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Arjun MukherjeeView profile

Lecturer

• Bayesian Inference
• Data Mining
• Natural Language Processing
• +3 more

Arjun Mukherjee is a Lecturer at the Department of Computer Science , University of Houston , where he teaches courses in Machine Learning , Data Mining , Natural Language Processing , and Data Structures . His research focuses on Bayesian Inference , Data Mining , Natural Language Processing , Sentiment Analysis , Opinion Spam , and Web Mining , with a strong emphasis on deception detection and social media analysis. His recent publications explore advanced techniques in LLM-generated content detection synthetic data applications cross-domain deception modeling temporal user behavior analysis , reflecting his commitment to addressing modern challenges in digital content authenticity and machine learning robustness. Dr. Mukherjee has developed educational materials for graduate-level courses, including a well-structured Machine Learning course (COSC 6342) covering probabilistic inference, supervised/unsupervised learning, and neural networks. He earned his Ph.D. from the University of Illinois at Chicago in 2014, with a thesis titled Probabilistic Models for Fine-Grained Opinion Mining: Algorithms and Applications .

Xiaoli FernView profile

Associate Professor

• Machine Learning
• Data Mining
• Graph Learning
• +5 more

Xiaoli Fern is an Associate Professor in the School of Electrical Engineering and Computer Science at Oregon State University. She holds a Ph.D. in Computer Engineering from Purdue University (2005) and dual degrees (B.S. and M.S.) in Automation and Computer Science from Shanghai Jiao Tong University (2000). Her research focuses on applied machine learning , graph learning , and explainability in AI systems , with applications in microbiome analysis , ecological monitoring , and human-computer interaction . Research Expertise: Unsupervised learning, clustering, correlation analysis, outlier detection, and scientific data mining. Collaborations: Active involvement in the IGERT Ecosystem Informatics program and interdisciplinary projects with ecologists, roboticists, and biologists. Awards: 2011 NSF CAREER Award for early-career excellence in research. Her recent work includes applying deep learning to microbiome data and developing interactive systems that bridge theory with real-world applications in biology and materials science. She mentors students across all academic levels and emphasizes the importance of collaborative, real-world problem-solving in her research lab.

Michael FergusonView profile

Professor

• Biochemistry
• Glycobiology
• Mass Spectrometry
• +7 more

Professor Sir Michael Ferguson is the Regius Professor of Life Sciences at the University of Dundee and an Interim Dean of the School of Life Sciences. He is a Fellow of the Royal Society (FRS), Royal Society of Edinburgh (FRSE), Academy of Medical Sciences (FMedSci), and Royal Society of Biology (FRSB). Education : BSc in Biochemistry, University of Manchester (1976-1979) PhD in Biochemistry, University of London (1979-1982) His research focuses on the biochemistry of protozoan parasites causing tropical diseases such as human African Sleeping Sickness, Chagas' disease, and leishmaniasis. He emphasizes the Biology/Chemistry interface and translational research, co-founding the Drug Discovery Unit and directing the Dundee Proteomics Facility . His work on glycosylphosphatidylinositol (GPI) membrane anchors has transformed understanding of eukaryotic biology. Recent publications highlight advancements in antimicrobial resistance , serology standards for SARS-CoV-2 , and mechanochemical drug formulation . He contributes to UN Sustainable Development Goals in Health and Life Sciences . Scientific Awards : Royal Society Leeuwenhoek Medal (2025) Biochemical Society Morton Lecture (2024) Knight Bachelor (2019) Colworth Medal (1991) Howard Hughes International Scholar (1993) He serves on the boards of UK Biobank , Medicines Discovery Catapult , and chairs PhaSER Bio . During the pandemic, he advised the UK government on antibody testing and national core studies.

Cheng Zhi HuangView profile

Assistant Professor

• Artificial Intelligence
• Music Technology
• Computer Science
• +4 more

Cheng Zhi Huang is the Robert N. Noyce Career Development Professor and Assistant Professor at MIT, holding a shared appointment between the departments of Music and Theater Arts and Electrical Engineering and Computer Science (EECS). His work bridges artificial intelligence, music technology, and computer science to advance human-AI collaboration in musical creativity. Huang leads research in generative models for music composition, real-time interactive systems, and expressive performance synthesis. His contributions include tools like ReaLJam for AI-assisted jamming and the MAESTRO dataset for piano performance modeling. His research interests span AI-driven music generation, human-AI interaction frameworks, and culturally-aware music technologies. Notable projects include The Bach Doodle—an accessible web-based composition tool—and MIDI-DDSP for detailed performance control. Huang’s work emphasizes ethical and creative applications of AI in arts, fostering collaborations between musicians, engineers, and computer scientists. His publications highlight advancements in hierarchical generative modeling, source separation techniques, and co-creation interfaces for novices. Huang’s research has been showcased in venues like TISMIR and IEEE conferences, reflecting his interdisciplinary impact on music technology and machine learning.

Johanna RimmeleView profile

Researcher

• Auditory perception/cognition
• Temporal processing
• Neural basis of speech perception
• +5 more

Dr. Johanna Rimmele is a Researcher at the Max Planck Institute for Empirical Aesthetics in Frankfurt, Germany. She holds a PhD in Psychology from the University of Leipzig (2012) and has conducted postdoctoral research at institutions including the Albert Einstein College of Medicine, New York University, and the University Medical Center Hamburg-Eppendorf. Her work focuses on auditory perception, temporal processing, and the neural basis of speech perception. She has received several awards, including the 8th Dissertation Competition in Psychology and the Sign UP! Careerbuilding grant. Her research explores how temporal structure in speech influences neural processing, particularly through the lens of cortical oscillations. She investigates neuroplasticity in sensory deprivation (e.g., blindness) and the interplay between auditory perception and motor systems. Rimmele has authored over 20 peer-reviewed articles and co-edited a book on brain oscillations in human communication. She is affiliated with the CLaME research group and actively contributes to interdisciplinary studies on music, language, and neural mechanisms. Education: PhD in Psychology, University of Leipzig (2008–2012) Visiting Researcher, Albert Einstein College of Medicine (2006–2011) Diploma in Psychology (minor Philosophy), University of Leipzig (2002–2008) Awards & Grants: 8th Dissertation Competition, German Society for Psychology (2013) Sign UP! Careerbuilding MPG Grant (2016/2017) ERASMUS MUNDUS Stipendium (2011–2012) Key Research Themes: Rimmele’s projects address speech-specific neural processing, the role of delta/theta oscillations in speech segmentation, and how rhythmic speech production influences perception. Her work on neuroplasticity in blind individuals highlights cross-modal reorganization of brain networks.

• Neuroscience
• Cell Signaling
• Neurodegenerative Diseases
• +5 more

Jose Ramon Bayascas Ramirez is an Associate Professor in the Department of Biochemistry and Molecular Biology at the Universitat Autònoma de Barcelona's Institute of Neuroscience. With a Ph.D. in Biological Sciences from the University of Barcelona (1998), he completed postdoctoral training at the University of Lleida (1998-2002) and University of Dundee, Scotland (2002-2007) before joining UAB in 2007 as a Ramon y Cajal Fellow, becoming a Serra Húnter Associate Professor in 2014. His research focuses on the neurodevelopmental functions of the $$\text{PDK1}$$ signaling network and its implications for neurodegenerative and mental illnesses. His laboratory specializes in the $$\text{PI3K}$$/$$\text{Akt}$$ signaling pathway, utilizing brain-specific conditional knock-in mice with engineered $$\text{PDK1}$$ mutations (K465E and L155E) to study how these affect neuronal development and disease processes. The K465E mutation selectively impairs $$\text{Akt}$$ activation, while the L155E mutation abolishes activation of most $$\text{PDK1}$$ effectors except $$\text{Akt}$$. His work has revealed that reduced $$\text{Akt}$$ activation in $$\text{PDK1}$$ K465E mice protects against neurodegenerative insults, while the exclusive $$\text{Akt}$$ activation in $$\text{PDK1}$$ L155E mice causes severe mental disorders resembling human schizophrenia. His recent publications span molecular insights into $$\text{PDK1}$$ structure, behavioral studies in Alzheimer's models, and investigations into lysine crotonylation and metabolic homeostasis. His research has been recognized with a Ramon y Cajal Fellowship, and he has led multiple research projects including: "Assaig de l'inhibidor d'$$\text{Akt}$$ MK-2206 pel tractament de la Malaltia d'Alzheimer" (2022-2023) "Implicació de la ruta de senyalització $$\text{PI3K}$$/$$\text{PDK1}$$/$$\text{Akt}$$ en la Malaltia d'Alzheimer" (2019-2022) "Participació de $$\text{PDK1}$$ en les respostes a $$\text{PI3K}$$ durant el desenvolupament neuronal" (2015-2018) His group has published 53 research outputs with significant citations, demonstrating impactful contributions to understanding the molecular mechanisms underlying brain pathology and potential therapeutic targets for neurodegenerative and mental disorders.

James F CarmodyView profile

Professor

• Mindfulness
• Meditation
• Psychological mechanisms
• +5 more

James F Carmody, PhD is a Professor at UMass Chan Medical School with dual appointments in the Department of Medicine and Department of Population and Quantitative Health Sciences, Division of Preventive and Behavioral Medicine. He is a leading researcher in mindfulness-based interventions and their psychological and neural mechanisms, with over forty-five years of meditation practice across Zen, Tibetan, Theravada and Advaita traditions. Education: Ph.D. from University of Iowa, 1971 Dr. Carmody's research focuses on the psychological and neural mechanisms of mindfulness and mind-body processes, examining how these can modify distress and enhance well-being. His work spans evolutionary psychology, stress reduction, meditation practices, and their clinical applications for conditions including chronic pain, PTSD, asthma, and hot flashes. He has made significant contributions to understanding how mindfulness training affects brain structure and function, particularly in relation to emotional regulation and stress response. Analysis of Dr. Carmody's recent publications reveals a consistent focus on mindfulness-based stress reduction (MBSR) across multiple clinical contexts. His work demonstrates expertise in comparative effectiveness research, examining mindfulness against other therapeutic approaches for chronic pain conditions. There's a strong emphasis on identifying specific mechanisms of action and understanding how mindfulness interventions produce clinical benefits across diverse populations from veterans with PTSD to patients with chronic medical conditions. Research Leadership: Principal Investigator on multiple NIH-funded clinical trials Former Director of Research for the Center for Mindfulness Lead investigator on studies examining mindfulness for chronic pain, PTSD, asthma, hot flashes, and smoking cessation Dr. Carmody teaches mindfulness courses for clinicians, focusing on making the conceptualization and psychological mechanisms of mindfulness straightforward, jargon-free, and practically accessible for patient care. His research has been widely featured in national and international media including the New York Times (reaching #1 on the most emailed list), NPR, ABC, and numerous other outlets.

Lindsey D. CameronView profile

Assistant Professor

• Algorithmic Management
• Gig Economy
• Future of Work
• +5 more

Lindsey D. Cameron is an Assistant Professor of Management at the Wharton School and holds a secondary appointment in Sociology at the University of Pennsylvania’s School of Arts & Sciences. She is a Dorinda and Mark Winkelman Distinguished Faculty Scholar, and a member of the Institute for Advanced Study and the Berkman Klein Center for Internet & Society at Harvard University. Her research focuses on algorithmic management’s impact on workplaces, particularly in the gig economy, and its implications for labor dynamics, worker well-being, and organizational control. Professor Cameron’s academic journey includes a PhD in Management from the University of Michigan, an MS in Engineering Management from George Washington University, and an SB in Electrical Engineering and Computer Science from Harvard University. Her prior career spanned over a decade in U.S. intelligence and diplomatic roles, including overseas assignments in the Middle East, Africa, and Europe. She has conducted a seven-year ethnography of the ride-hailing industry and studies the effects of the pandemic on gig workers across platforms like Uber, Instacart, and Amazon Flex. Research Interests: Her work explores the gig economy’s future, algorithmic governance, worker activism, mindfulness practices in the workplace, and global labor dynamics. She employs ethnographic methods, longitudinal interviews, and field experiments, with research published in journals like Organization Science and Journal of Applied Psychology . Her findings have been featured in media such as Bloomberg , NPR , and the World Economic Forum . Awards & Recognition: She has received Best Paper Awards and teaching accolades, supported by funding from institutions like the Mack Institute for Innovation and the Data & Society Research Institute. Her speaking engagements include Harvard, MIT, and Fortune 500 companies, alongside legislative testimony and expert witness roles in litigation. Teaching & Mentorship: While no specific student names are listed, her work involves advising on platform labor policies and workplace interventions. She advocates for mindfulness and non-dual awareness practices in professional settings, blending technical and humanistic approaches to organizational challenges.

• Macroeconomics
• Monetary Economics
• Fiscal Policy
• +3 more

Evi Pappa is a Full Professor of Macroeconomics at Universidad Carlos III de Madrid. Her research focuses on fiscal policy, monetary economics, and open economy macroeconomics, with a particular emphasis on business cycle analysis and policy impacts in developed economies. She holds affiliations including Research Fellow at the Center for Economic Policy Research (CEPR), member of the Euro Area Business Cycle Dating Committee (EABCDC), and non-executive member of the Portuguese Fiscal Council. Previously, she held positions at LSE (2001-2006), Bocconi University (2004-2005), UAB (2005-2011), and EUI (2011-2018). Her work addresses topics like the macroeconomic effects of fiscal and monetary policies, structural funds, climate transition costs, and policy responses to economic crises. She serves as associate editor for journals including the Economic Journal and the Journal of International Economics. Educational background includes a PhD from Universitat Pompeu Fabra (UPF) in Barcelona (2001). Her research has explored fiscal multipliers, greenflation dynamics, and the interplay between sentiment and economic behavior. She has collaborated with central banks such as the European Central Bank, Bank of Spain, and Bank of England. Her recent work analyzes crisis support measures, green transition challenges, and the implications of gender representation on societal outcomes. Awards and recognitions include membership in high-profile economic committees and editorial roles. Her research spans theoretical and empirical frameworks, with a focus on policy relevance and real-world economic challenges. She contributes to policy design through academic publications and advisory roles, addressing issues from pandemic response to long-term structural economic transformation.

Volker RodehorstView profile

Professor

• Computer Vision
• Image Analysis
• 3D Reconstruction
• +5 more

Univ.-Prof. Dr.-Ing. habil. Volker Rodehorst is a full professor of computer vision at Bauhaus-Universität Weimar, holding positions in both the Faculty of Media and Faculty of Civil Engineering. His research focuses on photogrammetric computer vision, image analysis, 3D reconstruction, and structural health monitoring with applications in civil infrastructure inspection and urban modeling. He leads projects like ev.AI.luate and InfraCloud, leveraging AI and UAS technologies for infrastructure assessment. Education: PhD (2003): Technical University of Berlin, Faculty of Civil Engineering & Applied Geosciences Habilitation (2013): TU Berlin, Faculty of Electrical Engineering & Computer Science Computer Science Diploma (1994): TU Berlin Research Interests: UAS-based structural inspection using multi-view stereo and deep learning Crack detection and segmentation in concrete structures Automated building age estimation for energy modeling Flight path planning optimization for complex structures Integration of computer vision into BIM workflows Publications: Recent work emphasizes robust algorithms for crack detection (Omnicrack30k benchmark), UAS flight path optimization, and semantic segmentation challenges in bridge inspections. Key contributions include MVCrackViT and CISOL datasets advancing structural analysis methodologies. Awards: Best Academic Performance Prize (1994) - TU Berlin ISPRS Presidential Citation (2008) for WG III/2 leadership Grants & Labs: Leads Bauhaus' 3D-RealityCapture-ScanLab and coordinates EU projects like AISTEC-PRO. Active in developing modular solutions like smoodPLAN for infrastructure inspection. Teaching: Offers courses in photogrammetric computer vision, geodesy, and parallel systems. Supervises PhD students in structural health monitoring and computer vision.

Christoph StiefelView profile

Professor

• Jazz
• Piano Performance
• Composition
• +4 more

Christoph Stiefel is a Professor at the Lucerne School of Music (HSLU), specializing in Jazz Piano, Keyboard, and Jazz Ensemble Direction. He leads the Institute of Jazz and Folk Music, focusing on composition using Isorhythms, a medieval technique adapted into modern jazz frameworks. His career spans global performances with artists like Andreas Vollenweider, and he has produced 23 albums, including acclaimed works like Full Tree (2023) and CHUTES AND LADDERS (2021). His research explores the intersection of structured composition and improvisation, blending traditional jazz elements with experimental techniques. Key projects include the Inner Language Trio and Septet formations, emphasizing collaborative creativity. Recent work highlights his shift toward balancing conceptual frameworks with spontaneous musical interaction. No specific grants or awards are noted, but his discography reflects significant industry recognition.

Hamid ZargariaslView profile

Researcher

• Computer Networks
• IoT and Sensor Technology
• RFID Systems
• +3 more

Dr. Hamid Zargariasl is a Researcher in the Computer Engineering Department at BTU Cottbus-Senftenberg. His work focuses on IoT systems, RFID technology, social network analysis, and distributed computing. He leads the UBICO Team and contributes to the Computer Engineering Group, exploring interdisciplinary applications of telecommunications and sensor networks. His research integrates theoretical frameworks with practical implementations, addressing challenges in smart city infrastructure, healthcare systems, and educational technology. Key research areas include optimizing RFID and sensor performance, analyzing social object interactions in IoT networks, and developing protocols for distributed computing. His experimental studies bridge academic performance metrics with mobile social network dynamics, and he has pioneered methodologies for network integration and centrality analysis in evolving systems. Publications span 15 years (2009–2024), emphasizing real-world data analysis and system optimization. Notable work includes enhancing digital thread functionality in aerospace engineering and evaluating smart parking sensor technologies. His contributions inform both technical systems and socio-economic policy recommendations. Dr. Zargariasl collaborates within interdisciplinary teams, contributing to the BTU's research initiatives while maintaining active engagement in the academic community through lectures and student mentorship.

Lynne GreweView profile

Professor

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +3 more

Lynne Grewe serves as a Professor in the Department of Computer Science at California State University, East Bay, where she maintains active research and teaching responsibilities with current office hours and contact information. Her work bridges theoretical computer science with real-world applications across healthcare, education, and emergency response domains. Her research portfolio centers on three interconnected thrusts: Medical Technology : Development of computer vision systems for stroke detection through facial pattern analysis (StrokeChange), infrared-based disease monitoring, and assistive navigation tools for the visually impaired (Seeing Eye Drone) Educational Innovation : Creation of multimodal systems like ULearn that detect student frustration using deep learning, alongside community college partnerships to broaden participation in computing Sensor Fusion Applications : Integration of multi-modal data for disaster response, infrastructure monitoring, and mobile health platforms using advanced machine learning techniques Publication analysis reveals consistent evolution toward real-time, deployable systems—particularly mobile health applications and educational tools—while maintaining foundational work in sensor fusion. Her 2020-2024 output shows increasing emphasis on healthcare applications (40% of recent work) and educational technology (25%), often combining computer vision with mobile platforms. Grewe demonstrates significant commitment to educational equity through the Faculty in Residence program, collaborating with community colleges to prepare underrepresented students for computing careers. Her Google partnership and focus on practical applications indicate strong industry engagement, though specific grant details aren't documented in source materials. Current projects suggest ongoing expansion into in-situ health monitoring and AI-driven educational support systems.

Senay CebiogluView profile

Researcher

• Cross-Cultural Studies
• Developmental Psychology
• Child Development
• +4 more

Senay Cebioglu is a Postdoctoral Researcher in the Department of Human Behavior, Ecology and Culture at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. Her work focuses on cross-cultural developmental psychology, examining how cultural contexts shape child development across diverse societies. She holds a Ph.D. from Simon Fraser University, Canada. Dr. Cebioglu earned her Ph.D. in Developmental Psychology from Simon Fraser University, Canada. Her academic background includes advanced studies in cross-cultural research methodologies, with a focus on developmental processes in sociocultural contexts. Her research interests center on understanding the impact of culture on early socio-cognitive development, particularly in infants and children. She employs mixed methods, including naturalistic and structured observations, experimental tasks, interviews, and questionnaires. Key areas of focus include the development of self-awareness—such as mirror self-recognition—and the relationship between cultural practices and well-being in indigenous communities, such as the Bantu and BaYaka groups in the Republic of Congo. Her work integrates perspectives from psychology, anthropology, and cultural evolutionary theory. Cebioglu’s publications explore cross-cultural comparisons in child development, including studies on child-directed speech, teaching strategies influenced by formal education, and phonetic variations in baby-talk across cultures. Her research consistently emphasizes the importance of cultural context in shaping developmental outcomes, with recent attention to the dynamics of cultural change and its effects on well-being. While no specific grants are detailed, her research is supported through collaborative projects, such as co-leading a multidisciplinary investigation into cultural change and well-being in Congo. No advisees are listed in the provided materials. She is part of the Department of Human Behavior, Ecology and Culture at the Max Planck Institute, which facilitates interdisciplinary research into human development and cultural evolution.

Hanan SametView profile

Professor

• Spatial Data Structures
• Geographic Information Systems (GIS)
• Computer Vision
• +3 more

Hanan Samet is a Distinguished University Professor in the Computer Science Department at the University of Maryland, College Park. He holds affiliations with the Center for Automation Research and the Institute for Advanced Computer Studies (UMIACS). His academic journey includes a PhD from Stanford University (1975) in Computer Science, following degrees in Engineering (UCLA) and Operations Research/Computer Science (Stanford). Affiliations: University of Maryland, College Park (since 1975) Roles: Professor, Founding Editor-in-Chief of ACM Transactions on Spatial Algorithms and Systems, Founder of ACM SIGSPATIAL Samet's research focuses on spatial data structures, spatial databases, GIS, computer vision, and information retrieval. His seminal work includes the Foundations of Multidimensional and Metric Data Structures , an award-winning book addressing spatial indexing and query optimization. He pioneered frameworks like NewsStand for map-based news exploration and Coronaviz for pandemic visualization. Key contributions span spatial synonyms for approximate search, SAND spatial browser for digital government, and trajectory analysis systems for aviation safety and urban mobility. His work bridges theory and practice, influencing databases, graphics, and geographic systems. Education: B.S. Engineering, UCLA M.S. Operations Research, Stanford M.S./Ph.D. Computer Science, Stanford Samet has advised numerous students and led NSF-funded projects on spatio-textual data, similarity search, and spreadsheet analysis. His honors include the ACM Paris Kanellakis Award (2011), IEEE Wallace McDowell Award (2014), and UCGIS Research Award (2009). His labs and teams focus on spatial algorithms, visualization, and GIS applications. Notable projects include VASCO (spatial index demo), MARCO (image databases), and CHOLERA (disease tracking).