جستجوی استاد راهنمای دانشگاهی

Anna S. Mattila is the Marriott Professor of Lodging Management and serves as Professor-in-Charge of the Graduate Program at the School of Hospitality Management, Pennsylvania State University. Her research spans social media, service recovery, servicescape, prosocial behaviors, cross-cultural studies, and wellness in hospitality contexts. Education : B.S. and Ph.D. from Cornell University, M.B.A. from University of Hartford Mattila's work examines how emotions, cultural norms, and technological innovations like AI influence consumer decisions in hospitality. Her studies cover topics from robotic service interactions to sustainable food marketing and moral psychology in tourism. She has published extensively in journals such as International Journal of Hospitality Management and Journal of Consumer Marketing . Her recent articles focus on AI integration in hospitality, consumer trust in virtual influencers, upcycled food adoption, and the psychological effects of servicescape design. Key themes include ethical consumption, digital transformation, and cross-cultural consumer behavior. Advising : Supervised Anqi Luo's dissertation on service recovery in 2022 Mattila's office is located in 224 Mateer Building, University Park, PA. She contributes to advancing hospitality research through methodological consulting and the Penn State Biomarker Core Laboratory.

• Social Media
• Service Recovery
• Servicescape
• +۸ مورد دیگر

Sandro Carrara is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Bio/CMOS Interfaces (BCI) laboratory. He is affiliated with the School of Engineering (STI), the Institute of Electrical Engineering (SCI-STI-SC), and the Integrated Systems Laboratory (LSI). His academic leadership spans teaching, doctoral supervision, and editorial roles in major journals including IEEE Sensors Journal and BioNanoScience. Education: Diploma in Electronics, National Technical Institute of Albenga, Italy Master in Physics, University of Genoa, Italy PhD in Biochemistry and Biophysics, University of Padua, Italy His research focuses on the integration of biological systems with CMOS technology, particularly in the development of nanoscale biosensors for health monitoring. Key areas include memristive biosensors, wearable and implantable sensors, electrochemical detection, and therapeutic drug monitoring. His work bridges electronics, nanotechnology, and biomedicine to enable point-of-care diagnostics and personalized medicine. His recent publications (2023–2025) show a strong trend toward sustainable printed electronics, machine learning for biosensing, in-memory computing for cancer diagnostics, and remote health monitoring. These works appear in high-impact journals such as IEEE Sensors Journal , Nanoscale , and Biosensors and Bioelectronics: X . Scientific Awards: IEEE Fellow (2015) IEEE Sensors Council Technical Achievement Award (2016) Distinguished Lecturer, IEEE Sensors Council (2017) Best Paper Award, IEEE MeMeA Symposium (2020) Multiple Gold and Bronze Leaf Prizes at PRIME and IEEE conferences Best Poster Awards at EMBEC and Nano-Tera meetings He actively advises PhD students and leads research projects involving CMOS-based biosensors, wireless implants, and smart sensor systems. His lab collaborates widely across disciplines and institutions, focusing on real-world applications in oncology, neurology, and environmental health. He has also contributed to the development of battery-free wearable devices, optical power transfer systems, and IoT-enabled telemedicine platforms. Laboratories and Teams: Bio/CMOS Interfaces (BCI) Laboratory, EPFL Integrated Systems Laboratory (LSI), EPFL Collaborations with IEEE Sensors Council and Circuits and Systems Society Editorial leadership in IEEE Sensors Journal and BioNanoScience

• Bioelectronics
• Nanotechnology
• CMOS Technology
• +۱۲ مورد دیگر

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

• Protein Biophysics
• In-Cell NMR Spectroscopy
• Macromolecular Crowding
• +۳ مورد دیگر

Dr. Scarlett Raine is a Lecturer in the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT), where she serves as a Chief Investigator at the QUT Centre for Robotics and an Associate Investigator at the QUT Centre for Data Science and QUT Centre for Environment and Society. Her work focuses on applying Artificial Intelligence to automate underwater image analysis for marine ecosystem monitoring.

• Artificial Intelligence
• Computer Vision
• Robotics
• +۷ مورد دیگر

Baharan Mirzasoleiman is an Assistant Professor in the Department of Computer Science at the University of California, Los Angeles (UCLA), where she leads the BigML research group. Prior to joining UCLA, she was a postdoctoral research fellow in Computer Science at Stanford University working with Jure Leskovec. She received her Ph.D. in Computer Science from ETH Zurich advised by Andreas Krause. Her research focuses on addressing sustainability, reliability, and efficiency of machine learning, with particular emphasis on improving big data quality by developing theoretically rigorous methods to select the most beneficial data for efficient and robust learning. Her work spans several critical areas including data efficiency, robustness against label noise and data poisoning, and addressing spurious correlations in machine learning models. She has made significant contributions to understanding how neural networks exploit spurious features that correlate with certain categories during training but fail to generalize to minority groups. Professor Mirzasoleiman's research demonstrates how theoretically grounded approaches can lead to practical improvements in model robustness and efficiency across various applications including medical diagnosis and environmental sensing. Her work has resulted in the development of the SpuCo package, a Python library that provides modular implementations of state-of-the-art methods to address spurious correlations, along with controllable synthetic datasets like SpuCoMNIST and large-scale vision datasets like SpuCoAnimals. She has received numerous prestigious awards including the ETH medal for Outstanding Doctoral Thesis, being selected as a Rising Star in EECS by MIT, an NSF Career Award, a UCLA Hellman Fellows Award, and an Okawa Research Award. Her students have also received multiple fellowships and awards including Amazon Doctoral Student Fellowships and an OpenAI Superalignment Fast Grant. Professor Mirzasoleiman actively contributes to the academic community through invited talks at major conferences including ICML, ICLR, NeurIPS, and KDD, as well as co-organizing workshops on new frontiers in adversarial machine learning and sparsity in neural networks. She has developed educational resources including tutorials on Foundations of Data-efficient Learning presented at ICML 2024.

• Machine Learning
• Data Efficiency
• Robustness
• +۴ مورد دیگر

Peter Seele is a Full Professor at the Faculty of Communication, Culture and Society at Università della Svizzera italiana (USI). He is affiliated with the Center for Climate Finance and Sustainability (CCFS), Ethics and Communication Law Center (ECLC), and the Luxury Observatory Lugano (LOLugano). His research focuses on Corporate Social Responsibility (CSR), Business Ethics, Digital Ethics, Greenwashing, and Machinewashing. Dr. Seele holds dual PhDs in Economics (University of Witten/Herdecke, Germany) and Philosophy (University of Düsseldorf, Germany). He previously served as an Assistant Professor at the University of Basel and conducted post-doctoral research at the Institute for Advanced Studies in the Humanities (KWI) in Essen. His educational background includes studies at the University of Oldenburg and Delhi School of Economics, followed by two years as a business consultant in Frankfurt. His research explores ethical challenges in digitalization, sustainability, and technology. Notable themes include AI ethics governance, ethicswashing in corporate communication, and the interplay between blockchain and business ethics. Recent work addresses greenwashing trends, the ethical implications of algorithmic systems, and sustainable practices in luxury industries. Publications highlight critical analyses of digital ethics frameworks, sustainability backlashes, and the societal impact of emerging technologies. His interdisciplinary approach bridges philosophy, business studies, and environmental science, with a focus on practical solutions for ethical dilemmas in modern organizations. Peter Seele collaborates across academic and industrial sectors, emphasizing real-world applications of ethical theories. He advises on CSR strategies, digital transparency, and regulatory frameworks for sustainable business practices.

• Corporate Social Responsibility
• Business Ethics
• Digital Ethics
• +۶ مورد دیگر

Sanjay Purushotham is an Assistant Professor in the Department of Information Systems at the University of Maryland Baltimore County (UMBC), with a PhD in Electrical Engineering from the University of Southern California (USC) and a postdoctoral background in Computer Science at USC's Integrated Media Systems Center (IMSC). His research focuses on machine learning, data mining, and their applications in biomedical informatics, social network analysis, and multimedia data mining. Key contributions include survival analysis models using pseudo values and federated learning frameworks for healthcare data. He has received awards including the Best Paper Award at SIGSPATIAL 2014 and a Best Poster Runnerup at SCMLS 2016. Education: PhD in Electrical Engineering (USC), Postdoc in Computer Science (USC) His work spans interdisciplinary areas such as domain adaptation for remote sensing, thermal face translation, and interpretable neural networks for medical applications. Recent projects include federated survival analysis models and climate-informatics frameworks for cloud property retrieval. He teaches courses in artificial intelligence, healthcare informatics, and statistical learning at UMBC. Research highlights include developing MedFuseNet for multimodal medical question answering and VDAM for multi-sensor cloud data analysis. His work on fair survival analysis models addresses algorithmic bias in healthcare predictions. Current grants include a NSF CAREER award for trustworthy federated learning in computational healthcare.

• Machine Learning
• Data Mining
• Optimization Theory
• +۵ مورد دیگر

Anocha Aribarg is a Professor of Marketing and Area Chair of Marketing at the Ross School of Business, University of Michigan, with additional faculty affiliation at the Center for Southeast Asian Studies (CSEAS). Her interdisciplinary research bridges psychological theory, consumer behavior, and advanced statistical modeling to address complex marketing challenges. Education: PhD in Marketing, University of Wisconsin, 2004 MBA, University of Wisconsin-Milwaukee, 1998 BS in Statistics, Chulalongkorn University, Thailand, 1994 Research Focus: Prof. Aribarg investigates cognitive processes in consumer decision-making, specializing in individual/joint choice dynamics, product search behaviors, and responses to marketing stimuli. Her methodology integrates Bayesian econometrics with physiological measures (eye tracking, skin conductance) and multi-method experimental designs to uncover hidden decision mechanisms. Publication Trends: Her 14 recent publications (2009-2024) reveal consistent innovation in choice modeling, with increasing emphasis on attention dynamics (2020), moral psychology in aesthetics (2022), and high-frequency service data integration (2023). Work appears predominantly in Marketing Science Journal of Marketing Research, and Psychological Science, demonstrating methodological rigor across consumer behavior, advertising, and service contexts. Academic Service: She serves as Associate Editor for Marketing Science, Journal of Marketing, and Journal of Marketing Research, while contributing to the Journal of Retailing editorial board. Teaching: Prof. Aribarg delivers graduate-level courses in Marketing Research and Analytics and Predictive Analytics at Ross, emphasizing data-driven decision frameworks.

• Consumer Behavior
• Marketing Research
• Econometric Modeling
• +۳ مورد دیگر

Jason M. LaBelle is a Professor of Anthropology at Colorado State University (CSU), affiliated with the College of Liberal Arts. He serves as Director of the Center for Mountain and Plains Archaeology (CMPA) and Curator of the Archaeological Repository of CSU (AR-CSU). His research focuses on hunter-gatherer societies, particularly in the Intermountain West, emphasizing subsistence, mobility, and pre/post-contact Native American cultures. His work spans environments from the Great Plains to high alpine regions, with specialties in Clovis/Folsom cultures, communal hunting practices, and lithic technology. LaBelle teaches courses in archaeology, lithic technology, and public archaeology. He oversees CMPA projects funded by federal agencies like the National Park Service and the Bureau of Land Management, supporting student training in fieldwork, lab analysis (lithics, faunal studies), and report writing. His lab houses extensive collections from Colorado’s South Platte and Colorado River Basins, including alpine artifacts. He actively engages with tribal partners and the public through outreach, conferences, and NAGPRA coordination. LaBelle’s recent research includes studies on lithic quarries, ice patch archaeology, and Bayesian chronology modeling. His publications address prehistoric mobility, site chronology, and cultural resource management. He values interdisciplinary collaboration and student mentorship, aiming to bridge academic and applied archaeology.

• Environmental and Landscape Archaeology
• Peopling of the Americas
• Contact Era Studies
• +۴ مورد دیگر

Ann B. Lee is a Professor and Co-Director of the PhD Program in Statistics at Carnegie Mellon University , with a joint appointment in the Department of Statistics & Data Science and the Machine Learning Department. Prior to joining CMU, she held positions as a J.W. Gibbs Assistant Professor at Yale University and a visiting research associate at Brown University. PhD in Physics, Brown University MSc/BSc in Engineering Physics, Chalmers University of Technology, Sweden Her research focuses on statistical methodology for complex data in the physical sciences , emphasizing trustworthy inference, uncertainty quantification, and integration of classical statistics with machine learning. Recent work includes likelihood-free inference, calibrated forecasting, and diagnostics for generative models. The STAMPS research group , which she co-founded in 2018, hosts weekly meetings and public webinars. In Fall 2024, STAMPS will transition into a CMU Research Center. Recent publications span likelihood-free inference , climate modeling , and astronomy . Notable collaborations include applications to hurricane intensity guidance , galaxy redshift estimation , and cosmological parameter biases . She mentors PhD students and has advised multiple award-winning researchers, including ASA Best Student Paper Award winners. Her teaching includes advanced courses on probability, regression, and AI for climate sciences.

• Scientific Machine Learning
• Trust-Worthy UQ
• Likelihood-Free Inference
• +۱ مورد دیگر

Farnoush Banaei-Kashani is an Associate Professor (Tenured) in the Department of Computer Science and Engineering at the University of Colorado Denver. She also holds an Adjunct Associate Professor position in the Department of Mathematical and Statistical Sciences. As the founder and director of the Big Data Management and Mining Lab (BDLab), she leads multiple GAANN Fellowship Programs, including BDSE (Big Data Science and Engineering), DDC (Data-Driven Cybersecurity), and II (Infrastructure Informatics). She directs the 'Data Science in Biomedicine' MS Track and focuses on data-driven decision systems (DDSs), integrating machine learning and big data analytics into healthcare, energy, transportation, and environmental applications. Education: Details not explicitly provided in the text. Her research spans data management cycles for DDSs, addressing challenges like big data volume, velocity, and variety. Key projects include iWatch (crime surveillance), POCM (mobility monitoring), and GeoSIM (urban texture documentation). She teaches courses such as Machine Learning Systems, Big Data Science, and Data Mining. Publications highlight advancements in sea ice classification, federated learning, proteomic networks, and privacy-preserving AI. Her work is funded by NSF, NIH, DOT, and industry partners like Google and IBM. She has advised numerous students and contributes to academic leadership as editor, conference chair (ACM SIGSPATIAL 2018/2019), and program committee member for venues like SIGMOD and KDD.

• Data Management
• Big Data
• Decision Support Systems
• +۴ مورد دیگر

Prof. Vasilis Ntziachristos is a Professor and Chair of Biological Imaging at the Technical University of Munich (TUM), leading the Institute of Biological and Medical Imaging at the Helmholtz Centre Munich. His research focuses on developing novel optical and optoacoustic imaging techniques for early disease detection, diagnostics, and theranostics. He holds a PhD in Bioengineering from the University of Pennsylvania and previously served as an Assistant Professor at Harvard University and Massachusetts General Hospital. Affiliations: TUM School of Medicine and Health, Helmholtz Munich, Institute of Biological and Medical Imaging. Key Research Themes: Non-invasive imaging methods, molecular imaging, optoacoustic technology, and clinical translation. His work bridges theoretical developments with clinical applications, including advancements in glucose monitoring, cancer imaging, and drug delivery systems. Notable awards include the Leibniz Prize (2013) and the World Molecular Imaging Society Gold Medal (2015). Labs/Teams: Imaging to Sensing I2S, Optoacoustic Mesoscopy, Fluorescence Imaging, and AI in Optoacoustics. Grants/Projects: Involvement in Horizon Europe initiatives and collaborations with TranslaTUM and Helmholtz Munich. Prof. Ntziachristos actively contributes to education via courses like 'Biological Imaging' and 'Introduction to Bioengineering', fostering the next generation of imaging scientists.

• Biomedical Imaging
• Optoacoustic Imaging
• Medical Diagnostics
• +۳ مورد دیگر

Yuvraj Agarwal is a Professor in the School of Computer Science at Carnegie Mellon University , where he leads the SYNERGY Labs . His research focuses on Systems and Networking with emphasis on Embedded Systems , Security , and Energy Efficiency in computing environments. He has been recognized with the NSF Expeditions in Computing Award for Computational Decarbonization research and multiple best paper awards. Education : PhD in Computer Science from University of California, San Diego Research Leadership : Founder/Director of SYNERGY Labs; Executive Director of NSF Expeditions in Variability (2010-2013) Research Trajectory : Recent publications highlight his work on Privacy-preserving smart classroom systems (EduSense, ClassID) IoT security labeling frameworks Audio privacy protection mechanisms Computational decarbonization of infrastructure His research combines hardware-software co-design with societal impact considerations. Scientific Recognition : NSF Expeditions in Computing Award for CoDec (2024) Ubicomp/IMWUT Distinguished Paper Award (2024) CHI Best Paper Honorable Mention (2022) Advising & Collaboration : Mentors students in IoT systems , privacy research , and green computing . Collaborates with institutions including University of Massachusetts Amherst and industry partners like Johnson Controls. Grants include NSF funding for multi-university research initiatives.

• Systems
• Embedded Systems
• Security
• +۷ مورد دیگر

Jürgen König is a full professor at the Department of Nutritional Sciences , University of Vienna, leading the Research Professorship Specialized Human Nutrition . His work bridges psychological and physiological dimensions of eating behavior, with additional focus on population-level nutritional assessment in Austria. Academic Rank: Professor Department: Nutritional Sciences Research Focus: Hunger/satiety mechanisms, Public health nutrition, Food safety Key research themes include: Psychological drivers of eating behaviors (stress, food craving, sensory cues) Physiological regulation of nutrient homeostasis National nutrition surveys assessing dietary patterns Caloric restriction and metabolic adaptation Child and adolescent hydration/nutrition policies Recent publications highlight: Mechanistic studies on caloric restriction effects (2025) Pandemic impacts on school nutrition (2024) Global obesity/diabetes trends analysis (2024) Behavioral nudging in food selection (2024) Microbiota's role in dietary interventions (2023) Contact: juergen.koenig@univie.ac.at | Sekretariat: sekretariat.ew@univie.ac.at

• Nutritional Sciences
• Eating Behavior
• Public Health Nutrition
• +۴ مورد دیگر

Romain Franck is an Associate Professor in Marketing at IÉSEG School of Management, with a focus on advanced research in marketing strategies and digital tools. He previously served as an Associate Professor of Sales and Marketing at EM Strasbourg Business School (2022–2024) and earned his Advanced Research in Marketing degree from IAE of Grenoble in 2017. His research explores the intersection of technology, sales performance, and consumer behavior. Education: 2017 – Advanced Research in Marketing (IAE of Grenoble) His work examines how digital technologies (e.g., sales force automation, social media) influence sales effectiveness and the adoption of eco-innovations like laser-marked organic products. Recent publications highlight barriers and motivations in sustainable consumer behavior, alongside the role of interpersonal dynamics in tech-mediated sales environments. Email: r.franck@ieseg.fr

• Marketing
• Sales Management
• Digital Marketing
• +۳ مورد دیگر