Dr. Lecturer Sevinç Ünsal Oral is affiliated with Başkent University as a faculty member in the Department of Civil Engineering. She holds a PhD (2013), Master's (2009), and BSc (2006) in Civil Engineering from Middle East Technical University. Specializes in geotechnical engineering and earthquake engineering Active in seismic hazard analysis and soil-structure interaction Her research focuses on liquefaction assessment, landslide modeling, and seismic performance of infrastructure. Articles highlight work on geothermal facilities, dams, and airport structures. Scientific contributions include numerical modeling frameworks for earthquake-induced geohazards. She serves as a thesis advisor for graduate students and participates in projects related to UN Sustainable Development Goals.
Paolo Prandoni is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC). He serves as a Scientist in the Audiovisual Communications Laboratory (LCAV) and teaches in the SSC-ENS and SIN-ENS units, focusing on signal processing theory and practical applications in audiovisual communications. He earned his PhD from EPFL after completing all prior education there, driven by childhood fascination with long-distance telephony. His doctoral work established foundations in communication systems that continue to inform his research. Prandoni's research spans audio/image processing, machine learning for media analysis, and DSP education. Key areas include computational photography (e.g., spectral imaging, stained glass rendering), speech quality assessment via transfer learning, music information retrieval (e.g., fingering prediction), and audience analytics through his company Quividi. His work consistently bridges theoretical signal processing with real-world implementation. Recent publications reveal a strategic shift toward machine learning integration in signal processing tasks, particularly non-intrusive speech assessment and lensless imaging reconstruction. Simultaneously, he advances DSP pedagogy through MOOC development and hands-on teaching tools using off-the-shelf hardware, emphasizing accessibility and practical skill development. No scientific awards are documented in the provided materials. He has advised PhD student Thanikachalam Niranjan (thesis: Image Based Relighting of Cultural Artifacts , 2016) and teaches Communication Systems and Computer Science courses. His educational impact extends through the open-access textbook Signal Processing for Communications (2008) and tools like MultiPub for maintainable online classes. Industry engagement includes Quividi co-founding (2006) and ongoing CSO role in attention analytics. As a core LCAV laboratory member, he collaborates on interdisciplinary projects including cultural heritage digitization, embedded signal processing systems, and real-time audience measurement, leveraging EPFL's infrastructure for both academic and commercial applications.
Dr. Anna Hatton is a Senior Lecturer at the School of Health and Rehabilitation Sciences , The University of Queensland. As Co-Director of the UQ Centre for Neurorehabilitation, Ageing and Balance Research and Associate Editor for Gait & Posture , she leads interdisciplinary research into sensory-based rehabilitation technologies. Her work bridges clinical practice with engineering innovation, focusing on footwear devices for balance enhancement. Research themes: novel textured/vibratory insoles , neurological gait analysis , age-related mobility Key funding: NHMRC IDEAS Grants , Bionics Queensland Challenge , Diabetes Australia , PA Research Foundation Her Young Tall Poppy Science Award (2016) recognizes contributions to plantar sensory stimulation. Current supervised projects explore bionic insole neurophysiology , combat sports injury prevention , and sport performance optimization . Media engagements focus on electromyography , sensorimotor function , and footwear interventions .
Hatim Rahman serves as Associate Professor of Management and Organizations and Sociology (by courtesy) at Northwestern University, holding the prestigious PepsiCo Chair in International Management. His research fundamentally examines how artificial intelligence and algorithms reshape work structures, employment relationships, and labor market dynamics, with particular focus on digital platform ecosystems and algorithmic management systems. Professor Rahman's academic credentials include a PhD in Management Science & Engineering (2019) and MS in Organizations, Technology, Entrepreneurship (2014) from Stanford University, complemented by a BA in Business Process Management with Minor in Technology and Management from the University of Illinois-Urbana Champaign (2009). His scholarly work centers on the sociotechnical transformation of work through algorithmic systems, investigating worker reactivity to opaque evaluations, platform power dynamics, and emergent resistance movements in digital labor markets. Key contributions explore the "invisible cage" of algorithmic control, the experimental nature of platform management, and the sociological implications of AI-driven workplace restructuring. His research bridges management theory, sociology of work, and technology studies to address critical questions about fairness, autonomy, and accountability in the algorithmic age. Analysis of his publication trajectory reveals a clear evolution from creative occupations research (2017) toward concentrated investigation of algorithmic labor platforms (2021-2025). His work consistently demonstrates how digital platforms reconfigure worker autonomy through experimental management practices, opaque evaluation systems, and novel control mechanisms, while simultaneously generating new forms of worker resistance and activism. The 2024 book "Inside the Invisible Cage" synthesizes these insights into a comprehensive framework for understanding algorithmic worker control. Professor Rahman's exceptional contributions have earned him significant recognition: National Science Foundation CAREER Award recipient for bridging STEM skills and employment gaps George R. Terry Book Award winner from the Academy of Management Named among Poets & Quants' Best 40 Business School Professors Under 40 (2023) Thinkers50 Radar listing for influential management thinking Multiple Academy of Management best paper awards across divisions Microsoft Research AI and Society Fellowship International Labour and Employment Relations Association prizes His research program includes substantial grant funding from the NSF CAREER award, while his academic service encompasses editorial board membership at Administrative Science Quarterly and review work for top management journals. As an educator, he develops innovative courses like "Artificial Intelligence and the Future of Work" that prepare MBA students for technology-driven organizational transformation, emphasizing practical integration of AI systems while addressing ethical implications for workers and organizations.
Arlie Adkins serves as Associate Professor with dual appointments in the School of Landscape Architecture and Planning at the University of Arizona's College of Architecture, Planning and Landscape Architecture (CAPLA) and the Health Promotion Sciences Department within the Mel and Enid Zuckerman College of Public Health. He holds the position of Program Chair for the Master of Science in Urban Planning program and teaches transportation planning, planning theory, and capstone studios. Dr. Adkins earned his PhD in Urban Planning from Portland State University and Master's in City Planning from UC Berkeley. Prior to academia, he worked as a planner at TriMet (Portland's transit agency) and for carsharing pioneer Flexcar. His research program investigates transportation equity through three interconnected lenses: systemic health and safety disparities in urban transportation, socioeconomic applicability of walkability metrics, and affordable housing's role in enabling access to opportunity-rich neighborhoods. He emphasizes sociocultural contexts in built environment assessments, particularly focusing on Mexican American communities and refugee populations. His work integrates critical race theory to expose racial biases in transportation systems, as demonstrated by his nationally covered research on driver yielding behavior at crosswalks. Recent publications reveal a methodological shift toward qualitative assessment tools like the Qualitative Pedestrian Environments Data (QPED) Toolkit, addressing limitations of quantitative metrics in capturing social dimensions of walkability. His scholarship increasingly centers refugee mobility and Global South urbanism, reflecting expansion into transnational equity frameworks while maintaining core focus on transportation-housing-health intersections. Dr. Adkins has secured major funding from the Federal Highway Administration, National Institute for Transportation and Communities, and Centers for Disease Control and Prevention. He co-led the CDC-funded Physical Activity Policy Research Network (PAPRN+) collaborating center and directs the QPED initiative, which has trained practitioners through workshops including the 2019 Transportation and Communities Summit in Portland. His leadership extends to program development, evidenced by the MS Urban Planning program's #5 national ranking among public programs without PhDs by Planetizen (2023) and the UA Urban Planning Capstone's award for best graduate project from the Arizona APA chapter. He actively mentors students through capstone projects focused on transportation equity and housing justice.
Shane Dawson is the Executive Dean of UniSA Education Futures and Professor of Learning Analytics at the University of South Australia. His work bridges social network analysis and learner interaction data to enhance teaching quality and educational outcomes. Affiliation : University of South Australia Research Focus : Learning Analytics, Curriculum Mapping, K-12 Decision-Making Systems, and AI in Education Recent Research Trends : Shane’s 2025 publications emphasize generative AI for curriculum analytics, ethical considerations in K-12 dashboards, and longitudinal graduate attribute monitoring. His articles often integrate psychometric models, social network tools, and open-source software like OVAL and SNAPP . Advising and Collaboration : As a co-developer of key learning analytics tools and a supervisor for research students, he collaborates globally with institutions such as Johns Hopkins University and Shahid Beheshti University of Medical Sciences. Labs and Teams : Shane leads UniSA’s Teaching Innovation Unit and is a founding member of the Society for Learning Analytics Research , driving institutional and international initiatives in educational technology.
Alejandro J. Ganimian is an Associate Professor of Applied Psychology and Economics (with tenure) at New York University's Steinhardt School of Culture, Education, and Human Development, and a Visiting Associate Professor of Education at the Harvard Graduate School of Education. His interdisciplinary research bridges economics, psychology, and education policy to address critical challenges in educational systems, particularly in low- and middle-income countries, with a focus on transitioning from providing schooling to ensuring learning for all. Education: Doctorate in Quantitative Policy Analysis in Education (with concentration in economics) from Harvard University, where he was a fellow in the Multidisciplinary Program in Inequality and Social Policy Master's in Educational Research from the University of Cambridge, where he was a Gates Scholar Bachelor's in International Politics from Georgetown University Postdoctoral fellow at the Abdul Latif Jameel Poverty Action Lab (J-PAL) Ganimian's research centers on addressing educational challenges for "first-generation learners" in low- and middle-income countries. His methodology combines cutting-edge experimental designs from economics with innovative measures from education and psychology to evaluate causal effects of policies at scale. He specifically investigates how to prepare children for educational transitions, support teachers in large heterogeneous classrooms, and encourage principals to allocate resources to students who need them most. His work spans educational assessment, technology in education, teacher policies, and school management, with fieldwork conducted primarily in Latin America and South Asia. His research has been published in top journals including Nature , American Economic Review , Journal of Political Economy , and Review of Educational Research . Scientific Awards and Affiliations: Jacobs Foundation Research Fellow National Academy of Education/Spencer Foundation Post-Doctoral Fellow Gates Scholar Advisory-Board member at the Organization of Ibero-American States for Education, Science, and Culture (OEI) Non-Resident Fellow at the Center for Universal Education at the Brookings Institution Invited Researcher at the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT Member of the CESifo Network on Economics of Education Ganimian actively mentors doctoral students at NYU, with primary advisee Verónica Mesalles and secondary or co-advisees including Sorana Acris, Berta Bartoli, Arja Dayal, Trenel Francis-Porter, and Jessica Siegel. His former advisees have secured prestigious positions at institutions including Oxford University, UC Irvine, Duke University, and Stanford University. He has consulted for major international organizations including the Bill & Melinda Gates Foundation, World Bank, and Inter-American Development Bank, and co-founded educational initiatives "Enseñá por Argentina" and "Educar y Crecer" in Argentina.
María del Pilar Berrios Martos is a Professor in the Department of Psychology at the University of Jaén, Spain, specializing in Social Psychology with a focus on emotional intelligence and organizational dynamics. Education: PhD in Psychology, University of Granada (2001). Thesis: "Effects of congruence between personality style and task type on performance and satisfaction" supervised by Dr. José Miguel Ángel García Martínez. Research Focus: Her work examines emotional intelligence across educational and workplace contexts, including gender differences in team dynamics, leadership effects on performance, and well-being predictors. She develops assessment tools like the Video-Test of Emotional Intelligence for Teachers (ViTIED) and conducts cross-cultural validations. Publication Trends: Recent work (2020-2025) emphasizes meta-analyses of emotional intelligence in education, transformational leadership comparisons between public/private sectors, and Chilean scale validations. Methodologies include structural equation modeling and time-lagged designs. Research Group: Leads "PSYCHOSOCIAL ANALYSIS OF BEHAVIOR IN THE FACE OF THE NEW SOCIAL REALITY," investigating behavioral adaptations to contemporary social challenges through systematic reviews and empirical studies.
Jie Chen is an Assistant Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. Their research bridges machine learning with engineering analysis and design under uncertainty, focusing on process-structure-property-performance relationships. PhD, Mechanical Engineering (2022) – Arizona State University MS, Civil Engineering (2018) – Beihang University BS, Civil Engineering (2015) – Beihang University Research interests include: physics-informed machine learning, uncertainty quantification, predictive maintenance, materials design, and advanced manufacturing. The SEAD Lab develops methods to integrate engineering analysis into stochastic machine learning algorithms and uses AI for knowledge discovery in uncertain environments. Recent publications emphasize: Digital twin frameworks combining machine learning and Bayesian optimization Graph neural networks for high-entropy alloy and molecular mixture property prediction Physics-guided neural networks for fatigue life analysis of additively manufactured alloys Uncertainty quantification in imbalanced regression tasks and multi-fidelity data fusion Real-time imaging of polymer deformation mechanisms The lab actively mentors students, including PhD candidate Yisheng Lu, and manages projects in predictive maintenance, fatigue modeling, and materials design.
Núria Agell Jané is a Full Professor at ESADE Business School , Universitat Ramon Llull, specializing in Artificial Intelligence and Decision-Making Systems. She leads the JUICE (Judgements and Decisions in the Market Place) research group and the ESADE D3 - Institute for Data-Driven Decisions . Doctorate in Applied Mathematics (Qualitative Reasoning Modelling), UPC-BarcelonaTech Bachelor's in Mathematics, University of Barcelona Her research focuses on Artificial Intelligence , Decision-Making Systems , and Fuzzy Logic , with applications in Business, Marketing, and Sustainability. Recent publications emphasize Hesitant Fuzzy Linguistic Term Sets , Consensus Modeling , and AI in Sustainable Development . She coordinates multiple publicly and privately funded projects applying AI to Business and Marketing challenges. As PhD Programme Director (2005-2013) and current Department Director of Operations, Innovation and Data Sciences , she has shaped academic and research strategies at ESADE. Her work spans collaborations with institutions like LAAS-CNRS (France) and University of Edinburgh Business School , with over 40 journal publications and 50 conference contributions. She has directly supervised 11 PhD students in AI and Decision Sciences.
Katherine B. Grevelding, an Associate Professor of Physical Therapy at Quinnipiac University's School of Health Sciences, serves as the DPT Program Director. With expertise in anatomy education and interprofessional collaborative practice (IPCP), she has been instrumental in shaping physical therapy curricula and advancing patient-centered care initiatives. Education: BS (University of Virginia), MSPT/DPT (MGH Institute of Health Professions), EdD (University of St. Augustine) Her research focuses on anatomy pedagogy , assessment in clinical sciences , and interdisciplinary teaching . Recent publications highlight innovations in virtual interprofessional learning and biomechanical analysis for sports injury prevention. Key trends in her work include: Development of assessment frameworks for clinical science competency Advancements in anatomy education using collaborative technologies Biomechanical studies in sports physical therapy Integration of mental health stigma reduction into athletic care Scientific recognition includes: School of Health Sciences Interprofessional Education Fellow (2020-2022) Board Certified Orthopedic Clinical Specialist, Emeritus (2021) As a Capstone research mentor and committee member across university, school, and department levels, she contributes to institutional governance and student development. Her involvement in the Anatomy Education Special Interest Group and leadership roles in professional organizations like the American Physical Therapy Association (APTA) underscore her influence in the field.
Tania Lombrozo serves as the Arthur W. Marks ’19 Professor at Princeton University, leading the Concepts and Cognition Lab where she investigates the psychological and philosophical dimensions of human reasoning. Her work uniquely integrates empirical methods from cognitive science with conceptual frameworks from analytic philosophy. Her academic background includes a Ph.D. from Harvard University, establishing her foundation in interdisciplinary research approaches. Lombrozo's research centers on the human drive to explain, examining why we seek explanations for certain phenomena but not others, how explanation-seeking affects learning, and whether explanatory processes serve epistemic goals or introduce reasoning errors. She explores connections between causal reasoning, moral responsibility, and intuitive theories of knowledge, drawing from cognitive, social, and developmental psychology alongside philosophy of science and moral philosophy. Her methodology emphasizes experimental rigor while addressing normative questions about ideal reasoning. Analysis of her 2024-2025 publications reveals dominant themes in explanation evaluation across scientific and moral contexts, with significant attention to jargon in science communication, simplicity principles (Ockham’s razor), and moral responsibility in collective action. Her work increasingly addresses AI-human interaction, particularly how explanations influence trust in large language models and the cognitive effects of chain-of-thought reasoning. Notable honors include: Arthur W. Marks ’19 Professorship Excellence in Mentoring Graduate Students Award Lombrozo actively mentors graduate students including Sarah Joo, Casey Lewry, and Sebastian Montesinos, with research supported by interdisciplinary grants spanning cognitive science, ethics education, and technology policy. Her Concepts and Cognition Lab functions as a collaborative hub where philosophical questions are tested through behavioral experiments, contributing to both theoretical advances and practical applications in science communication and AI design.
Lynn Helding serves as Professor of Practice in Voice and Vocal Pedagogy at the University of Southern California's Thornton School of Music, where she also coordinates the Vocology & Voice Pedagogy program. She is a distinguished author, most notably of The Musician's Mind: Teaching, Learning and Performance in the Age of Brain Science , and was appointed Editor-in-Chief of the Journal of Singing in 2023. With decades of experience as both a performer and pedagogue, Helding bridges the gap between voice science and artistic practice, advocating for cognitive science as the "Third Pillar of Voice Science" alongside physiology and acoustics. Helding's educational background includes: Master's Degree in Vocal Pedagogy with Distinction from Westminster Choir College of Rider University (2005) Artist Diploma from Indiana University (1988), where she was the first singer ever accepted into this prestigious program Completion of the Summer Vocology Institute at the National Center for Voice and Speech Helding's research focuses on the application of cognitive science to voice pedagogy, with particular emphasis on motor learning theory and expertise studies from social psychology. She pioneered the concept of cognitive science as the "Third Pillar of Voice Science," arguing that understanding the brain's role is essential for effective voice teaching. Her work challenges traditional approaches by emphasizing the "how" of teaching over the "what," advocating for science-informed (rather than science-based) pedagogy that respects both scientific findings and artistic tradition. Helding's research has significant implications for addressing performance anxiety, optimizing practice methods, and developing more effective teaching strategies that account for how musicians actually learn. Her scholarly contributions demonstrate a consistent focus on bridging cognitive science with practical voice teaching. Rather than treating voice science as purely technical knowledge, Helding examines how this information can be effectively communicated to students, recognizing that the delivery method is as important as the content itself. This approach has led to innovative frameworks for evidence-based voice pedagogy that consider both physiological realities and cognitive processing limitations. Helding's significant recognition includes: Lifetime Achievement Award from the Contemporary Commercial Music (CCM) Vocal Pedagogy Institute at Shenandoah University (2020) Van L. Lawrence Fellowship, jointly awarded by the Voice Foundation and the National Association of Teachers of Singing Foundation (2005) Induction into the prestigious American Academy of Teachers of Singing (2022) Recognition as a "legendary figure in the field of voice pedagogy" As an educator, Helding maintains a thriving studio with private clients including members of the Los Angeles Opera and Los Angeles Master Chorale. Her USC Thornton voice students have earned fellowships to prestigious programs including the Aspen and Tanglewood Music Festivals. She has presented masterclasses described as "life-altering" at major voice conferences throughout the United States, Europe, and Australia. Helding previously served twenty-two years as Associate Professor of Voice and Director of Performance Studies at Dickinson College, and four years as voice faculty at Vanderbilt University's Blair School of Music. Helding is actively involved with the USC Voice Center at Keck Medicine of USC as a team member, where she applies her vocology expertise to help singers with functional vocal issues and those recovering from voice surgery. She is a co-founder of the NATS Science-Informed Voice Pedagogy Institute and frequently collaborates with voice scientists and medical professionals to advance the field of vocology.
Kathryn Stolee is an Associate Professor in the Department of Computer Science at North Carolina State University. She received her Ph.D. in Computer Science from the University of Nebraska-Lincoln under Sebastian Elbaum after graduating from the Jeffrey S. Raikes School of Computer Science and Management. Her research spans multiple perspectives in software engineering: technical (program analysis), human (human aspects of software engineering, software product management), and educational (comparative comprehension of algorithms). Notable contributions include work on regular expression refactoring for improved comprehension, constraint solvers for code reuse identification, and cross-language code-to-code search to aid developers learning new languages. Dr. Stolee has secured over $2,000,000 in federal grants, including an NSF CAREER award. Her research combines analysis techniques (refactoring, semantic code search, code-to-code search) with human factors (comprehension, reuse, learning). Her scholarly contributions have been recognized with a National Science Foundation Faculty Early CAREER Award (2018) and a Best Paper Award at the International Symposium on Empirical Software Engineering and Measurement (ESEM, 2011). Actively engaged in the software engineering research community, Dr. Stolee serves as an author, reviewer, and organizer at top conferences. She is committed to mentoring the next generation of computer scientists and has developed educational interventions focused on software testing and code comprehension.
Ridhi Kashyap is a Professor of Demography and Computational Social Science at the University of Oxford, where she contributes significantly to demographic research through innovative computational approaches. She is affiliated with the Leverhulme Centre for Demographic Science, where she co-leads the Digital and Computational Science strand. Her work bridges traditional demographic methods with cutting-edge computational techniques to address pressing social issues related to population dynamics and inequalities. Dr. Kashyap's research spans multiple areas of demography, with particular focus on: Mortality and population health, including pandemic impacts on life expectancy Gender inequality, especially son preference and digital gender gaps Marriage and family dynamics in relation to educational expansion and gender norms Migration and ethnicity patterns using digital data sources Sustainable development goals related to digital access and gender equality Her methodological expertise lies at the intersection of demography and computational social science. She leverages agent-based models, microsimulation, and machine learning techniques applied to novel data streams such as digital trace data from social media platforms. A notable example of her work is the digitalgendergaps.org platform, which nowcasts global digital gender inequalities in internet and mobile access - a key sustainable development goal indicator where official data is lacking. Her research demonstrates how computational approaches can fill critical data gaps and provide timely insights for policy decision-making. Analysis of Dr. Kashyap's recent publications reveals a strong focus on digital demography and computational approaches to understanding population dynamics. Her work frequently examines gender inequalities through digital lenses, including analyses of LinkedIn data to understand professional gender gaps and social media data to track digital access disparities. She has made significant contributions to understanding pandemic mortality patterns, particularly in India and the US, and has pioneered methods for using social media data to nowcast demographic phenomena. Her research consistently bridges theoretical demographic concepts with practical computational methodologies. Dr. Kashyap has been actively involved in several significant research initiatives, including leading the development of the Digital Gender Gaps dashboard and contributing to the creation of the World Cybercrime Index. Her work with the Leverhulme Centre for Demographic Science has positioned her at the forefront of computational demographic research. Within her academic role, Dr. Kashyap supervises graduate students and collaborates with interdisciplinary teams across demography, computer science, and public health. She has secured funding for projects that leverage digital data to address demographic research questions, particularly those related to gender inequality and sustainable development goals. Her work with social media data platforms demonstrates innovative approaches to overcoming traditional data limitations in demographic research. Dr. Kashyap co-leads the Digital and Computational Science strand at the Leverhulme Centre for Demographic Science, where she oversees a team of researchers working at the intersection of demography and computational methods. Her team develops innovative approaches to using digital trace data for demographic research, with particular focus on gender inequality metrics and pandemic impact assessment. The Digital Gender Gaps project represents one of her team's flagship initiatives, providing near-real-time monitoring of a key sustainable development indicator.
