and effectiveness.
Dr. Ruth F. Lucas, PhD, RNC, CLS, is an Associate Professor at the University of Connecticut School of Nursing. Her research focuses on breastfeeding equity through biopsychosocial and molecular mechanisms, infant breastfeeding biomechanics, and pain self-management. Education: PhD in Nursing from University of Illinois at Chicago (2011) Dr. Lucas leads projects translating the PROMPT study for WIC-eligible populations and testing biomedical lactation devices for real-time intraoral pressure measurement. Her work integrates genetic factors (e.g., COMT and OXTR variants) with social determinants of health, particularly in African American communities. Her recent research trends span genomics education for nurses, maternity care deserts in the U.S., breastfeeding self-efficacy metrics, and global lactation disparities. Current efforts include competency frameworks for genomics nurse educators and meta-ethnographies on diverse breastfeeding experiences. Contact: ruth.lucas@uconn.edu
Jasmine Travers Altizer is an Assistant Professor at NYU Rory Meyers College of Nursing, where she conducts research to improve health outcomes and reduce disparities among vulnerable older adults. Her work spans long-term care systems, aging, and health equity, with a focus on both quantitative and qualitative approaches. Education: PhD, Columbia University School of Nursing MHS, Yale University MSN, Stony Brook University (Adult-Gerontological Health) BSN, Adelphi University Her research interests include gerontology, health disparities, workforce diversity, infection control, and policy in long-term care. She investigates how neighborhood disadvantage, staffing levels, and systemic inequities affect care quality in nursing homes and home-based settings. Her recent work has explored antipsychotic medication use, caregiver coping strategies, and the impact of federal programs like the Paycheck Protection Program on staffing. The 15 most recent publications reflect a strong trajectory in health services research, with recurring themes in equity, workforce well-being, and policy evaluation. Her studies frequently use large national datasets and mixed methods to address structural barriers in care delivery for underserved populations, particularly Black and Latino older adults. Scientific Awards and Honors: Rising Star Research Award, Eastern Nursing Research Society (2022) Health in Aging Foundation New Investigator Award (2022) NASEM Committee Member on Quality of Care in Nursing Homes (2020) Scholar, National Clinician Scholars Program, Yale (2020) Jonas Policy Scholar (2019) Douglas Holmes Emerging Scholar Paper Award (2018) Travers is actively involved in mentoring and accepting PhD students. She leads multiple federally funded research projects, including a Robert Wood Johnson Foundation Career Development Award and a National Institute on Aging K76 Beeson Award. She has served on national committees and contributed to high-impact policy reports, demonstrating leadership in translating research into action. Her work is frequently covered in media outlets such as Scientific American , AARP , and Crain's New York . Laboratories and Research Teams: She is affiliated with several active research initiatives, including the NH Explanatory Trials Network and projects examining dementia care workforce experiences, health equity in nursing home quality measures, and culturally sensitive interventions for Black adults with chronic conditions.
Katalin Piniel is an Assistant Professor at the Department of English Applied Linguistics within the School of English and American Studies at Eötvös Loránd University, Budapest. Her work bridges applied linguistics and educational psychology , focusing on the dynamic interplay of emotions , including language anxiety , motivation, and self-efficacy in foreign language learning contexts, particularly in Hungary. PhD in Language Pedagogy (ELTE) Associate Editor of Studies in Second Language Learning and Teaching Active reviewer for applied linguistics journals Her research integrates complex dynamic systems theory to analyze longitudinal changes in affective variables and employs meta-analytic techniques to validate anxiety measurement tools like the Foreign Language Classroom Anxiety Scale (FLCAS) . She explores formative and summative assessment practices in Hungarian high schools and investigates flow experiences during language tasks. Her methodological interests include quantitative tools (e.g., Rasch analysis), collaborative research , and cross-cultural comparisons (e.g., Hungarian-Kazakh studies). Recent publications highlight trends in emotion-motivation dynamics , skills-based anxiety measurement , and the impact of online education on affective variables. She collaborates on projects examining special needs learners , including Deaf and hard-of-hearing students , in foreign language acquisition. Contact: brozik-piniel.katalin@btk.elte.hu | ORCID | Google Scholar | ResearchGate
David J. Moore, Ph.D., is a licensed clinical psychologist and Professor of Psychiatry at UC San Diego Health. He co-directs the SDSU/UCSD Joint Doctoral Program (JDP) in Clinical Psychology and leads research at the HIV Neurobehavioral Research Program (HNRP). His work focuses on neurocognitive impairments in individuals with HIV, comorbid mental illness, and substance use disorders, with a special emphasis on technological interventions for medication adherence. Doctorate: Ph.D. in Clinical Psychology (SDSU/UCSD JDP, neuropsychology specialization) Postdoctoral Fellowship: UCSD (serious mental illness) Clinical Internship: West Los Angeles VA Dr. Moore’s research addresses: Neurocognitive complications of HIV infection Intersection of HIV and aging Technological interventions for medication adherence Impact of comorbid psychiatric/substance use disorders on functioning His publications span topics including HIV neurocognitive profiles, syndemic factors in sexual risk behavior, and aging with HIV. Current studies integrate metabolomics, neuroimaging, and behavioral data through NIH-funded grants.
Professor Edward Palmer is a faculty member in the School of Education at the University of Adelaide, serving as Director of the Unit of Digital Education and Training and Acting Deputy Head of School. His research focuses on technology's role in education and training, particularly in virtual/extended realities, AI-driven assessment, and personalized learning approaches. He has secured over $3 million in funding from government and industry partners, with projects addressing AI ethics, VR applications in medical training, and MOOC design. Education & Roles: Holds academic leadership positions and directs digital education initiatives. Research: Investigates AI in education, VR for situational awareness, and innovative assessment methods. Active in collaborative projects with industry and defense sectors. Grants & Funding: Secured significant grants for ventures in AI ethics, VR training simulations, and digital health hubs. Labs/Teams: Leads the Unit of Digital Learning and Society, collaborating with postdocs like Daniel Lee on AI and VR projects. His work emphasizes practical applications, such as medical procedure training in VR and adaptive learning systems. He mentors HDR students and postdocs in AI-driven training scenarios and digital education innovation.
Dr. Daniel A. Sass is an Associate Dean for Graduate Studies and Associate Professor in the Department of Management Science and Statistics at the University of Texas at San Antonio’s Carlos Alvarez College of Business. He directs the Statistical Consulting Center and focuses on methodological research, including psychometrics, structural equation modeling, and factor analysis. His applied work spans education, public health, and organizational behavior. Education: Ph.D. in Management Science and Statistics, University of Wisconsin-Milwaukee B.A., University of Wisconsin-Milwaukee Research Interests : Dr. Sass specializes in advanced statistical methodologies with applications in education and social sciences. His work emphasizes psychometric validation, measurement invariance, and applied collaborative projects. Key areas include teacher retention, classroom management, and cross-cultural scale adaptation. His research bridges theoretical statistical frameworks with real-world challenges in education and public policy. Publications Trends : Recent work explores pandemic impacts on productivity, educator stress in charter schools, and diabetes management programs. Earlier studies focus on statistical methods like factor analysis and structural equation modeling validation. His articles consistently address practical implications for policy and practice. Advising/Grants : While no advisees are listed, his collaborative projects involve interdisciplinary teams across education, public health, and organizational studies. His Statistical Consulting Center supports UTSA researchers in applying rigorous statistical methods to their work. Labs/Teams : Director of the Statistical Consulting Center, providing methodological support for academic and applied research projects.
Dr. Geoffrey L. Herman serves as the Severns Teaching Professor in the School of Computing and Data Science at the University of Illinois at Urbana-Champaign. He earned his Ph.D. in Electrical and Computer Engineering from UIUC as a Mavis Future Faculty Fellow and completed postdoctoral research at Purdue University's School of Engineering Education. His research focuses on understanding how students learn engineering and computing concepts and developing systemic approaches to improve teaching methods in higher education. With over $7 million in research funding and more than 120 peer-reviewed publications, his work spans educational technology, cognitive aspects of learning, and faculty development initiatives. His recent publications demonstrate a consistent focus on evidence-based instructional practices, assessment methodologies, and collaborative learning approaches, with particular emphasis on computer science education, proof writing tools like Proof Blocks, and mastery learning techniques. These works collectively advance the understanding of effective educational strategies in STEM fields. IEEE Education Society Mac Van Valkenburg Early Career Teaching Award Scott H. Fisher Computer Science Teaching Award Best paper award in the first 50 years of the ACM Special Interest Group, Computer Science Education As a mentor, Dr. Herman guides graduate students interested in engineering and computing education research, focusing on designing better instruction. He also works with undergraduates on improving educational experiences through platforms like PrairieLearn. His leadership extends to founding the Grainger College of Engineering's Strategic Instructional Innovations Program, which has secured millions in external funding. He serves on the Computer Research Association Education committee and as associate editor for the Journal of Engineering Education. Dr. Herman leads national workshops on professional development for computer science teaching faculty and has created peer mentoring networks through the Teaching Professionals Program, significantly impacting faculty development in engineering education.
Cengiz Zopluoglu is an Associate Professor in the Department of Special Education and Clinical Sciences at the University of Oregon's College of Education. His research focuses on quantitative methods in education, item response theory, computational psychometrics, and educational data science. He teaches advanced courses on psychometrics, statistical methodology, and data analysis using R. Education: PhD, 2013: University of Minnesota (Educational Psychology, Quantitative Methods) MA, 2009: University of Minnesota (Educational Psychology, Quantitative Methods) BA, 2005: Abant Izzet Baysal University (Mathematics Education, K-8) Research Interests: Zopluoglu's work emphasizes integrating machine learning and statistical models into educational measurement. He develops methods to detect test misconduct (e.g., item preknowledge) using response time and accuracy data, and explores automated scoring of open-ended responses using AI (e.g., transformers). His contributions include advancements in continuous response models, multidimensional IRT, and DETECT analysis for dimensionality assessment. Awards: 2023 Runner-up Prize in NAEP Math Automated Scoring Challenge (NCES) 2021 3rd Place in NIJ Recidivism Forecasting Challenge 2013 Graduate Student Research Award (University of Minnesota) Advising & Grants: Zopluoglu has advised on projects related to test security, automated scoring, and machine learning applications. His work often involves open-source tools like R and Stan, with a focus on reproducible research. Labs & Collaborations: He collaborates on initiatives like the Deterministic Gated Models for Test Security and the WrightRightNow automated scoring platform. His research leverages interdisciplinary approaches, blending psychometrics with computer science and data science.
John Leahy is the Allen Sinai Professor of Macroeconomics and Public Policy at the University of Michigan, holding dual appointments in the Department of Economics (College of Literature, Science, and the Arts) and the Gerald R. Ford School of Public Policy. As Chair of the Economics Department, he focuses on macroeconomic theory, monetary policy, and behavioral economics, particularly rational inattention models. His research emphasizes how cognitive limitations and information processing affect economic decisions, contrasting classical economic assumptions. Leahy has held positions at Harvard, NYU, and Boston University, and served as Coeditor of the American Economic Review and Editor of the American Economic Journal: Macroeconomics. He consults with Federal Reserve Banks, advocating for data-driven, question-first research methodologies. His work bridges theoretical rigor and practical applications, influencing policy analysis and academic discourse. Education: PhD in Macroeconomics from Princeton University; MSFS from Georgetown University; BA in Math and History. His research spans macroeconomic policy, structural change, and behavioral models of decision-making, with recent focus on wishful thinking and imperfect information processing. He collaborates widely, emphasizing interdisciplinary approaches and creative problem-solving. Key contributions include modeling rational inattention, analyzing age structure impacts on monetary policy, and exploring North-South economic disparities. His editorial leadership and academic mentorship reflect his commitment to advancing innovative economic inquiry.
Professor Sarah Bate is an academic at Bournemouth University, currently serving as Interim Associate Pro Vice-Chancellor (Research and Knowledge Exchange). She leads the Centre for Face Processing Disorders and authored the seminal book *Face Recognition and its Disorders*. Her work focuses on face-processing impairments in developmental and acquired prosopagnosia (face blindness), employing eye-movement technology to explore theoretical and remediation strategies. Education: Completed a BSc (2004), MSc (2005), and PhD (2009) in Psychology at the University of Exeter, followed by postdoctoral research before joining Bournemouth in 2010. Research Interests: Prosopagnosia sub-classification, face recognition disorders, neuropsychological assessment tools, and applications in forensic and clinical settings. Her studies span cognitive mechanisms, rehabilitation techniques, and individual differences in face perception. Recent articles emphasize taxometric analysis of prosopagnosia subtypes, familial transmission patterns, and the role of birthweight in face recognition. Collaborations include work on oxytocin’s effects and the development of diagnostic tools like the Oxford Face Matching Test. Grants and Affiliations: Active in grants such as the *Face Blindness Awareness Campaign* and affiliated with the British Psychological Society and Experimental Psychology Society. Supervises PhD students like Anna Bobak, focusing on neuropsychological and developmental aspects of face recognition.
