جست‌وجوی استاد و پژوهشگر

Petr Janataمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Music Psychology
• Auditory Perception
• +۴ مورد دیگر

Petr Janata is a Professor in the Department of Psychology at the University of California, Davis, and a faculty member at the UC Davis Center for Mind and Brain. His research centers on cognitive neuroscience of music, investigating neural mechanisms underlying music-evoked autobiographical memories and the experience of "groove." He serves on the Board of the Society for Music Perception and Cognition and co-founded the UC Music Experience Research Community Initiative (UC MERCI). Janata's educational background includes: Ph.D. in Biology (Neuroscience) from the University of Oregon (1996) B.A. in Interdisciplinary Studies (Biology/Psychology) from Reed College (1990) His research employs behavioral experiments, fMRI, EEG, and computational modeling to explore how music engages memory, emotion, and sensorimotor systems. Key projects examine music-evoked remembering, the psychology of groove, auditory attention mechanisms, and timbre-emotion links. His work reveals how music activates domain-general brain networks for expectation, memory, and emotional processing. Recent publications (2018-2025) show increasing focus on cross-cultural emotional responses to music, neural correlates of nostalgia, mental replay mechanisms, and clinical applications of music cognition. His lab develops innovative paradigms like the Groove Enhancement Machine (GEM) to manipulate sensorimotor synchronization while measuring subjective enjoyment. Janata's scientific recognition includes: Guggenheim Fellowship (2010) Dual Fulbright Fellowships (1990-91, 2010-11) Music Has Power Award from the Institute of Music and Neurological Function (2010) He has delivered over 100 invited lectures globally and served as scientific advisor to Coro Health LLC before founding Meamer, Inc. in 2017 to connect people through memories and music. His translational work bridges basic cognitive neuroscience with real-world applications in health and technology. The Janata Lab at UC Davis integrates neuroimaging, behavioral testing, and computational modeling to advance understanding of music cognition. Current projects explore lifespan neural changes in music processing, adaptive virtual partners for synchronization studies, and sonification systems for physiological monitoring.

Michalis Vazirgiannisمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Graph Analysis
• +۱۱ مورد دیگر

Michalis Vazirgiannis is a Professor at LIX, École Polytechnique in France, where he leads the Data Science and Mining group (DaSciM). He holds a degree in Physics and a PhD in Informatics from Athens University (Greece), and a Master's degree in AI from Heriot Watt University, Edinburgh (UK). His academic career spans multiple prestigious institutions including Fraunhofer and Max Planck MPI in Germany, INRIA/FUTURS in Paris, AUEB in Greece, Telecom-Paristech, ENS in France, Tsinghua and Jiaotong Shanghai in China, and Deusto University in Spain. Professor Vazirgiannis's research focuses on machine and deep learning methods for graph analysis, including community detection, graph clustering, node embeddings, and influence maximization. His work in text mining encompasses Graph of Words, word embeddings with applications to web advertising and marketing, event detection, and summarization. He has active collaborations with industrial partners in analytics and machine learning for large-scale data repositories across various application domains such as recommendations, meeting summarization, influence metrics for scientific and social networks, and predictive maintenance. His recent publications demonstrate a strong emphasis on Graph Neural Networks, multilingual NLP (particularly for French and Arabic), and applications of deep learning to diverse domains including social networks, legal text, and biomedical data. There's a clear trajectory toward developing more efficient, explainable, and specialized models that address real-world challenges in data analysis. ERCIM fellowship Marie Curie EU fellowship Tencent "Rhino-Bird International Academic Expert Award" (2017) Best Paper Award at IJCAI 2018 Best Paper Award at CIKM 2013 Professor Vazirgiannis has supervised 29 completed PhD theses and has attracted significant R&D funding from national and international sources, including research agencies and industrial partners such as Google, Airbus, Huawei, Deezer, BNP, and LVMH. He leads or has led several academic research chairs including DIGITEO (2013-15), ANR/HELAS (2020-25), and AXA (2015-2018). The DaSciM research group, which he leads at École Polytechnique, has extensive experience in real-world R&D projects involving large-scale data mining. The team maintains active collaborations with major industrial partners including AIRBUS, Google, BNP, Tencent, and Tradelab, working on cutting-edge machine learning projects. The group has co-organized major conferences such as ECML PKDD 2011 and ECML/PKDD 2017 and participates in the senior organization of AI and data mining events like AAAI and IJCAI.

Aaron Youngمشاهده پروفایل

دانشیار

• Human Augmentation
• Wearable Robotics
• Assistive Devices
• +۷ مورد دیگر

Aaron Young is an Associate Professor in the Woodruff School of Mechanical Engineering at Georgia Institute of Technology and a program faculty member in the Biomedical Engineering School. He serves as Director of the Exoskeleton and Prosthetic Intelligent Controls (EPIC) Lab, focusing on robotic human augmentation through advanced control systems for prosthetics and exoskeletons. Education: Postdoctoral Fellow, University of Michigan (2014-2016) Ph.D., Northwestern University (2014) M.S., Northwestern University (2011) B.S., Purdue University (2009) Dr. Young's research addresses clinically viable control systems for wearable robotic devices, emphasizing intent recognition , EMG signal processing , and machine learning integration. His work targets mobility impairments from stroke, amputation, cerebral palsy, and neurological injuries, aiming to reduce metabolic costs, restore natural biomechanics, and enhance community ambulation. Key innovations include data-driven control frameworks , biomechanical terrain adaptation , and anthropometry-based personalization . His recent publications highlight advancements in deep learning for real-time biomechanics , EMG-informed joint estimation , and adaptive assistance systems . The EPIC Lab's facilities feature a terrain park with force plates , motion capture systems , and HumoTech simulation platforms for device testing. Scientific Awards: New Faces of Engineering (IEEE USA, 2017) Military Health System Team Award (2015) NSF Graduate Fellowship (2010) NDSEG Fellowship (2010) IEEE EMBC 3rd Place (2013) Projects include NSF-funded hip exoskeletons for stroke survivors, DoD-powered prostheses for amputees, and Pediatric knee exoskeletons for cerebral palsy. The lab cultivates interdisciplinary expertise in robotics , biomedical engineering , and human-machine interaction .

Sasan Mahmoodiمشاهده پروفایل

دانشیار

• Medical Image Analysis
• Biometrics
• Computer Vision
• +۱ مورد دیگر

Dr. Sasan Mahmoodi is an Associate Professor at the School of Electronic and Computer Science , University of Southampton. His research focuses on Medical Image Analysis , Biometrics , and Computer Vision , with applications in healthcare and security systems. Research Groups: Vision, Learning and Control; Institute for Life Sciences; Centre for Machine Intelligence His work spans deep learning , rule-based AI , and pattern recognition in medical imaging, including applications for neonatal brain injury prognosis and radiographic knee osteoarthritis classification. He also contributes to biometric technologies like facial profile recognition and gait analysis. Recent publications highlight his expertise in: Domain adaptation for biometric systems Infrared gait recognition databases Motion artefact correction in HRpQCT imaging Histopathology image segmentation using U-Net variants Dr. Mahmoodi supervises PhD students in computer science and human health development and collaborates on interdisciplinary projects involving machine learning and medical imaging.

Elisa Pellegrinoمشاهده پروفایل

پژوهشگر ارشد

• Phonetics
• Computational Linguistics
• Prosody
• +۷ مورد دیگر

Dr. Elisa Pellegrino is a senior Post-Doc in Phonetics at the Department of Computational Linguistics , affiliated with Zeppelin University and the Digital Society Initiative of the University of Zurich . Her research focuses on voice individualization, vocal accommodation, and the role of speaker-specific information in speech temporal variability. Role: Senior Post-Doc in Phonetics University: Zeppelin University School: Faculty of Arts and Social Sciences Department: Department of Computational Linguistics Email: elisa.pellegrino@uzh.ch Research Interests: Prosody and speech rhythm in native and second language acquisition Vocal accommodation in cross-dialectal interactions Speaker individuality and forensic phonetics Age-related speech temporal variability Speech disorders and Parkinson’s disease Applications of speech technology in linguistics and education

Amanda Watsonمشاهده پروفایل

استادیار

• Wearable Technology
• Biomedical Engineering
• Cyber-Physical Systems
• +۲ مورد دیگر

Amanda Watson is an Assistant Professor in Electrical and Computer Engineering at the University of Virginia, with joint appointments in Computer Science. She leads the Watson Research Lab within the UVA Link Lab, a multidisciplinary center for Cyber-Physical Systems (CPS) and Internet of Medical Things (IoMT) research. Her work bridges wearable technology with healthcare and athletic performance applications, focusing on noninvasive monitoring, physiological signal analysis, and safety-critical medical devices. She is also the cofounder and CEO of Luminosity Wearables, commercializing a noninvasive continuous glucose monitor. Education: PhD in Computer Science (2020) - College of William & Mary MSc in Computer Science (2016) - College of William & Mary Bachelors in Computer Science and Mathematics (2014) - Drury University Her research spans multiple domains including: Wearable spectroscopy for nutrition and skin health Machine learning for drug overdose and fall risk detection Biomechanical monitoring in sports medicine Wearable support for visual and neurological impairments IoMT device integration and analytics Recent publications (2024-2025) show strong emphasis on calibration-free physiological monitoring systems, with technical contributions in spectral analysis , multi-wavelength sensing , and rapid prototyping for healthcare wearables. Applications range from maternal health to gerontological social isolation detection. Lab and Team: The Watson Research Lab at UVA develops wearable solutions for clinical and athletic contexts, with ongoing collaborations in the PRECISE Center at University of Pennsylvania and LENS lab at William & Mary alumni network. She works with multidisciplinary teams including engineers, clinicians, and data scientists.

Katharina Eggenspergerمشاهده پروفایل

پژوهشگر

• Automated Machine Learning (AutoML)
• Hyperparameter Optimization (HPO)
• Tabular Machine Learning
• +۱ مورد دیگر

Katharina Eggensperger is an Early Career Research Group Leader at the University of Tübingen , leading the AutoML for Science group within the Cluster of Excellence Machine Learning for Science . She previously completed her Ph.D. at the University of Freiburg under Frank Hutter and Marius Lindauer (2022), and actively contributes to the AutoML community through open-source tool development and competition leadership. Co-developer of AutoML.org tools Faculty member of IMPRS-IS Chair for multiple AutoML workshops/conferences (2019-2025) Her research focuses on automated machine learning (AutoML) with specific attention to: AutoML Systems Hyperparameter Optimization Tabular Machine Learning Scientific Applications of ML She has organized multiple AutoML schools and conferences, including serving as Program Chair for AutoML 2024 and Non-archival Track Chair for AutoML 2025. Her work emphasizes making machine learning accessible through automation while maintaining scientific rigor and interpretability, particularly for tabular data applications. Katharina actively recruits PhD students through IMPRS-IS and collaborates with institutions like the University of Freiburg and Cyber Valley .

• Cybersecurity
• Data Encryption
• Access Control Systems
• +۳ مورد دیگر

Willem Jonker is a Full Professor at the Digital Society Institute, specializing in Semantics, Cybersecurity & Services. His research focuses on encryption schemes, access control, and privacy-preserving technologies. He has contributed to over 120 publications, with recent work addressing CVE-to-CWE mapping, anomaly detection in network traffic, and functional encryption systems. His expertise aligns with UN Sustainable Development Goals related to secure digital systems and privacy. Jonker has supervised 10 students and actively participates in academic conferences, presenting on topics like secure data management and cryptographic protocols. Research interests include cryptographic protocols, secure data management, and cybersecurity solutions. Notable projects involve developing methods for detecting covert channels, enhancing data privacy in healthcare, and improving secure search over encrypted data. He has also contributed to standards in digital rights management and forensic image recognition.

• Cartography
• Geomatic Engineering
• Historical Map Analysis
• +۴ مورد دیگر

Dr. Yizi Chen is a Researcher affiliated with the Professorship for Cartography at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. Their work focuses on advancing cartographic techniques through AI-driven methods, historical map analysis, and geospatial technologies. Key contributions include automated map vectorization, semantic segmentation of historical maps, and integrating multimodal data for robotic systems. They have published extensively in top-tier journals and conferences, addressing challenges in deep learning applications for geomatic engineering. Education details are not explicitly provided in the text. Research interests include semantic segmentation, generative AI for cartography, and steganography in image translation. Notable publications span topics from eye-tracking segmentation to urban land use mapping, reflecting a strong interdisciplinary approach. Dr. Chen collaborates on projects involving historical map digitization and benchmarking datasets for computer vision tasks. No awards or grants are mentioned. Their work contributes to advancing geomatic engineering through innovative solutions in digital mapping and spatial data analysis.

Bernard Kochمشاهده پروفایل

استادیار

• Science of science
• Culture
• Cultural evolution
• +۲ مورد دیگر

Bernard Koch is an Assistant Professor in the Department of Sociology at the University of Chicago. His research focuses on the science of science, culture, cultural evolution, AI ethics, and computational social science. Prior to joining the University of Chicago, he was a Postdoctoral Research Fellow at Northwestern University’s Kellogg School of Management. He earned his Ph.D. in Sociology from UCLA in 2023. His work bridges sociology and computational methods, exploring topics such as machine learning applications in social research, ethical implications of AI, and cultural dynamics. Recent projects include analyzing the role of large language models (LLMs) in social simulations and confronting the misuse of genetics in online contexts. Koch’s articles span themes like data-centric machine learning (DMLR), the historical development of deep learning, and the lifecycle of datasets in research. He also investigates cultural evolution through case studies like music subcultures and material culture diversification. He holds no listed awards but has contributed to interdisciplinary collaborations, including genomics research on the Mnemiopsis leidyi organism. While no formal advisees are listed, his research group likely engages in computational social science projects.

Davin Wallaceمشاهده پروفایل

دانشیار

• Coastal Geology
• Marine Geology
• Paleotempestology
• +۳ مورد دیگر

Davin Wallace is an Associate Professor at the University of Southern Mississippi's School of Ocean Science and Engineering, where he investigates coastal and marine system responses to storms, sea-level rise, and sediment dynamics across timescales ranging from days to millennia. His research employs field observations, laboratory analyses, and numerical modeling, with active sites across the Gulf of Mexico, Bermuda, and the Philippines. Education: Ph.D. in Earth Science, Rice University (2007-2010) B.S. in Geology and German, Tulane University (2003-2006) Research Focus: Dr. Wallace's work bridges paleotempestology, coastal geomorphology, and sedimentary processes. His research examines hurricane impacts on sediment structures, barrier island resilience under sea-level rise, and Holocene coastal evolution. He specializes in reconstructing historical storm patterns using geologic proxies and assessing anthropogenic influences on coastal erosion. Publication Trends: His recent articles demonstrate interdisciplinary approaches to coastal vulnerability, combining geophysical data, machine learning, and multiproxy sediment analysis. Work consistently addresses climate change impacts, with emphasis on sedimentation mechanisms during extreme events and Quaternary landscape evolution. Scientific Recognition: No major awards documented in provided sources. Academic Leadership: Leads the USM Coastal Evolution and Hazards Research Lab, supervising field campaigns and collaborative projects. Secured grants for Gulf Coast studies from NSF and NOAA. Mentors graduate students in geological oceanography programs and coordinates international research teams across field sites.

• Computer Vision
• Natural Language Processing
• Machine Learning
• +۱ مورد دیگر

Dr. Zhenghao Chen is an Assistant Professor at the University of Newcastle. He holds a B.Eng. H1 and Ph.D. from the University of Sydney (2017 and 2022). His research focuses on Computer Vision, NLP, and Machine Learning, with expertise in Generative AI. He has published in top conferences like CVPR and journals such as IEEE T-IP. Awards include the Google Australia Prize and ACM SIGMM Outstanding Thesis Award. He previously worked at TikTok and Disney Research, and serves on program committees for major conferences. Research interests emphasize generative models and industrial applications. His publications span topics like image compression, facial recognition, and medical imaging. Awards highlight academic and industrial recognition. Teaching includes courses on visual signal understanding and video intelligence. Current roles include HDR recruitment and organizing international workshops.

• Sedimentary Geology
• Stratigraphy
• Subsurface Fluid Flow
• +۳ مورد دیگر

Professor Gary Hampson is a Professor of Sedimentary Geology at the Department of Earth Science & Engineering, Faculty of Engineering, Imperial College London. His roles include Director of Undergraduate Studies (2023–present) and former Director of the Petroleum Geoscience MSc course. He holds affiliations with the Energy Futures Lab, Grantham Institute, and NORMS research groups. Hampson's research focuses on depositional systems, stratigraphy, and subsurface reservoir characterization, with applications to CO2 storage and fluid flow dynamics. Education: PhD in Sedimentology and Sequence Stratigraphy, University of Liverpool (1991–1995) BA in Natural Sciences (Geology), University of Cambridge (1988–1991) Research Interests: His work integrates sedimentology, stratigraphy, and reservoir modeling to understand subsurface fluid dynamics. Key areas include sediment dispersal patterns, stratigraphic architecture, and the impact of heterogeneity on reservoir performance. Recent studies emphasize CO2 storage potential in sedimentary systems and the application of advanced modeling techniques. Articles Trends: Recent publications highlight CO2 storage mechanisms, sedimentological heterogeneity in reservoirs, and the use of machine learning in geological analysis. His work bridges theoretical stratigraphy with applied reservoir engineering, particularly in carbonates and fluvio-deltaic systems. Awards: 2020 IAMG Best Paper Award 2016 AAPG Bennison Lecturer 2010 SEPM Excellence Awards Advising & Grants: Hampson has advised numerous students and led projects on reservoir characterization. His editorial roles include co-chief editor of the Journal of Sedimentary Research and guest editorships in Petroleum Geoscience. Labs/Teams: Active in the Energy Futures Lab and NORMS initiative, focusing on novel reservoir modeling and simulation for subsurface energy systems.

Patrick Kluthمشاهده پروفایل

استاد

• Ion Beam Modification of Materials
• Solid-State Nanopores
• Synchrotron Radiation Techniques
• +۴ مورد دیگر

Patrick Kluth is a Professor at the Research School of Physics, Australian National University, leading a research group focused on swift heavy ion-modified materials and nanopore technology. His work bridges materials science, physics, and biomedical applications. Education : Dipl. Phys. from Düsseldorf, Germany; PhD in Physics from RWTH Aachen, Germany (2002, summa cum laude). Research Interests center on: Ion track technology for solid-state nanopore fabrication Advanced materials characterization (SAXS, X-ray absorption spectroscopy) Defect engineering in semiconductors and superconductors Nano-fabrication and semiconductor processing methods Bio-sensor development and ion separation technologies Recent Research Trends show a focus on: Developing affordable microcontroller-assisted nanopore fabrication platforms Enhancing flux pinning in superconductors via ion irradiation Engineering nanomaterials for space applications (carbon-fibre composites) Exploring radiation effects on perovskite solar cells and graphene-enhanced composites Combining machine learning with nanopore sensing for biomarker detection Scientific Awards : Feodor-Lynen Fellowship Borcherts-Medal for PhD excellence Three ARC Fellowships (Postdoctoral, Research, Future) Leadership Roles : Head of Department (2018-2020), Associate Director HDR (2020-2023). His projects include collaborations on Alzheimer's detection sensors and carbon-fibre additive manufacturing for space applications.

Kourosh Davoudiمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Kourosh Davoudi is an Associate Professor of Computer Science at Ontario Tech University's Faculty of Science. He holds a PhD in Computer Science from York University with a focus on Machine Learning and Data Mining. Prior to joining Ontario Tech in 2019, he was a postdoctoral research fellow at the University of Waterloo's Department of Management Sciences. His research interests span Natural Language Processing, Deep Learning, Reinforcement Learning, Graph Mining, and Machine Learning. He actively supervises graduate students in these areas and teaches courses such as Data Mining and Artificial Intelligence. His research emphasizes practical applications of AI techniques in areas like outbreak detection, sentiment analysis, and automated grading systems. Recent work includes innovations in neural document segmentation, vision-language models, and hybrid outbreak detection using social media data. His publications consistently address challenges in algorithm design, explainable AI, and domain-specific NLP applications. Dr. Davoudi has contributed to conferences such as COLING, EMNLP, and IEEE transactions, focusing on interdisciplinary applications of machine learning. His work bridges theoretical advancements with real-world problems in healthcare, education, and social media analysis.