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Daniel A NewmanView profile

Professor

• Industrial-Organizational Psychology
• Diversity in HR Management
• Leadership
• +7 more

Daniel A Newman is a Professor in the Department of Psychology at the University of Illinois, with additional affiliations at the School of Labor and Employment Relations. His research spans industrial-organizational psychology, leadership, and diversity in human resources. Ph.D. from Pennsylvania State University B.A. from Rice University His research focuses include: Diversity in HR management (racial equality in hiring, adverse impact) Leadership dynamics (gender, personality dominance, emotional/social skills) Social network analysis (contagion effects, multilevel modeling) Emotional intelligence (cascading models, gender implications) Narcissism (leadership applications, counterproductive behavior) Work engagement (attitude models, temporal factors) His publications emphasize meta-analytic methodologies and theoretical integration across organizational behavior, personality psychology, and HR practices. Key themes include cross-cultural leadership analysis, diversity optimization, and ethical workplace dynamics. Scientific awards include: Sage/McDonald Advancement of Organizational Research Methodology Award (2020) Best Paper in Personnel Psychology (2020) Elected Division Chair (2013-2018), Academy of Management Multiple teaching and early career awards As a prolific researcher, Newman contributes to organizational research methods and construct development while maintaining active editorial and leadership roles in academic societies.

Sam Hartharn-EvansView profile

Research Fellow

• Physical Oceanography
• Cryosphere Interactions
• Fluid Dynamics
• +3 more

Sam Hartharn-Evans is a Research Fellow at Northumbria University in the Department of Geography and Environmental Sciences, focusing on cryosphere-ocean interactions through laboratory experiments and numerical modeling. His work investigates ice shelves, sea ice, and buoyant meltwater plumes in polar oceans. Education BSc in Marine Biology and Oceanography (Bangor University, 2018) MSc in Physical Oceanography (Bangor University, 2019) PhD in Applied Mathematics (Newcastle University, 2023) His research integrates fluid dynamics with environmental science, particularly studying internal solitary waves' behavior in stratified water columns and their impact on ice structures. Recent publications analyze wave-ice interactions, stratified shear instability, and nonlinear processes in geophysical fluids using both experimental and computational approaches. Current projects involve replicating ice shelf meltwater plumes in a 7m flume tank and conducting direct numerical simulations at laboratory scale. His work bridges oceanography, geophysics, and cryospheric science, with applications to climate modeling and polar environmental change.

Ali NadimView profile

Professor

• Fluid Dynamics
• Mathematical Modeling
• Scientific Computing
• +4 more

Ali Nadim is a Full Professor at Claremont Graduate University's Institute of Mathematical Sciences, Department of Physical Applied Mathematics. He holds a PhD in Chemical Engineering from MIT (1986) and has held prior appointments as Assistant Professor at MIT (1986–1991), Associate Professor at Boston University (1991–2001), and dual roles at Keck Graduate Institute (bioengineering) and CGU (applied mathematics) since 2001. Education: BS Chemical Engineering (UC Davis), PhD (MIT). Affiliations: Claremont Graduate University (2001–present), Keck Graduate Institute (2001–2010), Boston University (1991–2001). His research focuses on fluid dynamics, mathematical modeling, and scientific computing, with applications in biomedical engineering (e.g., alveolar surfactant dynamics, lab-on-chip devices) and multiphase flow systems. Notable contributions include: Thin film dynamics on rotating spheres and fibers. Electrowetting-driven microfluidic mixing. Modeling p53 signaling pathways in response to DNA damage. Mathematical analysis of bubbly liquids and viscoelastic drops. He has pioneered methods for simulating blood flow in arterial systems and contributed to patents on rapid lysis devices for nucleic acid diagnostics. His work bridges applied mathematics, engineering, and biomedicine, with over 150 peer-reviewed publications and extensive grant-funded research.

• Game Theory
• Operations Research
• Mathematical Economics
• +3 more

Julio González-Díaz is a university professor at the Department of Statistics, Mathematical Analysis, and Optimization at the Faculty of Mathematics, University of Santiago de Compostela. His research focuses on game theory, operations research, and decision models, with applications in economics and mathematics. He leads the research group MODESTYA (Optimization, Decision, Statistical Models and Applications) and is affiliated with the Galician Mathematical Research and Technology Center (CITMAga). Education: PhD from the University of Santiago de Compostela (2005), thesis titled Essays on Competition and Cooperation in Game Theoretical Models , supervised by Dr. María Estela Sánchez Rodríguez and Dr. Ignacio García Jurado. Research Interests: Game theory (cooperative and non-cooperative), operations research, optimization, and statistical models. His work includes studies on core stability, airport cost allocation, paired comparisons analysis, and algorithmic game theory. Publications: Over 30 peer-reviewed articles and books, including influential works like An Introductory Course on Mathematical Game Theory (2010) and widely cited contributions on core-center concepts and ranking methods. Recent work involves polynomial optimization algorithms (RAPOSa solver), gas transportation networks, and bilevel portfolio design. Collaborations: Extensive co-authorship network, including researchers like Fiestras-Janeiro, Sánchez-Rodríguez, and international collaborations in optimization and game theory. Contact: julio.gonzalez@usc.es

Loraine Lau-GeskView profile

Associate Professor

• Consumer Behavior
• Affect and Emotions in Decision Making
• Cultural Influences on Consumer Judgment
• +4 more

Loraine Lau-Gesk is an Associate Professor in the Marketing area at the Paul Merage School of Business, University of California, Irvine. She holds a PhD from UCLA and is actively engaged in research on consumer behavior, particularly focusing on emotional and cultural influences in decision-making processes. Her research centers on two primary domains: the role of affect and emotions in consumer decisions, and the impact of culture and self-concept on persuasion and judgment. She explores how consumers navigate complex, conflicting emotional experiences in real-world contexts such as advertising and consumption. Her work challenges traditional models that isolate single variables, instead advocating for more integrative approaches that reflect the multifaceted nature of consumer life. Professor Lau-Gesk’s research has significantly contributed to top academic journals including the Journal of Consumer Research , Journal of Marketing Research , Journal of Consumer Psychology , and Organizational Behavior and Human Decision Processes . Her publications reveal trends toward studying emotional complexity, cultural duality, and cognitive-affective interactions, offering counterintuitive insights that refine marketing theory and practice. PhD, University of California, Los Angeles While no specific awards or honors are listed in the provided text, her publication record in premier journals indicates significant scholarly recognition. There is no mention of formal advising roles, grants, or student mentorship in the available information. She does not appear to lead a named research lab or formal research team based on the current description, though her affiliation with the Merage School places her within a vibrant research community focused on innovation in business and consumer insights.

• Marketing Analytics
• Data-Driven Design
• Preference Measurement
• +7 more

Ryan Dew is an Assistant Professor of Marketing and the Govil Family Faculty Scholar at the Wharton School of the University of Pennsylvania. He is affiliated with the Wharton AI and Analytics Initiative, Wharton Human-AI Research, and the Penn Eidos LGBTQ+ Health Initiative. His research bridges marketing, data science, and machine learning, with a focus on developing interpretable computational tools for customer analytics and design. Research Interests: His work centers on marketing analytics, data-driven design, preference measurement, and decision support. He leverages Bayesian nonparametrics, deep generative models, and representation learning to analyze unstructured data (e.g., text, images) in marketing contexts such as branding, logo design, and influencer selection. His methodological approach emphasizes flexibility and interpretability in modeling consumer behavior. The recent publications reflect a strong trend toward integrating AI and machine learning into core marketing problems—particularly in customer segmentation, product design, and influencer marketing. There is a clear emphasis on adaptive systems, dynamic modeling, and the use of rich data sources to enhance decision-making. Scientific Awards: 2022 Frank M. Bass Award 2018 INFORMS SMS Doctoral Dissertation Award 2018 ASA Marketing Section Doctoral Research Award Finalist, 2019 Frank M. Bass Award Finalist, 2020 Paul Green Award Finalist, 2022 John D.C. Little Award 2023 MSI Young Scholar Wharton School's 2024-2025 Govil Family Faculty Scholar Wharton Teaching Excellence Award Advising and Grants: Ryan Dew teaches PhD and MBA courses including MKTG9570 (Empirical Models in Marketing) and MKTG7120 (Data & Analysis for Marketing Decisions). He advises PhD students through dissertation supervision (MKTG9950) and independent study. He co-organizes a cross-school virtual reading group on probabilistic ML and Bayesian computation for junior faculty and PhD students, indicating active mentorship and collaboration. While specific grants are not listed, his research awards and scholar designation suggest competitive funding support. Labs and Teams: He is actively involved in the Wharton AI and Analytics Initiative and Wharton Human-AI Research, suggesting participation in interdisciplinary research teams focused on AI applications in business. His collaborations span multiple institutions and disciplines, including psychology, computer science, and statistics.

Paul OhnoView profile

Assistant Professor

• Analytical Chemistry
• Physical Chemistry
• Environmental Chemistry
• +3 more

Paul Ohno is an Assistant Professor in the Department of Chemistry and Biochemistry at Auburn University. He leads the Ohno Research Group, which focuses on aerosol and interfacial spectroscopy. His research employs advanced analytical techniques like sum-frequency generation, fluorescence probe spectroscopy, and aerosol mass spectrometry to study chemical systems at surfaces and interfaces, particularly aerosol particles and liquid interfaces. Education: Ph.D. in Chemistry, Northwestern University (2014-2019) B.A. in Chemistry, Princeton University (2010-2014) Research interests include physical chemistry, environmental chemistry, and aerosol science. His lab develops tools to elucidate molecular details of interfacial systems, with a focus on aerosol particle surfaces and bulk liquid interfaces. Techniques used include second harmonic generation, fluorescence spectroscopy, and scanning mobility particle sizing. Key awards include the ACS Nobel Laureate Signature Award (2021), Schmidt Science Fellowship (2019), and Harvard Environmental Fellowship (2019). His work bridges multiple disciplines, addressing fundamental questions in environmental chemistry and materials science.

Annette Kopp-SchneiderView profile

Professor

• Medical Biometry
• Biostatistics
• Clinical Trials
• +7 more

Prof. Dr. Annette Kopp-Schneider is Head of Department at the German Cancer Research Center (DKFZ) and affiliated with the Faculty of Medicine at the University of Heidelberg. She holds a professorial rank and leads research in medical biometry with a focus on clinical trial methodology in precision oncology. Diploma in Mathematics, RWTH Aachen, 1984 Dr. rer. nat. in Mathematics, RWTH Aachen, 1987 Habilitation in Medical Biometry, University of Heidelberg, 1997 Her research interests include clinical trials for precision oncology , dose-response modeling , and biologically based mechanistic modeling of cell systems . She develops advanced statistical methods for trial design, particularly in pediatric oncology and settings with small sample sizes. Her work emphasizes rigorous control of type I error when borrowing historical data and optimal experimental designs for drug combinations. The recent publications reflect a strong trend in methodological biostatistics , particularly in Bayesian and frequentist approaches to clinical trial design , external data incorporation , and transparent evaluation in biomedical image analysis . Her contributions span oncology, toxicology, and translational medicine, with a consistent focus on statistical rigor and reproducibility. She has contributed to major initiatives such as the Pediatric Precision Oncology INFORM Registry, advancing personalized treatment for children with cancer. Her methodological work supports fair comparisons in hybrid and single-arm trials and improves the reliability of challenge-based research in medical imaging. Prof. Kopp-Schneider is actively engaged in grant-funded research and mentoring within her department. She leads a team focused on biostatistical innovation in clinical research, particularly in oncology settings where data are sparse and traditional designs face limitations. She is involved in collaborative teams working on biomedical image analysis challenges and pediatric cancer registries. Her lab contributes to open science through toolkits for challenge analysis and transparent reporting guidelines like BIAS (Transparent Reporting of Biomedical Image Analysis Challenges).

• Transportation and Logistics
• Supply Chain Management
• Applied Mathematics
• +3 more

Assoc Prof Ser Aik QUEK is an Honorary Fellow in the Department of Analytics and Operations at the National University of Singapore (NUS) Business School since January 2022. He holds a PhD in Sciences from the University of California, Berkeley (1987), preceded by a Master of Science from MIT (1981), a Diploma in Mathematical Statistics from the University of Cambridge (1978), and a First-Class Honors Bachelor of Science from Victoria University of Manchester (1975). His research focuses on Transportation & Logistics , Applied Mathematics , and Machine Learning , with notable contributions to manufacturing strategy, healthcare operations, and appointment systems optimization. His work often employs advanced statistical methods like the ACE algorithm to analyze nonlinear relationships in complex systems. Teaching Philosophy: Prioritizes student empowerment through personalized engagement, encouraging innovation and integrity. Courses taught include Predictive Analytics, Decision Analytics, and Business Analytics fundamentals, blending technical skills with strategic thinking. Collaborations: Available for projects in industry partnerships, advisory roles, and interdisciplinary initiatives. Proficient in English and Mandarin. Active on LinkedIn and Facebook for academic networking.

Jay GopalakrishnanView profile

Professor

• Scientific computation
• Numerical analysis
• Finite elements
• +3 more

Jay Gopalakrishnan is a Professor of Mathematics and the Maseeh Distinguished Chair at Portland State University's Department of Mathematics. His research focuses on scientific computation, numerical analysis, finite elements, and multigrid methods with applications in optics and mechanics. He has contributed significantly to the development of hybridizable discontinuous Galerkin (HDG) methods and the Discontinuous Petrov-Galerkin (DPG) framework, emphasizing structure-preserving numerical techniques. His work spans diverse domains including microstructured optical fibers, spacetime tents for hyperbolic systems, and eigenvalue cluster computations. Notable research activities include developing accurate computational tools for leaky modes in fibers, stability analysis of acoustic waveguides, and bone mineralization models. He advises doctoral students at institutions such as Intel Corporation, The MathWorks, and James Madison University. His teaching includes advanced numerical analysis courses and undergraduate mathematical computing. Collaborations with researchers like L. Demkowicz and J. Schöberl highlight his interdisciplinary impact in computational mathematics and engineering.

Shaul MukamelView profile

Professor

• Ultrafast Spectroscopy
• Nonlinear Optical Spectroscopy
• Biophysical Chemistry
• +7 more

Shaul Mukamel is the Chancellor Professor of Chemistry at the University of California, Irvine (UCI), with affiliations at the Freiburg Institute for Advanced Studies (FRIAS) in Germany. He holds a Ph.D. from Tel Aviv University (1976) and has held faculty positions at Rice University, the Weizmann Institute, and the University of Rochester. His research focuses on developing computational techniques for ultrafast laser spectroscopy, probing electronic and vibrational dynamics in molecules, and applying these to biophysical systems like protein folding, photosynthetic complexes, and semiconductor nanostructures. He is a recipient of prestigious awards including the Sloan, Dreyfus, Guggenheim, and Alexander von Humboldt Fellowships, and is a Fellow of the American Physical Society and Optical Society of America. Research Interests: His work spans nonlinear optical spectroscopy, attosecond X-ray techniques, quantum coherence in photosynthetic systems, and entangled photon-based spectroscopy. He has pioneered methods for analyzing multidimensional optical signals and simulating energy transfer pathways in biological complexes. Grants & Funding: Supported by NIH, NSF, DOE, and Petroleum Research Fund grants for studies on molecular relaxation, nonlinear optical phenomena, and single-molecule spectroscopy. Awards: OSA Lippincott Award (2015), APS Plyler Prize (2008), and numerous fellowships. His textbook Principles of Nonlinear Optical Spectroscopy (Oxford, 1995) is a seminal reference in the field.

Kenneth KigerView profile

Professor

• Fluid Mechanics
• Multiphase Flows
• Turbulent Mixing
• +4 more

Kenneth Kiger is a Professor and Associate Dean of Undergraduate Programs in the Department of Mechanical Engineering at the University of Maryland, College Park. He holds the endowed Keystone Professor title and is affiliated with the Maryland Energy Innovation Institute and Brain and Behavior Institute. His research focuses on fluid mechanics and experimental techniques, with emphasis on multi-phase flows, particle-turbulence interaction, turbulent mixing in complex geometries, and applications in nuclear reactor safety, spray cooling, and sediment transport. Dr. Kiger earned his Ph.D. in Mechanical Engineering from the University of California, San Diego (1995). He has received the National Science Foundation CAREER Award (1997) and the Distinguished Scholar-Teacher award from the University of Maryland. His work has advanced fluid dynamics education and curriculum development, particularly in hands-on engineering pedagogy. His research employs advanced experimental methods like Particle Image Velocimetry (PIV) and Laser Induced Fluorescence (LIF). Notable projects include studying air entrainment by plunging jets, boron mixing in nuclear reactors, and the dynamics of sediment-laden flows. He has contributed to biomimetic fluid dynamics, exploring gill kinematics in mayfly nymphs, and developed novel measurement techniques for two-phase flows. Prof. Kiger actively engages in academic service, serving on the organizing committee for the APS Division of Fluid Dynamics Annual Meeting (2000) and as a reviewer for journals including Physics of Fluids and Journal of Fluid Mechanics. He has mentored numerous students and pioneered educational initiatives such as mastery-based assessment approaches in engineering education. His lab work involves fluid-structure interaction studies, particularly flexible plate impacts on water surfaces, and high-fidelity simulations of complex fluid dynamics phenomena. Recent contributions address environmental fluid mechanics (e.g., foundry physics modeling) and energy-related applications (e.g., spray cooling for electronics).

Nancy Jane KopellView profile

Professor

• Mathematical Biology
• Dynamical Systems
• Neuroscience
• +3 more

Nancy Jane Kopell is a distinguished Professor of Mathematics at Boston University, holding the William Fairfield Warren Distinguished Professor title since 2009, the first woman to achieve this honor at BU. She earned her B.S. from Cornell University and her Ph.D. in Mathematics from the University of California, Berkeley. Before joining BU in 1986, she held positions at MIT and Northeastern University, where she became a full professor in 1978. Her research focuses on mathematical modeling of neural networks, particularly oscillatory systems in vertebrate and invertebrate nervous systems. She co-directs the Center for BioDynamics (CBD), a multidisciplinary initiative training students in dynamical systems theory applied to biology and engineering. Her work bridges mathematics and neuroscience, analyzing how network properties emerge from cellular interactions. Key achievements include the MacArthur Fellowship (1990), election to the National Academy of Sciences (1996), and the William Goodwin Aurelio Professorship (2000). Her publications span over 80 papers, emphasizing dynamical systems, nonlinear oscillations, and applications in neuroscience.

• Biomedical Signal Processing
• Sleep Apnea
• Respiratory Analysis
• +4 more

Jordi Solà Soler is a Researcher at the Institute for Bioengineering of Catalonia (IBEC) , specializing in Biomedical Signal Processing and Interpretation . His work focuses on cardiorespiratory dynamics and sleep-related breathing disorders, particularly obstructive sleep apnea syndrome (OSAS). Research Areas : Biomedical signal processing, sleep apnea, respiratory analysis, ECG-derived respiration, cardiorespiratory synchronization, breath sound analysis Recent publications highlight his expertise in: Cardiorespiratory phase synchronization analysis ECG-derived respiration estimation methods Snore pattern classification for apnea screening Upper airway assessment through acoustic monitoring Geriatric breathing pattern variability studies Neurovascular hemodynamic responses in apnea patients Key methodologies include advanced signal processing algorithms, linear mixed-effects modeling, and multimodal sensor integration. Collaborations span sleep medicine, biomedical engineering, and clinical physiology domains. His work contributes to non-invasive diagnostic tools and understanding cardiorespiratory interactions during sleep-wake cycles.

• Nanophysics
• Quantum Thermodynamics
• Language Variation and Change
• +8 more

David Sánchez Martín is a Full Professor at the Universitat de les Illes Balears (UIB) , affiliated with the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) and the Physics Department . He has been a faculty member since 2009 and was promoted to Full Professor in 2021. His research spans interdisciplinary domains, connecting nanophysics, quantum thermodynamics, and quantitative linguistics. PhD in Physics (Universidad Autónoma de Madrid, 2002) MA in Hispanic Philology (UNED, 2014) His research focuses on nanophysics (quantum dots, spintronics, Kondo effect), quantum thermodynamics (thermoelectrics, mesoscopic systems), and quantitative linguistics (language variation, digital humanities). Publications include work on quantum transport, cultural analytics, and computational social sciences. Recent publications show a dual focus on physics (quantum dots, thermoelectric devices) and linguistics (language variation, sociolinguistic modeling). Key trends include entropy analysis, computational methods in language studies, and nonlinear transport phenomena. Ramon y Cajal Fellow (2005-2008) He teaches courses such as Quantum Mechanics , Computational Social Sciences , and Information Theory at both undergraduate and master's levels. He is a member of the Consolidated R+D+I Groups Complex Systems and Socio-technical Applications (CSSA) and Physics of Nanosystems (FISNANO) .