Ivana Lolić is an Assistant Professor at the Department of Statistics, Faculty of Economics & Business, University of Zagreb. She holds a PhD in Economics from the same institution, with a focus on economic uncertainty and consumption modeling, and has additional education in Mathematical Statistics (MSc, Summa Cum Laude) and Financial Analysis (BSc). Her research bridges Behavioral Economics and Econometrics, with emphasis on economic sentiment analysis, uncertainty measurement, and macroeconomic modeling. Her scholarly contributions include developing economic sentiment indicators, analyzing inflation expectations, and exploring nonlinear effects in macroeconomic processes. She has received multiple awards for scientific excellence, including the Mijo Mirković Award (2016) and recognition as Most Productive Assistant Professor (2022). She actively reviews for journals like Financial Innovation and European Journal of Finance. Scientific Awards: 2022 Most productive faculty member among Assistant professors 2016 Mijo Mirković Award 2016 Isaac Kerstenetzky Award 2016 Best paper in Official Statistics session 2013 Best paper at Dubai conference She teaches courses in Applied Machine Learning, Statistical Computer Lab, Business Statistics, and Statistics, while mentoring national statistics competition participants. Her work has been funded by Croatian Science Foundation and University of Zagreb grants, with methodological expertise in machine learning, time series analysis, and Bayesian econometrics.
Dr. Tom Brownlee is an Assistant Professor in Applied Sport Sciences at the School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham. His expertise bridges academic research and elite sports practice, with a strong background in professional football environments. Education: BSc (Hons) Sport and Exercise Science, Coventry University MSc Exercise Physiology, Loughborough University PhD Applied Exercise Physiology, University of Liverpool (conducted at Liverpool FC) Tom’s research is centered on applied physiology and strength and conditioning , with a focus on high-performance sport . His work investigates strength training methodologies, periodisation strategies, nutritional practices, and effective communication between scientists and coaches in elite settings. He has extensive experience working within professional football, informing both his teaching and research direction. His recent publications reflect a strong trend in elite football science , particularly in training load monitoring, strength development across genders and age groups, genetic influences on performance and injury, and the practical application of technology like GPS and flywheel training. The research emphasizes real-world implementation and practitioner perspectives. Professional Roles and Recognition: Leader, UK Strength and Conditioning Association (UKSCA) Football Special Interest Group Consultant for the English Premier League Reviewer for leading journals including Journal of Sports Sciences , International Journal of Sports Physiology and Performance , and European Journal of Sports Science Tom is an active supervisor, having guided multiple doctoral and master’s students to completion, with a focus on candidates embedded in high-performance sport. He regularly advertises PhD opportunities through his professional network, particularly on Twitter. While specific grants are not listed, his consulting and leadership roles indicate significant professional engagement and impact. He also contributes to teaching, delivering modules such as Introduction to Sports Science and Athletic Training and Conditioning.
Ronald Linn Rivest is an Institute Professor at the Massachusetts Institute of Technology (MIT), where he holds the Andrew and Erna Viterbi professorship in the Department of Electrical Engineering and Computer Science. He is a member of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), where he is part of the Theory of Computation Group and leads the Cryptography and Information Security Group. Rivest has been at MIT since 1974, after completing a post-doctoral position at INRIA in France. His educational background includes: Niskayuna High School, Niskayuna, New York (1965) B.A. in Mathematics from Yale University (1969) Ph.D. in Computer Science from Stanford University (1973) Rivest's research spans multiple areas of computer science with a particular focus on cryptography, computer security, algorithms, and election security. He is best known for co-inventing the RSA public-key cryptosystem with Adi Shamir and Leonard Adleman in 1977, which revolutionized secure communications and is widely used in internet-based commercial transactions. His work on election security has led to innovative voting systems like the ThreeBallot scheme, designed to ensure verifiability while maintaining voter privacy. Rivest has also made significant contributions to algorithm design and analysis through his co-authorship of the influential textbook "Introduction to Algorithms," which has become a standard reference in computer science education. An analysis of Rivest's recent publications reveals a continued focus on election security and voting systems, with numerous papers on risk-limiting audits, ballot design, and verification methods. His work has expanded into related areas including pandemic response technology (particularly contact tracing systems during the COVID-19 pandemic), climate change mitigation, and privacy-preserving technologies. The interdisciplinary nature of his research bridges computer science with political science, public policy, and environmental science. Rivest has received numerous prestigious awards throughout his career: ACM Turing Award (2002) - considered the "Nobel Prize of Computing" Marconi Prize (2007) Member of both the National Academy of Engineering (1990) and National Academy of Sciences (2004) Fellow of the ACM (1993) and American Academy of Arts and Sciences (1993) IEEE Koji Kobayashi Computers and Communications Award (2000) NEC C&C Prize (2009) Named an Institute Professor at MIT (2015) - the highest faculty honor at MIT Rivest has been actively involved in advising government bodies on election security and technology policy. He has testified before congressional committees and served on the National Academies of Sciences, Engineering, and Medicine committee that produced the report "Securing the Vote: Protecting American Democracy." His work with the Encryption Working Group has influenced national discussions on encryption policy. Rivest has also co-founded companies including RSA Data Security, demonstrating his ability to translate theoretical work into practical applications. His research has been supported by various grants from government agencies and private foundations focused on cybersecurity, election integrity, and privacy-enhancing technologies. At MIT, Rivest leads the Cryptography and Information Security Group within CSAIL, which conducts cutting-edge research in cryptographic protocols, secure systems design, election security, and privacy-preserving technologies. The group collaborates with policymakers, election officials, and other researchers to develop practical solutions for real-world security challenges. Rivest's team has been particularly active in developing and testing risk-limiting audit methods for election verification and creating secure, verifiable voting systems that maintain voter privacy.
Bella Struminskaya is an Associate Professor at Utrecht University’s Department of Methodology & Statistics, Faculty of Social and Behavioural Sciences. She is also an affiliated researcher at Statistics Netherlands and previously held a senior researcher role at GESIS - Leibniz Institute for the Social Sciences. Her work bridges survey methodology with digital data collection techniques, focusing on smartphone sensors and passive data donation. Education: PhD in Survey Methodology, Utrecht University M.A. in Sociology, University of Mannheim B.A. in Sociology, Novosibirsk State University Her research explores innovative data collection methods, including smartphone surveys, mixed-mode designs, and ethical frameworks for data donation. She investigates how mobile technologies can reduce survey burden while addressing nonresponse bias and measurement errors. Recent work emphasizes integrating digital trace data with traditional surveys to enhance accuracy and scope. Key article trends highlight applications of smartphone sensors in health studies, GDPR compliance for data access, and methodological advancements in smart surveys. Her contributions span technical tools like the Port software and theoretical insights on panel conditioning and ethical data augmentation. Scientific Awards: GOR Thesis Award 2015 She serves as a board member for the German Society for Online Research, Program Chair for the General Online Research Conference (GOR), and holds advisory roles in organizations like the European Social Survey, SHARE ERIC, and ODISSEI. She is an associate editor for multiple journals, including the Journal of Survey Statistics and Methodology and Survey Research Methods.
Jason Abrevaya serves as Associate Dean for Graduate Education and holds the Murray S. Johnson Chair in Economics at the University of Texas at Austin within the College of Liberal Arts and Department of Economics. His research spans econometric methodology, applied microeconomics, and demography, with significant contributions using U.S. birth databases to study birthweight inequality, smoking effects, and gender selection practices among ethnic groups. Dr. Abrevaya's work centers on econometrics (panel data analysis, treatment effects, missing data), health economics (birth outcomes, vaccination), labor economics, and sports economics. His methodological innovations address data challenges in causal inference and microeconomic applications, characterized by rigorous statistical approaches to real-world problems. Recent publications demonstrate continued emphasis on theoretical econometrics with empirical applications in public health and sports analytics. His article trends reveal sustained focus on treatment effects under heteroskedasticity, partial effects in nonlinear models, and applications to vaccine uptake and sports (e.g., penalty calls in hockey). Methodological contributions frequently bridge theoretical econometrics with empirical practice in health and social sciences. Dr. Abrevaya has secured research funding from the National Science Foundation and Robert Wood Johnson Foundation. He is author of the textbook Probability and Statistics for Economics and Business: An Introduction Using R . No scientific awards are explicitly mentioned in available sources. As Associate Dean for Graduate Education, he oversees graduate programs while maintaining active research and mentorship. His warning about scam impersonation attempts (via Gmail addresses posing as research opportunities) underscores the importance of verifying communications through his official university email.
Professor Adam Hamrol is a distinguished academic at Poznań University of Technology, serving in the Faculty of Mechanical Engineering within the Institute of Materials Technology. With a career spanning over four decades since his doctoral completion in 1982, he has established himself as a leading expert in mechanical engineering with a 100% focus in this discipline according to official classifications. His research interests center on quality engineering, sustainable manufacturing processes, materials technology, and the integration of Industry 4.0 technologies into production systems. Professor Hamrol has made significant contributions to energy efficiency in manufacturing, digital transformation of quality management systems, and sustainable production methodologies. His work bridges theoretical research with practical industrial applications, as evidenced by numerous case studies in his publications. Analysis of his recent publications reveals a strong emphasis on the intersection of traditional manufacturing with digital technologies and sustainability considerations. His research group produces work that addresses contemporary challenges in production engineering, including machine learning applications for predictive maintenance, environmental impact reduction, and digital quality control systems. Professor Hamrol has supervised 18 doctoral students to completion, with recent graduates working on topics ranging from production leveling to CNC programming automation and quality control in manufacturing processes. His research activities are supported by multiple ongoing projects as indicated by his research reports from 2021-2023. As an active researcher, he continues to publish in high-impact journals through 2025 and serves as editor for Springer's 'Advances in Manufacturing' book series, demonstrating his ongoing contribution to the academic community and his leadership in the field of mechanical engineering and manufacturing research.
