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Xin GuoView profile

Professor

• Mathematical Finance
• Financial Engineering
• FinTech
• +7 more

Xin Guo is Professor and Department Chair of Industrial Engineering and Operations Research (IEOR) at UC Berkeley's College of Engineering, holding the Coleman Fung Chair in Financial Modeling. Her research bridges mathematical finance, stochastic control, and machine learning with applications in risk analytics and quantitative trading. Education: Ph.D. in Mathematics, Rutgers University (1999) Research Interests: Professor Guo's work centers on mathematical finance , stochastic games , and reinforcement learning . She develops theoretical frameworks for α-potential games and mean-field systems while applying signature methods and GANs to financial data. Her research addresses critical problems in portfolio optimization, fraud detection (e.g., Medicare analytics), and market forecasting, emphasizing the intersection of stochastic control with machine learning for real-world decision-making under uncertainty. Publication Trends: Recent work (2023-2025) shows increasing focus on multi-agent reinforcement learning through mean-field game theory, with applications spanning finance (corporate bonds, trading), healthcare (fraud detection), and transportation (rate forecasting). Key innovations include BSDE approaches for stochastic games, signature-based time series analysis, and theoretical guarantees for GAN training dynamics. Scientific Awards: Holds the prestigious Coleman Fung Chair in Financial Modeling, reflecting significant contributions to quantitative finance research. Advising and Grants: As IEOR Department Chair, Professor Guo mentors graduate students in stochastic modeling and financial engineering. Her research is supported by the Coleman Fung Endowment Fund, with collaborations spanning finance, healthcare, and transportation sectors through industry partnerships. Labs and Teams: Leads the Risk Analytics & Data Analysis Research (RADAResearch) Lab ( https://risklab.ieor.berkeley.edu/ ), which develops cutting-edge methodologies for risk assessment, data-driven decision-making, and game-theoretic solutions to complex systems. The lab fosters interdisciplinary work connecting mathematical theory with practical applications in FinTech and beyond.

Tatyana YordanovaView profile

Associate Professor

• Figure Skating
• Short Track Speed Skating
• Ice Dancing
• +7 more

Assoc. Prof. Tatyana Yordanova is affiliated with the National Academy of Sports in Bulgaria, where she serves in the Faculty of Sports and Department of Technical and Ice Sports . She holds the academic rank of Associate Professor and has been leading the department since 2024. Education: Master's from State Central Institute of Physical Culture (1987); Doctorate in Sports Science (2019) Languages: English, Italian, Russian Her research focuses on technical elements in figure skating , speed-power abilities , balance stability , and judging systems . She has extensively studied jump mechanics and anthropometric factors in skaters. Her publications from 2018-2024 include studies on judging systems, jump techniques, and sports management. Key themes in her work involve training methodology, competition analytics, and biomechanics of skating. Since 2002, she has worked as an international figure skating judge, including at the Sochi 2014 Olympics . She chaired the Bulgarian Skating Federation (2011-2023) and participated in projects like Erasmus+ mobility (2022, 2024). Her pedagogical career includes roles as scientific assistant (1988), senior assistant (2006), and associate professor (2023).

Anthony CaterisanoView profile

Professor

• Exercise Physiology
• Resistance Training
• Sports Medicine
• +3 more

Anthony Caterisano is a Professor of Health Sciences at Furman University, with over 35 years of academic and athletic leadership. He holds a Ph.D., M.A., and B.S. from The University of Connecticut, SUNY, and UNC Chapel Hill. His research focuses on exercise physiology, resistance training, and sports medicine, with notable publications in journals like Medicine and Science in Sports and Exercise . Dr. Caterisano is a Fellow of the American College of Sports Medicine (FACSM) and has authored/co-authored books on football training and resistance techniques. He has served as wrestling coach at Furman, Spartanburg Methodist College, and currently coaches at Wade Hampton High School. As a competitive powerlifter, he has secured 16 South Carolina state titles, 10 national titles, and 10 world gold medals in masters-level competitions. His work bridges scientific research and practical application, with grants and presentations on topics like strength training methodologies and cardiovascular adaptations. Key contributions include studies on Tsunami Barbell training, metabolic responses to exercise, and core muscle engagement. His awards reflect both academic excellence and athletic achievement, while his grants and presentations underscore his commitment to advancing sports science.

Pasquale BottalicoView profile

Associate Professor

• Vocal Load
• Professional Voice Techniques
• Singer Techniques
• +3 more

Pasquale Bottalico serves as Associate Professor in the Department of Speech and Hearing Science at the University of Illinois, with dual appointments as Associate Professor at the Center for Latin American and Caribbean Studies and Affiliate Faculty in the School of Music. His unique interdisciplinary profile bridges engineering, music performance, and speech science, reflecting his dual academic training and professional artistry. His educational foundation includes: Bachelor's in Telecommunications Engineering from Univeristà Mediterranea di Reggio Calabria, Italy Concurrent Opera Singing degree from F. Cilea Music Academy, Reggio Calabria Master's in Telecommunications Engineering from Politecnico di Torino, Italy Ph.D. in Metrology specializing in acoustics measurement uncertainty and classroom acoustics Dr. Bottalico's research centers on vocal load quantification and professional voice techniques , with significant contributions to understanding vocal fatigue in teachers and singers. His work spans Speech Intelligibility in educational environments, Room Acoustics for performance and learning spaces, and Musical Acoustics of historical vocal styles. A distinctive thread throughout his research examines how acoustic conditions modulate voice production and perception, increasingly incorporating virtual reality and bone conduction technologies for innovative assessment and intervention approaches. His Colombian vocal health study demonstrates cross-cultural applications of his work. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) The impact of noise and dysphonia on children's speech processing in educational settings, using multimodal assessment including EEG; (2) Virtual reality applications for voice production research and therapeutic intervention; (3) Cross-cultural validation of vocal fatigue metrics and development of biofeedback systems. His work consistently bridges engineering precision with clinical applicability, particularly for professional voice users in challenging acoustic environments. No scientific awards were documented in the available information. While specific advising relationships aren't detailed, his research collaborations span international institutions including Colombian and Italian universities, suggesting graduate mentorship in interdisciplinary projects. No grant information was provided, though his systematic reviews and cross-cultural studies imply externally funded research activities. Though no dedicated laboratory is specified, his virtual reality voice studies and acoustic parameter assessments suggest affiliations with audio engineering facilities and voice clinics, likely through the Speech and Hearing Science department's research infrastructure.

Sara StymneView profile

Senior Lecturer

• Computational Linguistics
• Natural Language Processing
• Cross-lingual NLP
• +7 more

Sara Stymne is a Senior Lecturer in Computational Linguistics at the Department of Linguistics and Philology, Uppsala University, where she has been working since 2012. She initially joined as a post-doc (2012-2015), then worked as a researcher (2015-2017), and served as an assistant professor (2017-2023) before her current position as Senior Lecturer. Prior to Uppsala, she was a researcher at Linköping University's Department of Computer and Information Science. Dr. Stymne earned her PhD in Computational Linguistics from Linköping University in 2012 with the thesis 'Text Harmonization Strategies for Phrase-Based Statistical Machine Translation,' following a Licentiate degree in Computational Linguistics (2009) and a Master's degree in Cognitive Science (2006), both also from Linköping University. During her doctoral studies, she spent the autumn of 2010 and spring of 2009 at Xerox Research Centre Europe in Grenoble, France. Her primary research interests focus on cross-lingual natural language processing and digital humanities, with particular emphasis on multilingual dependency parsing. Dr. Stymne is passionate about applying computational linguistics to solve research questions in other fields, including language history, literary analysis, and political science. Her earlier work concentrated on machine translation, with specific interests in discourse-aware translation, compound processing, and error analysis. She has made significant contributions to the development of language technology tools for analyzing dialogue, narrative, and stylistic features in literature. Analysis of Dr. Stymne's recent publications reveals a strong focus on cross-lingual and cross-domain natural language processing. Her work spans multiple subfields including dependency parsing across genres and topics, discourse relation analysis in low-resource languages like Egyptian Arabic, direct speech identification in Swedish literature, and causality detection in governmental documents. A notable trend is her application of NLP techniques to digital humanities problems, particularly in analyzing literary texts and historical language change. Her research often involves creating and utilizing specialized datasets for specific linguistic phenomena across multiple languages. Dr. Stymne actively supervises graduate students, having guided numerous master's and bachelor's theses on topics ranging from speech recognition to multilingual parsing and causality detection. She leads or participates in several research projects including 'Fictional prose and language change' (funded by VR, 2021-2023) and 'Enabling climate-resilient development' (funded by Marianne and Marcus Wallenberg Foundation, 2023-2027), demonstrating her commitment to interdisciplinary research with practical applications. Her work has resulted in several notable software resources including uuPronPred for cross-lingual pronoun prediction, uuparser for dependency parsing, and Docent for document-level machine translation. Within the Computational Linguistics and Language Technology group at Uppsala University, Dr. Stymne contributes to multiple research initiatives focused on developing language technology tools for digital humanities applications. Her team works closely with literary scholars and historians to create computational methods for analyzing large corpora of literary texts, particularly focusing on Swedish literature across different historical periods. Her research bridges the gap between theoretical computational linguistics and practical applications in the humanities, creating new methodologies for quantitative analysis of literary and historical texts.

Gary PielakView profile

Professor

• Protein Biophysics
• In-Cell NMR Spectroscopy
• Macromolecular Crowding
• +3 more

Gary Pielak is a Kenan Distinguished Professor of Chemistry, Biochemistry, and Biophysics at the University of North Carolina at Chapel Hill, with a joint appointment in the School of Medicine. His research focuses on high-resolution protein NMR studies in living cells and the biophysics of tardigrade desiccation-tolerance proteins, bridging structural biology and molecular biophysics. Education: BS in Chemistry from Bradley University (1977), PhD in Biochemistry from Washington State University (1983), Postdoc at the University of British Columbia (1983-1986), Postdoc at Oxford University (1986-1988). Research Interests center on understanding protein structure, stability, and function in physiologically relevant environments. Key areas include: In-Cell NMR: Quantifying protein behavior in living cells using advanced NMR techniques. Macromolecular Crowding: Studying synthetic polymers and proteins as crowding agents to mimic cellular environments. Tardigrade Biology: Exploring desiccation-tolerance mechanisms in intrinsically disordered proteins from water bears. Recent Publications highlight interdisciplinary trends, combining AI-driven stability prediction, solid-state NMR for dry protein analysis, and molecular glass/gel applications for preservation. His Scientific Awards include: NIH Pioneer Award DuPont and Morrow Young Faculty Awards Multiple UNC Mentorship Awards Mentorship is a cornerstone, with a focus on training graduate students and advancing NMR methodologies. His group employs Research Methods : 19F, 1H, 15N, and 13C NMR Circular Dichroism and Calorimetry Protein Expression in E. coli

Clio AndrisView profile

Associate Professor

• Information Visualization
• Geovisualization
• GIS
• +4 more

Clio Andris is an Associate Professor at Georgia Tech, jointly appointed in the School of City and Regional Planning and the School of Interactive Computing. She directs the Friendly Cities Lab, focusing on mathematical models of social networks applied to urban planning, transportation, and geography. Her work integrates spatial analysis with visualization, emphasizing interdisciplinary collaboration. Education and Career: Andris earned a PhD in Urban Information Systems from MIT (2011), where she was an NDSEG Fellow. She held postdoctoral positions at Singapore-MIT Alliance for Research and Technology and the Santa Fe Institute. Prior to Georgia Tech, she was a faculty member at Penn State’s Department of Geography, affiliated with the GeoVISTA Center. Research Focus: Her research bridges social networks, geovisualization, and urban informatics. Key areas include spatial social network analysis, GIS applications for urban policy, and the impact of digital tools on civic engagement. She has developed innovative visual analytics tools like SNoMaN and ROBIN to democratize spatial data exploration. Awards: She received the NSF CAREER Award (2021) and NDSEG Fellowship (2011). Her lab is affiliated with the Center for Spatial Planning Analytics and Visualization (CSPAV) and the Information Visualization Lab. Labs and Collaborations: The Friendly Cities Lab focuses on socially just urban design through computational methods. Her work addresses issues like food security networks, pandemic impacts on biodiversity, and community mapping for activism. Grants and Outreach: Her NSF-funded projects emphasize public good applications, such as real-time pandemic risk communication and educational tools for migration data. She actively collaborates with non-profits and policymakers to translate research into actionable urban strategies.

• Early Childhood Education
• Art Education
• Play-Based Learning
• +5 more

Felicity McArdle is a Professor in the Department of Early Childhood Education within the Faculty of Education at Queensland University of Technology. With a distinguished career spanning over two decades, her work centers on reimagining early childhood pedagogy through critical lenses of social justice, art education, and play-based learning. Her research has significantly influenced Australian early childhood policy and practice. McArdle's research interests demonstrate a consistent commitment to transformative education. She critically examines how art and play function as vehicles for social justice, challenging neoliberal discourses in early childhood education. Her work on refugee children's artistic expression and anti-bias curriculum development reveals her dedication to equity-oriented pedagogy. Through collaborative drawing methodologies and visual research approaches, she has pioneered innovative ways of understanding children's perspectives. Her publication trends reveal a sophisticated evolution from foundational work on visual arts in education (2001-2010) toward increasingly critical examinations of power, policy, and social justice (2011-2021). The consistent citation impact of her work—particularly her 2002 paper 'Early Childhood Art Education: A Palimpsest' with over 13,000 citations—demonstrates her field-defining contributions to reconceptualizing art education as critical praxis. McArdle has held significant editorial roles including co-editing the influential 2013 volume 'Young Children, Pedagogy and the Arts' and serving on the editorial board of Australian Journal of Early Childhood. Her collaborations with leading scholars like Susan Grieshaber, Jennifer Sumsion, and Linda Knight have produced seminal work on intentional teaching and play-based learning. Her research methodology expertise centers on visual and arts-based approaches, particularly collaborative drawing techniques that engage children as active research participants. This methodological innovation reflects her commitment to ethical research practices that honor children's agency while generating meaningful insights about early childhood experiences.

• Mental Health Policy
• Implementation Science
• Health Equity
• +3 more

Briana S. Last is an Assistant Professor of Clinical Psychology at Stony Brook University, with a PhD from the University of Pennsylvania (2022). Her work focuses on improving mental health equity through policy research, implementation science, and community-based approaches. She examines social determinants of mental health, mental health workforce development, and clinical decision-making in public systems. Dr. Last leads the Mental Healthcare for All Lab, collaborating with governments, agencies, and clinicians to strengthen public mental health systems. Her research emphasizes workforce sustainability, anti-transgender policy impacts, and clinician well-being. She has published in high-impact journals like The Milbank Quarterly and Psychiatric Services . Her interdisciplinary methods combine qualitative and quantitative approaches, including mixed methods and implementation science frameworks. Current projects address workforce retention strategies, telehealth policy implications, and the sociopolitical context of gender-affirming care. Education: PhD in Clinical Psychology, University of Pennsylvania (2022) Labs: Mental Healthcare for All Lab Key Themes: Behavioral health policy, health equity, clinician-patient dynamics, LGBTQ+ mental health

• Neuropsychology
• Clinical Neuropsychology
• Cognitive Neuroscience
• +4 more

Cara Lena Crook, PhD, is an Assistant Professor in the Department of Neurology at Yale School of Medicine. She specializes in neuropsychology, focusing on how brain function affects cognition, emotion, and behavior in patients with neurological and psychological conditions. Institution: Yale School of Medicine Department: Neurology Academic Rank: Assistant Professor Dr. Crook earned her PhD in Clinical Neuropsychology from Fordham University, completed her residency at Alpert Medical School of Brown University, and a fellowship at VA Boston Healthcare System, where she advanced her skills in neuropsychological assessment and intervention. Her research and clinical interests center on understanding the neural basis of cognitive and emotional processes. She works at the intersection of neurology and psychology, contributing to patient care, teaching, and scholarly activity in clinical neuropsychology. Though specific publications are not listed, her work likely spans assessment methodologies, cognitive disorders, and brain-behavior relationships in neurological populations. Dr. Crook is actively engaged in the academic and clinical missions at Yale, with no indication of part-time status or retirement. She is not noted as a former staff member and is currently contributing to the department’s educational and research initiatives. PhD: Fordham University, Clinical Neuropsychology (2022) Residency: Alpert Medical School of Brown University, Neuropsychology (2022) Fellowship: VA Boston Healthcare System (2024) She has not been cited as having formal advisees or receiving specific scientific awards in the available text. There is no mention of grants, labs, or research teams she leads, though her fellowship and academic appointments suggest active involvement in clinical research and training.

• Machine Learning
• Computational Neuroscience
• Artificial Intelligence
• +7 more

Aapo Hyvärinen is a Professor of Computer Science at the University of Helsinki , affiliated with the Helsinki Institute for Information Technology and the Helsinki Probabilistic Machine Learning Lab . He previously held the position of Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London (2016-2019). Education : Undergraduate Mathematics at University of Helsinki, Vienna, and Paris; Ph.D. in Information Science from Helsinki University of Technology (1997) His research focuses on machine learning and computational neuroscience , particularly: Independent Component Analysis (ICA) Natural Image Statistics Causal Representation Learning Neural Signal Processing Applications to brain imaging (MEG, CryoEM) Recent publications emphasize causal discovery , identifiable machine learning , and nonlinear ICA . Key projects include: VETURI (AI for health) DIGIMIND (AI in mental health) CIFAR grants (2022-2025) Scientific awards : Highly Cited Researcher (2010) He serves as Action Editor for the Journal of Machine Learning Research and Neural Computation , and has held Area Chair roles at NeurIPS, ICML, ICLR, AISTATS, and UAI conferences. His work bridges theoretical machine learning with neuroscience and philosophical implications of artificial intelligence .

Paweł ChmuraView profile

Professor

• Exercise Physiology
• Sports Science
• Football Performance Analysis
• +3 more

Professor Paweł Chmura is a Full Professor at Wrocław University of Health and Sport Sciences, specializing in Sports Sciences with a focus on football performance analysis. He serves in the Department of Individual and Team Sports, where he conducts research on exercise physiology, training load monitoring, and physical activity analysis in soccer players. With over 130 publications, Professor Chmura is a recognized expert in sports science and also holds a UEFA A coaching license. Professor Chmura's research interests center on exercise physiology, particularly in the context of team sports. His work extensively examines repeated maximum effort capabilities, physical activity analysis in soccer players, and monitoring training loads. He has developed innovative concepts such as the Psychomotor Fatigue Threshold and investigates how environmental factors like temperature and air quality affect athletic performance. His research bridges the gap between theoretical sports science and practical coaching applications, making significant contributions to football performance optimization. Professor Chmura's extensive publication record demonstrates a consistent focus on soccer performance analysis, with recent work expanding into multidisciplinary approaches including physiological, psychological, and tactical aspects of the game. His research shows increasing sophistication in methodology, incorporating advanced monitoring technologies and comprehensive analysis frameworks that consider multiple performance indicators simultaneously. This evolution reflects broader trends in sports science toward integrated, holistic approaches to athlete performance. Professor Chmura actively supervises the Motosoccer Student Research Club and invites master's and doctoral students to collaborate on research projects related to football, exercise physiology, game analysis, and motor preparation. His mentorship extends beyond formal academic supervision to practical coaching guidance, leveraging his UEFA A coaching certification to provide students with both theoretical knowledge and practical field experience. As a UEFA A-licensed football coach and tennis instructor, Professor Chmura maintains strong connections between academic research and practical sports applications. He leads the Motosoccer Student Research Club, which provides hands-on research opportunities for students interested in sports science. His dual expertise in academic research and practical coaching creates a unique environment for applied sports science research that directly impacts coaching methodologies and athlete development.

Anand N.K.View profile

Professor

• Physics-Informed Neural Networks
• Finite Volume Techniques
• Reduced Order Modeling
• +5 more

N.K. Anand is a Distinguished Professor of Mechanical Engineering at Texas A&M University, holding the James J. Cain III Regents Professorship. He leads research in advanced computational methods and thermal-hydraulic systems, with affiliations to Multidisciplinary Engineering and Nuclear Engineering programs. His work focuses on physics-informed machine learning, finite volume methods, and aerosol transport in nuclear reactor contexts. Education: PhD (Mechanical Engineering, Purdue University, 1983), M.S. (Kansas State University, 1979), and B.E. (Bangalore University, 1978). Awards include the ASME James Harry Potter Gold Medal (2020) and multiple teaching/administrative excellence awards from Texas A&M. Research emphasizes fluid dynamics modeling (e.g., PINNs for periodic flows, turbulent deposition studies), heat pipe systems, and nuclear reactor thermal-hydraulics. His Versatile Test Reactor (VTR) contributions include cartridge loop designs and aerosol transport experiments. Active in high-temperature reactor safety, with facilities studying pebble beds, helical coil exchangers, and HTGR upper plenum dynamics. Publications span physics-informed ML applications, finite volume techniques, and nuclear thermal systems. Grants supported development of advanced CFD tools and reactor safety infrastructure. His lab collaborates on international nuclear energy projects and emerging AI-driven simulation methodologies.

Matthew GarverView profile

Professor

• Exercise Science
• Human Performance
• Resistance Training
• +3 more

Matthew Garver is a Professor and Chair of the Department of Nutrition, Kinesiology, and Health at the University of Central Missouri (UCM). He joined UCM in Fall 2016 after completing his Ph.D. in Exercise Science at The Ohio State University and teaching for five years in Abilene, Texas. Education: Ph.D. in Exercise Science (The Ohio State University) Garver’s research focuses on applied human performance, with emphasis on resistance training, interlimb asymmetry in athletes, and the intersection of exercise science with diversity, equity, and inclusion (DEI). His work spans collegiate sports, track and field, and health interventions for special populations. Recent publications highlight his exploration of artificial intelligence in sport science ethics, DEI initiatives in exercise research, and position-specific training in collegiate female soccer. His studies also address exercise-induced bronchoconstriction, biomechanical asymmetry in American football players, and affective responses to resistance training. Garver has contributed to understanding physical activity’s role in older adults, particularly patients with knee osteoarthritis, through the IMPACT-P trial. His interdisciplinary approach bridges kinesiology, physiology, and social science in promoting health and athletic performance. At UCM, he teaches courses in Kinesiology and leads research initiatives aimed at optimizing human performance and health outcomes through evidence-based strategies.

• Machine Learning
• Natural Language Processing
• Artificial Intelligence
• +4 more

Danqi Chen is an Associate Professor in the Department of Computer Science at Princeton University's School of Engineering and Applied Science. Their research focuses on advancing large language models (LLMs), with emphasis on model alignment, safety, and long-context reasoning capabilities. Key research areas: LLMs, AI safety, retrieval systems, and model optimization Recent work explores theorem proving, context encoding, and ethical content generation Their 2025 publications highlight innovations in formal verification scaffolding, attention mechanism efficiency, and copyright-aware generation. 2024 studies investigate continual memorization, rule-based chatbot representations, and scientific literature retrieval benchmarks. Current projects demonstrate commitment to improving model robustness, interpretability, and security compliance in multimodal systems.