Melissa A Bowles is a Professor at the University of Illinois, holding appointments in the Department of Spanish and Portuguese, Linguistics, and Educational Psychology. She is affiliated with the College of Liberal Arts & Sciences, European Union Center, Lemann Center for Brazilian Studies, and Center for Latin American and Caribbean Studies. Her research focuses on heritage language acquisition, second language learning, and language assessment methodologies. She earned her Ph.D. (with distinction) from Georgetown University, along with an M.S. and B.A. from Georgetown and University of Virginia, respectively. Her work emphasizes verbal protocols and think-aloud methodologies to study cognitive processes in language learning. She has received the Arnold O. Beckman Award (2018) and the Helen Corley Petit Scholar designation (2011-2012). Her research bridges educational outcomes and pedagogical practices, particularly for heritage language learners. She collaborates across disciplines, addressing topics like corrective feedback, assessment validity, and instructional strategies. Her offices are located in the Foreign Languages Building (Room 4150C), and she contributes to multiple research centers focused on Latin American and European studies.
Oscar Gonzalez is an Associate Professor of Quantitative Psychology in the L. L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. His research focuses on integrating psychometrics with machine learning and addressing measurement challenges in statistical mediation analysis. He holds a BA from the University of Notre Dame (2012) and a PhD from Arizona State University (2018), supported by an NSF Graduate Research Fellowship. Education Background: Bachelor of Arts, University of Notre Dame, 2012 Doctor of Philosophy, Arizona State University, 2018 Key Research Interests: Psychometric applications of machine learning for assessment Impact of measurement quality on mediation conclusions Validation of screening tools and construct overlap evaluation Teaching: Machine Learning in Psychology Advanced Test Theory Statistical Mediation Analysis Grants/Awards: National Science Foundation Graduate Research Fellowship Laboratory Affiliation: L. L. Thurstone Psychometric Laboratory
Dr. Kristi Angelopoulou is an Associate Professor in the Department of Physical Therapy at Emory & Henry College’s School of Health Sciences, where she has served since 2015. She holds advanced clinical certifications including Board Certification in Orthopedics (ABPTS), Mastery in Manual Therapy, and Musculoskeletal Ultrasound Imaging. Her academic roles include faculty advisor for the Physical Therapy Club and research projects, committee membership in curriculum and simulation lab affairs, and course mastery for key musculoskeletal and kinesiology courses. Dr. Angelopoulou’s education includes a Doctor of Physical Therapy (Northeastern University, 2011), Master’s in Exercise Physiology (University of Central Florida, 1999), and a Bachelor’s in Athletic Training (Minnesota State University, 1997). Her 18+ years of clinical experience spans sports medicine, outpatient orthopedics, and leadership roles in athletic training and rehabilitation practices. Her research focuses on medical screening, differential diagnosis, and musculoskeletal ultrasound imaging applications. Notable work includes studies on hypertension management in physical therapy patients and dynamic ultrasound assessment of ligament injuries. She has contributed to peer-reviewed journals and book chapters on orthopedic physical therapy, emphasizing clinical decision-making and evidence-based practice. Professional contributions include item writing for the American Board of Physical Therapy Specialties’ Orthopedic Certification and active membership in the APTA’s Imaging Special Interest Group. Her commitment to education is reflected in her dual roles as clinician and academic leader, bridging clinical practice with educational innovation.
Mark R. Wilson is a Professor at the University of California, Berkeley's Graduate School of Education, specializing in Educational Measurement and Statistics. He chairs the National Research Council's committee on science achievement assessment and is the founding editor of the journal Measurement: Interdisciplinary Research and Perspectives . His work focuses on psychometrics, statistical modeling of educational assessments, and the development of measurement frameworks for science education, child development, and policy. Wilson's research interests span measurement theory, applied statistics, and the integration of assessment into educational practices. Notably, he has authored influential books such as Constructing Measures: An Item Response Modeling Approach and co-edited works on explanatory item response models. His contributions include advancing methodologies for evaluating learning progressions, classroom assessments, and large-scale educational accountability systems. His publications emphasize interdisciplinary applications, with articles addressing core measurement principles, latent growth modeling, and the challenges of balancing statistical rigor with scientific relevance. Wilson collaborates internationally on projects like the BEAR Assessment System, aiming to align classroom assessments with broader educational goals. His work bridges theoretical psychometrics with practical educational policy, ensuring assessments are both valid and actionable. Wilson's expertise is further highlighted through his role in developing assessment tools such as the Desired Results Developmental Profile (DRDP) and contributions to international initiatives like PISA. His research consistently advocates for coherence between assessment practices and educational outcomes, emphasizing the importance of meaningful measurement in education and health sciences.
Associate Professor Matthew Sunderland is a leading researcher at the Matilda Centre for Research in Mental Health and Substance Use at the University of Sydney. He holds concurrent appointments as an External Fellow at the Black Dog Institute and Visiting Fellow at the Australian National University . His work focuses on psychiatric epidemiology, comorbidity between mental and substance use disorders, and the development of psychometric tools to improve classification systems in mental health. Current research explores data harmonisation , machine learning applications, and school-based eHealth interventions like Health4Life to address lifestyle risk factors in youth. Major projects include NHMRC-funded trials , implementation of eHealth portals for co-occurring disorders, and international collaborations on alcohol-dementia relationships. His publications span psychopathology modeling , dimensional assessment tools , and implementation science , with over 150 peer-reviewed articles and $22M+ in research funding . Awards include NHMRC Fellowships and Rising Star recognitions from UNSW and the Society for Mental Health Research.
Marilyn S. Thompson is a Professor and School Head in the School of Human Development and Family Sciences at Oregon State University. She holds a PhD in Educational Psychology and Quantitative Methodology from the University of Kansas. Her research focuses on quantitative methods in social sciences, children's academic and socioemotional development, and structural equation modeling, with an emphasis on bilingual education and English language learners. Thompson has held previous positions, including Professor and interim director at Arizona State University's Sanford School of Social and Family Dynamics. Her work spans interdisciplinary collaborations in longitudinal studies and methodological advancements. She has authored over 90 publications, addressing topics like peer influence, teacher-student relationships, and interventions in early childhood education. Her research integrates rigorous statistical methodologies with applied studies in child development, emphasizing practical implications for educational policies and practices. Thompson's contributions include advancing psychometric techniques for cross-cultural comparisons and validating assessments in bilingual populations.
Stella Bollmann is a Researcher at the University of Zurich's Research Methods in Developmental and Educational Sciences group led by Prof. Martin Tomasik. She holds a PhD in Psychology and M.Sc. in Statistics from Ludwig-Maximilians-University Munich. Her research focuses on latent variable models, multilevel data analysis, and improving research methodologies in education and development. Currently, she serves as a project manager for PISA and ÜGK initiatives while contributing to the Zurich Learning Progress Survey (LEAPS). Past roles include postdoctoral positions at Universities of Zurich and Lucerne, and leadership as President of the Swiss Statistical Society (2019–2022). Her work bridges statistical innovation with practical applications in healthcare and education systems. Education: PhD in Psychology (2015), Ludwig-Maximilians-University Munich M.Sc. in Statistics (2016), Ludwig-Maximilians-University Munich Diploma in Psychology (2011), Ludwig-Maximilians-University Munich Research Interests: Development of statistical methods for longitudinal data Evaluation of learning trajectories and educational assessments Addressing methodological challenges in research reproducibility Professional Milestones: Recipient of Bavarian Equal Opportunities Sponsorship (2015) Research collaborations with institutions like the Institute for Educational Evaluation (Zurich) and London School of Economics Labs/Teams: Active contributor to the Tomasik Research Group, focusing on quantitative methods and mathematical modeling in education and developmental research.
Ester Villalonga Olives is an Associate Professor in the Department of Practice, Sciences, and Health Outcomes Research (P-SHOR) at the University of Maryland School of Pharmacy. She holds a PhD in Biomedicine with specialties in Epidemiology and Public Health and is a tenured social epidemiologist. Her academic affiliations include adjunct appointments at New York University, a joint appointment at the University of Maryland School of Medicine, and visiting roles at Harvard, Yale, and currently as a Visiting Professor at Hôtel-Dieu Hospital in Paris. PhD in Biomedicine, Universitat Pompeu Fabra (with International Doctor Distinction) MsC in Sociology and Health, University of Barcelona BsC in Sociology, University of Barcelona International training at Università degli Studi di Trieste, London School of Economics, and University Medical Center Hamburg-Eppendorf Dr. Villalonga-Olives’ research centers on the social determinants of health, particularly social capital, structural racism, health inequalities, and the development of measurement instruments. She employs mixed methods, structural equation modeling, multilevel modeling, and item response theory to study underserved populations, including immigrants and racial minorities. Her work emphasizes intervention design and psychometric validation in public health contexts. Her recent publications reflect a strong focus on health equity, measurement bias (especially differential item functioning), social capital interventions, health literacy adaptation for Hispanic/Latino populations, and mental health among refugees. The trend shows consistent use of advanced statistical techniques to address structural inequities and improve health outcomes through culturally appropriate instruments and interventions. Scientific awards and recognitions include: Award from the Spanish Society of Epidemiology for training in Florence GLOBALtimore Teaching Fellowship (University of Maryland) Member of the NIH Early Investigators Advancement Program Elected board member, International Epidemiology Association (10 years) Multiple international conference awards for her publications Dr. Villalonga-Olives has secured over $4 million in extramural funding, including an NIH R01 grant to develop a multidimensional measure of structural racism. She serves as Principal Investigator on projects funded by the Prevent Cancer Foundation and Merck Investigator Studies Program, focusing on cancer screening and health literacy among Hispanic/Latino immigrants. She is also a co-investigator on two NIH R01 grants related to social connectedness and shared decision-making in maternity care. She advises students and collaborates with multidisciplinary teams. She serves as an associate editor for Frontiers in Public Health and has reviewed for NIH and the French National Cancer Institute. She is actively involved in research teams focusing on psychometrics, social epidemiology, and health outcomes. Her lab integrates item response theory and measurement development with public health interventions, particularly in vulnerable populations. She leads a research program that bridges methodological rigor with real-world impact, including collaborations with United Nations agencies on social capital in forced displacement contexts.
Mehmet Burak Erdoğan is a Professor in the Department of Mathematics at the University of Illinois. His academic career is built on a PhD in Mathematics from Caltech (2001) and extensive contributions to mathematical analysis. His research interests focus on Harmonic Analysis and Dispersive PDE , with particular expertise in Schrödinger operators and dispersive estimates. The fingerprint analysis of his work shows strong connections to Dispersive Mathematics (100%), Schrödinger Operators (82%), Dispersive Estimates (76%), and Schrödinger Equation Mathematics (75%). His recent publications demonstrate continued productivity in mathematical analysis, with work appearing in prestigious journals like Mathematische Annalen, Discrete and Continuous Dynamical Systems-Series A, and Journal of Differential Equations. His research shows consistent themes across publications, particularly in wave operators, dispersive equations, and spectral theory. His scholarly output includes 64 research items (60 articles, 3 conference contributions, and 1 book), with recent publications extending to 2025, indicating an active research program. His office is located at 347 Illini Hall, MC-382, 1409 W. Green Street, Urbana, IL 61801, with office phone (217) 265-6761.
Jillian Halladay is an Assistant Professor in the School of Nursing at McMaster University, Canada. She holds affiliations as a Faculty Member with the Peter Boris Centre for Addictions Research, an Associate of the Research Institute of St. Joe’s Hamilton Mental Health and Addictions Program, and an Affiliate of the Matilda Centre for Research in Mental Health and Substance Use (Australia). Her research focuses on co-occurring substance use and mental health concerns in youth (10-25 years), integrating biological, psychological, and socio-contextual perspectives. Education: BScN, McMaster University MSc, McMaster University PhD, McMaster University Her work emphasizes evidence-based interventions for preventing and treating substance use in youth, including development of outpatient programs. She has received the Health System Impact Embedded Early Career Researcher Award co-funded by Canadian Institute of Health Research, McMaster University, and St. Joseph’s Healthcare Hamilton. Recent publications investigate trends in youth substance use and mental health, mental health literacy programs, and methodological approaches like multiverse analysis. Her articles span journals including Addictive Behaviors , Psychological Medicine , and JAMA Network Open , reflecting expertise in quantitative methods, epidemiology, and intervention design. Scientific Awards: Health System Impact Embedded Early Career Researcher Award Dr. Halladay’s clinical experience includes inpatient and outpatient youth mental health and substance use care. She has supported program development for young adults aged 17-25 in Hamilton, Canada.
Assoc Prof Amirul Islam is a Senior Research Fellow (honorary) at The University of Melbourne and the Founder of an NGO in Bangladesh . His academic journey began with a PhD in Biostatistics from The University of Queensland , followed by roles at National University of Singapore , University of Western Australia , and The University of Melbourne . He combines statistical rigor with public health impact through his work in Chronic Disease Epidemiology , Ophthalmic Studies , and Health Literacy Assessment . Education : PhD in Biostatistics (The University of Queensland) Affiliations : Swinburne University of Technology (current), The University of Melbourne (honorary), North South University (collaborator), German Ophthalmological Society (grantee) His research focuses on chronic disease epidemiology , particularly Diabetes, Hypertension , and Ophthalmic Conditions in rural populations. He specializes in Rasch Analysis , Multinomial Regression , and Path Analysis for complex health data. His 15 most recent articles span health literacy validation , cyberbullying in Malaysia , rural hypertension management , and malaria awareness studies in Indonesia, with methodological strengths in population-based cohorts and behavioral interventions . He has received scientific awards including: Swinburne Innovation Award (2019) VC Teaching Excellence Award (2016) Teaching Award (University of Melbourne, 2012) As an academic editor for PLoS One and the Royal College of Ophthalmology's "Eye" journal , he contributes to peer review. His grant history highlights projects on mobile health interventions , diabetic retinopathy detection , and three-stage vision care programs in rural Bangladesh and Indonesia, funded by organizations like Novartis and Civil Aviation Safety Authority .
Claudio Violato is a Professor of Medicine with a focus on the Division of General Internal Medicine. His academic work spans medical education, clinical assessment, and faculty well-being. Research Interests : Medical education assessment validity and bias Clinical competence metrics Well-being in medical professionals E-learning interventions in health professions Psychosocial and demographic factors in medical training Article Trends : His recent publications emphasize the psychometric rigor of medical education tools, equity in assessment systems, and the intersection of technology and pedagogy. Key themes include bias mitigation, competency frameworks, and pandemic-related educational modeling.
Prof. Dr. Holger Brandt serves as Professor of Psychometrics at the Methods Center within the Department of Social Sciences, Faculty of Economics and Social Sciences, Eberhard Karls University of Tübingen since August 2021. Previously, he held Assistant Professor positions at the University of Zurich (2019-2021) and University of Kansas (2016-2019), following a postdoctoral fellowship at Tübingen's Hector Institute for Empirical Educational Research (2013-2016). His educational background includes a PhD (Promotion) from Goethe University Frankfurt's Institute of Psychology in 2013. Brandt's research pioneers advanced methodological frameworks at the intersection of psychometrics, statistics, and machine learning. He specializes in developing dynamic models for intensive longitudinal data, Bayesian estimation techniques, causal mediator analysis, and identification of inattentive response behaviors in surveys. His work rigorously addresses challenges in measurement invariance, structural equation modeling, and handling complex dependencies in social science data. Analysis of his recent publications reveals a dominant focus on Bayesian approaches for latent variable modeling, particularly spike-and-slab priors and latent class methods. His research consistently targets data quality issues in survey methodology while advancing causal inference techniques that relax traditional no-unmeasured-confounder assumptions. Applications span educational research, psychological assessment, and therapeutic alliance dynamics. As a core member of Tübingen's Methods Center, Brandt provides critical methodological infrastructure for social science research across the university, supporting researchers through statistical consulting and advanced methodology development.
Steve Buyske is a Professor at Rutgers University's Department of Statistics where he serves as Co-Director of both the Undergraduate Statistics Program and the Undergraduate Data Science Program. His office is located in Hill Center 578 at Rutgers University in Piscataway, New Jersey. Dr. Buyske earned his BA from Haverford College and holds PhDs from both Brown University and Rutgers University. His academic journey began in mathematics (differential geometry) before transitioning to statistics, where he initially focused on psychometrics, particularly item response theory and latent variable models, before moving toward statistical genetics and biostatistical collaborations. His research spans statistical genetics, biostatistics, psychometrics, and experimental design. He is particularly noted for his work on polygenic risk scores, genome-wide association studies, and genetic research in diverse populations, with special attention to health disparities in Black American and other underrepresented groups. A native of New Jersey, he has made significant contributions to understanding genetic factors in diseases like type 2 diabetes and obesity. His recent publications show a strong focus on statistical genetics and biostatistics, particularly in polygenic risk scores, genome-wide association studies, and multi-ethnic genetic research. Much of his work addresses health disparities in diverse populations, with particular attention to Black Americans and other underrepresented groups in genetic research. School of Arts and Sciences Award for Distinguished Contributions to Undergraduate Education Dr. Buyske co-directs the Rutgers University Genetics Coordinating Center (RUGCC) with Dr. Tara Matise and has been involved in major research initiatives including the PAGE Study (Population Architecture using Genomics and Epidemiology) and the Genome Sequencing Program. In 2023, they launched a research study on the genetics of breast cancer, which is accessible through the websites https://rugcc.rutgers.edu/breast_cancer/ and http://bcstudy.rugcc.org/. His teaching responsibilities include Statistics 295: Data Wrangling and Management with R, Statistics 365: Bayesian Data Analysis, and other courses in experimental design and data science. He is actively involved with the Rutgers University Genetics Coordinating Center (RUGCC) and has leadership roles in the PAGE Study and Genome Sequencing Program, contributing significantly to large-scale genetic research initiatives with focus on diverse populations.
Dr. Elizabeth A Keiffer is a Teaching Assistant Professor and Senior Associate Director of Graduate Programs in the Information Systems Department at the Sam M. Walton College of Business, University of Arkansas. With nearly a decade of service, she coordinates analytics curriculum across undergraduate and master's programs, teaching courses in decision support and data mining while advising graduate students on academic and career development. Education: PhD in Educational Statistics and Research Methods, University of Arkansas MA in Mathematics Education, University of Arkansas BS in Mathematics with Education minor, East Central University Graduate Certificate in Enterprise Systems (Business Analytics), University of Arkansas Her research examines the impact of data quality issues in analytical contexts, focusing on how missing or 'dirty' data affects statistical outcomes, analyst perceptions, and decision interpretations. This work bridges psychometrics, educational measurement, and modern analytics practices. Keiffer's publications (2010-2023) demonstrate consistent focus on psychometric methodologies, educational assessment tools, and data quality in surveys. Recent works (2022-2023) investigate response model validity and web-based survey quality, while earlier research developed observation instruments for science education and DIF detection methods. As Senior Associate Director, she oversees graduate student progression from course advising to career networking. No awards, research grants, or lab affiliations are documented.
