Find Academic Supervisors

John G. FlanneryView profile

Professor

• Gene Therapy
• Molecular Biology
• Retinal Degenerations
• +4 more

John G. Flannery serves as Professor of Molecular Therapeutics in the Department of Molecular and Cell Biology at the University of California, Berkeley. His research targets inherited retinal degenerations including retinitis pigmentosa and Usher syndrome, which collectively affect approximately 100,000 Americans and 1 in 3000 people globally. The Flannery Lab develops gene therapies using adeno-associated virus (AAV) and lentiviral vectors to deliver neuroprotective factors and correct genetic defects in photoreceptor and retinal pigment epithelial cells, with current emphasis on engineering vectors for efficient Müller glial cell transduction to enable broad retinal coverage. The lab investigates genetic and biochemical mechanisms of photoreceptor degeneration through animal models including rd mice, rhodopsin mutant rats, and Usher syndrome knockout mice. Key therapeutic strategies encompass viral-mediated gene replacement for recessive diseases, CRISPR/siRNA for dominant mutations, and neurotrophic factor delivery systems. Recent work focuses on overcoming viral delivery limitations through capsid engineering and addressing immune barriers to retinal gene therapy, particularly for Müller cell transduction which could revolutionize neuroprotective factor distribution. Analysis of Dr. Flannery's recent publications reveals consistent expertise in viral vector development for retinal applications, with significant contributions spanning AAV capsid evolution in primates, Müller cell-specific transduction, and optogenetic vision restoration. His research demonstrates progression from fundamental vector characterization to sophisticated in vivo applications, increasingly addressing translational challenges like immune responses and cell-type specificity through interdisciplinary collaborations with engineering and clinical teams. The Flannery Lab website explicitly states their mission as 'optimizing preclinical gene therapy and vision restoration with the therapeutic approach of using adeno-associated viruses to deliver gene replacements to models of inherited retinal degenerative diseases.' The team develops retinal cell-specific vectors and explores novel approaches for both dominant and recessive diseases, with particular emphasis on Müller glial cell transduction to overcome current limitations in achieving widespread therapeutic delivery across the retina.

Alexander PrechtelView profile

Researcher

• Mathematics in Geosciences
• Soil Structure Formation
• Reactive Transport Modeling
• +7 more

Dr. Alexander Prechtel is an Academic Councillor at the Chair of Applied Mathematics I at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where he has been working since 2005. He serves as the representative of academic mid-level staff in the Department of Mathematics since 2010 and previously worked as the new construction officer for the department from 2008-2012. His research focuses on mathematical modeling in geosciences, particularly soil structure formation, reactive transport in porous media, and natural attenuation processes. Prechtel earned his Dipl.-Math. from the University of Bayreuth in 1997 with a minor in Geoecology focusing on hydrology, followed by a DEA in Hydrology and Geochemistry from École Nationale Supérieure des Mines de Paris in 1998. He completed his Dr. rer. nat. in Mathematics at FAU in 2005 under Prof. Dr. P. Knabner with a dissertation on hydrogeochemical multicomponent transport problems. His research interests span mathematics in geosciences and natural sciences, with specific focus on structure formation in soils, modeling and simulation of reactive mass transport in porous media, evaluation of natural self-cleaning power of soils, and efficient solution methods for hydrogeochemical multicomponent models. Recent work has concentrated on soil microaggregates, particularly in the rhizosphere, and the carbon turnover processes associated with soil structure dynamics. He has made significant contributions to developing mechanistic models that explicitly represent pore structures derived from CT scans to study self-organization of soil aggregates. His publication record shows a clear progression toward increasingly sophisticated multiscale modeling approaches, with recent papers focusing on pore-scale interactions between roots, soil structure, and carbon dynamics. The research demonstrates how exudates like mucilage play a crucial role in soil structure formation in the rhizosphere, with persistent stabilization effects even after the exudates themselves have decomposed. Prechtel has successfully secured substantial research funding, with third-party funding volume as PI/Co-PI since 2015 totaling approximately 1.176 million euros. He has supervised numerous Bachelor's, Master's, and Diplom theses across mathematics, technomathematics, and Integrated Life Sciences programs. His teaching portfolio includes courses on differential equation models, metabolic networks, and groundwater modeling. As a reviewer, he serves for the Agence Nationale de Recherche in France and the Deutsche Forschungsgemeinschaft (DFG), and contributes to multiple prestigious journals including BioSystems, Environmental Science & Technology, Geoderma, and Water Resources Research.

Mohammad RastegariView profile

Adjunct Assistant Professor

• Computer Vision
• Efficient Machine Learning
• Model Compression
• +3 more

Mohammad Rastegari serves as a senior technical manager in Apple's AI/ML organization and holds an affiliate assistant professor position in the Computer Science and Engineering Department at the University of Washington. Previously, he was a research scientist at the Allen Institute for AI (AI2) where he contributed to the PRIOR team, and co-founded XNOR.ai as Chief Technology Officer. He completed his Ph.D. at the University of Maryland under the supervision of Professor Larry S. Davis, focusing on computer vision and machine learning. His research centers on efficient deep learning with major contributions in binary neural networks (notably XNOR-Networks for resource-constrained devices) and model compression . Current work extends to large language model efficiency through weight clustering, token pruning, and memory optimization while maintaining strong foundations in computer vision. Analysis of his recent publications reveals a strategic shift toward optimizing transformer-based architectures across vision and language domains, with consistent emphasis on deployable solutions for edge computing and real-world applications. He co-founded XNOR.ai (acquired by Apple) and contributed to AI2's PRIOR initiative, demonstrating a career trajectory bridging academic innovation and industrial implementation in efficient AI systems.

Marcin JurekView profile

Assistant Professor

• Spatial Statistics
• Computational Methods
• Gaussian Processes
• +3 more

Marcin Jurek is an Assistant Professor in the Department of Statistics and Data Science at Southern Methodist University (SMU). He previously held a postdoctoral position at the University of Texas at Austin, working under Dr. Catherine Calder and Dr. Corwin Zigler, and completed his PhD in Statistics at Texas A&M University in August 2020 under Dr. Matthias Katzfuss. Research Focus: Computational methods in spatial statistics, scalable Gaussian process approximations, spatio-temporal modeling Software Development: Maintains the GPvecchia package for R/Python Collaborations: National Center for Atmospheric Research (NCAR), Texas A&M University His work addresses challenges in analyzing massive spatio-temporal datasets through hierarchical sparse Cholesky decompositions and Vecchia approximations. Current research includes statistical inference for mobility trajectories and high-dimensional data analysis. He organized an SMU workshop on high-dimensional data in 2024 and has contributed to applications in environmental monitoring and agricultural data science. Recent publications demonstrate his expertise in developing computationally efficient algorithms for complex statistical problems, including applications to groundwater contamination datasets and maize breeding programs. He actively engages in interdisciplinary research across climate modeling, movement ecology, and Bayesian inference.

• High-Performance Integrated Circuit Design
• Artificial Intelligence Accelerators
• Digital Signal Processing Chips
• +3 more

Dr. Fengwei An is an Associate Professor at the Shenzhen-Hong Kong Institute of Microelectronics , Southern University of Science and Technology (SUSTech). He earned his Ph.D. in Engineering from Hiroshima University (2013) , following a Master's (2010) and Bachelor's (2006) from Qingdao University of Science and Technology. Current Role : 2025-Present - Associate Dean and Associate Professor, SUSTech Shenzhen-Hong Kong Institute of Microelectronics Prior Academic Roles : 2017-2018 - Associate Professor, Hiroshima University; 2013-2017 - Assistant Professor, Hiroshima University Industry Experience : 2018-2019 - Chief Engineer, Panasonic Semiconductor Co., Ltd., Japan Research Interests focus on low-power edge artificial intelligence chip design for computer vision, including: Ultra-large-scale digital integrated circuit design System-on-Chip (SoC) integration Image processing and recognition Machine learning hardware Autonomous driving applications High-speed motion tracking systems Publications include over 80 top-tier journal/conference papers (e.g., TCAS-I/II, ESSCIRC, APCCAS) on AI accelerators, stereo vision processors, and sensor interfaces, with 15 recent articles highlighting advancements in stereo matching, video denoising, and reconfigurable coprocessors. Scientific Awards : 2023 - SUSTech Outstanding Teaching Award 2022 - APCCAS Best Paper Nomination 2022 - PrimeAsia Bronze Leaf Award 2020 - Wu Wenjun Artificial Intelligence Science and Technology Award (Second Prize) Patents : 9 Chinese and 3 Japanese inventions in AI chip design, stereo matching systems, and sensor interfaces.

Aliaksandr HubinView profile

Associate Professor

• Statistics
• Artificial Intelligence
• Econometrics
• +4 more

Aliaksandr Hubin is an Associate Professor at the University of Oslo's Department of Mathematics and Natural Sciences, affiliated with the Center for Computational Inference in Evolutionary Life Science (CELS) and Statistics and Data Science research groups. His career spans Bayesian methodology development, machine learning applications, and interdisciplinary research. PhD in Statistics (University of Oslo, 2018) MSc in Operations Research (Molde University College, 2014) Specialist degree in Economic Cybernetics (Belarusian State University, 2013) Research spans: Bayesian model selection and averaging Probabilistic machine learning Computational statistics Applications in genomics, clinical diagnostics, and aquaculture Weak supervision methods in NLP Medical decision support systems Recent publications focus on: Bayesian neural network compression Clinical score validation Outlier detection mechanisms Evolutionary optimization in inference Domain-informed deep learning Scientific recognition: NIMA 2014 award Multiple student research awards (2012-2013) Graybill poster competition second place (2017) Methodological contributions include: Genetically modified MCMC algorithms Adaptive simulated annealing EM Probabilistic framework development

• Biophysics
• Optical Sensors
• Metrology
• +3 more

Dr. Koit Mauring is an Associate Professor at the Institute of Physics within the Faculty of Science and Technology at the University of Tartu, where he has maintained academic appointments since 1974. His career includes a Fulbright Scholarship at Stanford University (2000-2001) and extensive research in optical physics and biophysics. Education: PhD in Physics (Candidate of phys.math.), Estonian Academy of Sciences (1982) Higher Education in Physics, University of Tartu (1969-1974) Research Focus: Dr. Mauring's work bridges optical metrology and biomedical applications, specializing in: Optical sensor development for chemical detection Biophysical studies of fluorescent proteins Cataract diagnostics through light scattering analysis Advanced instrumentation for precision measurements Publication Trends: His 58 publications demonstrate sustained focus on optical measurement techniques, with recent emphasis on medical diagnostic devices and fluorescent protein dynamics. Work frequently appears in applied optics and biophysics journals. Awards & Honors: Estonian American Innovation Award Runner-up (2011) Fulbright Scholarship (2000) USSR Academy of Sciences Prize (1984) Projects & Leadership: Principal Investigator for cataract diagnostic device development and Estonian team leader for the CRDF-ETF collaborative grant on controlled molecular dynamics of fluorescent biopolymers. Holds a patent for quantitative cataract diagnostics apparatus. Serves on the IUPAP Commission for Metrology since 2005.

Zeynep Özer ÖzcanView profile

Assistant Professor

• Ophthalmology
• Refractive Surgery
• Corneal Diseases
• +3 more

Zeynep Özer Özcan serves as an Assistant Professor in the Department of Ophthalmology at Gaziantep University Faculty of Medicine since 2024. Her academic foundation includes a medical degree from Hacettepe University Faculty of Medicine (2008-2014) followed by ophthalmology specialization at Gaziantep University (2016-2020) within the Department of Surgical Medicine. Her educational background comprises: Medical Degree: Hacettepe University Faculty of Medicine (2008-2014) Ophthalmology Specialization: Gaziantep University Faculty of Medicine Department of Surgical Medicine (2016-2020) Dr. Özer Özcan's research spans ophthalmology with emphases on refractive surgery outcomes, corneal pathologies including keratoconus, and innovative applications of artificial intelligence in patient education. She investigates vascular dynamics through choroidal imaging techniques like OCT angiography, examining relationships between systemic conditions (Wilson's disease, preeclampsia, vitamin D deficiency) and ocular manifestations. Her work bridges clinical ophthalmology with bibliometric analysis of research impact in eye care literature. Analysis of her 13 publications (2020-2024) reveals three dominant research streams: bibliometric studies of high-impact ophthalmology literature (particularly refractive surgery and keratoconus), AI-driven patient education tools using chatbots, and clinical investigations of choroidal/vascular changes using advanced imaging. Approximately 60% of her work appears in Q2 SCI-Expanded journals, demonstrating consistent contributions to ophthalmology knowledge translation and technical innovation. No scientific awards were documented in the source material. While specific student mentorship details and grant funding aren't provided, her active publication record across multiple subspecialties suggests ongoing research supervision and potential grant involvement. Her collaborative patterns indicate regular teamwork with colleagues across ophthalmology subspecialties at Gaziantep University. As a core faculty member of Gaziantep University's Department of Ophthalmology, she contributes to both clinical care and academic missions. Her research collaborations span refractive surgery, corneal diseases, neuro-ophthalmology, and ocular imaging teams, leveraging departmental resources for comprehensive eye care research.

• Machine Learning
• Optimization
• Data Mining
• +2 more

Dr. Annabella Astorino is a researcher at ICAR-CNR (Italian National Research Council) in Rende, Italy, with expertise in machine learning, optimization, and computational biology. Her work focuses on classification algorithms using nonsmooth optimization, spherical separation, and multiple instance learning (MIL) approaches. Key Research Themes Geometric separation techniques (polyhedral, spherical) Multiple instance learning for biomedical applications Nonsmooth optimization in semisupervised learning Clustering methods for edge detection in images Recent publications highlight her development of Lagrangian relaxation for MIL, kernel-enhanced spherical separation algorithms, and DC optimization for computer vision tasks. Her collaborations include researchers like A. Fuduli, M. Gaudioso, and P. Veltri.

• Medical Imaging
• Ultrasound Tomography
• Image Registration
• +4 more

Torsten Hopp is a Research Associate at the Institute for Data Processing and Electronics (IPE) at Karlsruhe Institute of Technology (KIT). His work focuses on advanced medical imaging technologies, particularly 3D ultrasound computer tomography (USCT) and its integration with MRI and X-ray modalities for breast cancer diagnosis. Research Interests: Ultrasound tomography system development Image registration algorithms Machine learning applications in medical imaging Biomechanical and computational modeling GPU-accelerated image reconstruction Multimodal imaging for clinical workflows Publication Trends: Torsten Hopp has contributed extensively to the evolution of 3D USCT, with recent work emphasizing deep learning integration , refraction correction , and patient-specific modeling . His research bridges hardware innovation (e.g., PtQube device) with computational methods for clinical translation. Labs & Teams: Affiliated with KIT's Institute for Data Processing and Electronics , he collaborates on projects like the High Data Rate Processing and Analysis Initiative , advancing ultrasound tomography for breast cancer screening.

• Medical Imaging
• MRI Technology
• RF Coil Design
• +7 more

J. Rock Hadley is a researcher in the Department of Radiology and Imaging Sciences at the University of Utah , specializing in Advanced MRI Imaging and Custom RF Coil Design . His work focuses on Image-Guided High-Intensity Focused Ultrasound Therapy , Neurovascular Imaging , and Breast-Specific MRI Devices . Education: PhD, University of Utah ME, University of Utah BS, University of Utah Hadley's research spans MRI Technology Development , including RF Coil Design , Gradient Coil Systems , and Image-Guided Robotic Procedures . His recent work emphasizes Transcranial MRgHIFU , Carotid Artery Imaging , and High-SNR MRI Coils for organs like the Pituitary Gland and Optic Nerve . The 15 most recent publications highlight his contributions to 3T MRI Systems , MR Thermometry , and Phased Array Coil Decoupling . Articles from 2025–2020 demonstrate sustained innovation in Medical Robotics , Breast Imaging , and Neurovascular MRI . Hadley holds a patent for an Anatomical Positioning System (2009) and has collaborated extensively in Carotid Bifurcation Studies and Optic Nerve Imaging . His work is supported by grants and partnerships with institutions like the Coil Lab at the University of Utah.

Hulusi KafalıgönülView profile

Adjunct Professor

• Systems Neuroscience
• Visual Perception
• Multisensory Integration
• +4 more

Hulusi Kafalıgönül is an Adjunct Professor at Bilkent University, holding dual affiliations with the National Magnetic Resonance Research Center (UMRAM) and the Aysel Sabuncu Brain Research Center. He directs the Cortical Dynamics and Perception Lab and serves as faculty in the Interdisciplinary Neuroscience Program. His academic credentials include: Ph.D. in Electrical & Computer Engineering, University of Houston (2007) Certificate in Cognitive Science, Center for Neuro-Engineering & Cognitive Science, University of Houston (2007) B.S. in Electrical & Electronics Engineering, Boğaziçi University, Istanbul (2003) Dr. Kafalıgönül's research integrates experimental and theoretical approaches to decode neural mechanisms of visual perception. His lab employs psychophysics, brain imaging, and computational modeling using neural networks and non-linear dynamics to investigate sensory processing hierarchies. He posits that visual system analysis provides fundamental insights into how neural activity generates perception and behavior, leveraging that one-third of the human cortex processes visual information. His scientific recognition includes: Innovative Research Award from Kavli Institute for Brain and Mind, UC San Diego He oversees active mentorship of 4 Ph.D. students and 2 Master's students while having graduated approximately 10 researchers. His work receives substantial funding from TÜBİTAK, EU Marie Curie Actions, and the British Academy, enabling cross-disciplinary investigations into sensory systems. The Cortical Dynamics and Perception Lab operates within the Aysel Sabuncu Brain Research Center ecosystem, maintaining formal affiliations with the Neuroscience and Neurotechnology Center of Excellence (NÖROM), UMRAM, and the National Nanotechnology Research Center (UNAM), facilitating multimodal neuroscience research.

• Artificial Intelligence
• Business Informatics
• Semantic Technologies
• +6 more

Prof. Dr. Ralph Bergmann is a full professor at the University of Trier since 2004 and leads the Experience-Based Learning Systems research group. Since 2020, he serves as topic-field leader for experience-based learning systems at the Trier Branch of the German Research Center for Artificial Intelligence (DFKI) . He has directed approximately 35 EU/DFG/BMBF-funded projects and authored over 200 papers (h-index 40) with four books and 13 edited proceedings. Academic Rank: Professor (Business Information Systems II) Key Collaborations: DFKI, KI-AIM, KIAFlex, DZW (Digital Twins), myRPA, SPELL Ralph Bergmann's research focuses on hybrid AI systems that combine data-driven methods (machine learning, case-based reasoning) with semantic technologies (ontologies, knowledge graphs). His work addresses knowledge-intensive processes like emergency call handling, healthcare discharge management, smart factory automation, and political argumentation analysis. He explores similarity assessment, workflow flexibility, and context-sensitive reasoning through frameworks like ProCAKE and CBRkit . Recent publications highlight IoT data integration (SensorStream, DataStream XES), large language models for knowledge engineering, and graph neural networks for similarity ranking. Application domains span Industry 4.0 , oncology decision support, water resource management, and clinical guideline conformance checking. His teaching includes courses on Data Mining , Semantic Technologies , and Research Internships in business informatics, with consultation hours held both in-person and online. Current projects like KI-AIM and SPELL emphasize AI anonymization in medicine and semantic platforms for control centers .

John A. HammerView profile

Professor

• Cell Biology
• Molecular Biology
• Immunology
• +4 more

John A. Hammer, Ph.D., serves as Senior Investigator and Chief of the Section on Molecular Cell Biology at the National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health in Bethesda, MD. His research program investigates fundamental mechanisms of cellular motility through motor proteins and cytoskeletal dynamics. Dr. Hammer earned his Ph.D. in Physiology from Pennsylvania State University in 1980 before joining NHLBI as a Staff Fellow. He has led the Section on Molecular Cell Biology since 1990, establishing himself as a pioneer in cytoskeletal research. His educational background includes advanced training in physiological systems that underpin his current molecular investigations. Research centers on motor protein functions (particularly myosin Va) in organelle transport, cellular motility, and immunological processes. Key discoveries include defining myosin Va's role in melanosome distribution for coat color determination and endoplasmic reticulum transport in neuronal function, plus identifying CARMIL as a critical linker between actin regulators and myosin I. Recent work focuses on cytoskeletal dynamics in T lymphocyte immunological synapse formation, revealing how actin retrograde flow and myosin II contraction drive receptor clustering. His publication portfolio demonstrates consistent innovation across cell biology disciplines, with recent work emphasizing molecular mechanisms of actin-myosin interactions in both basic cellular processes and immune function. Articles show evolving focus from classical cell motility models toward immunological applications while maintaining core expertise in cytoskeletal dynamics. Scientific recognition includes: NHLBI Merit Award (1990) Orloff Award (2012) Dr. Hammer has authored approximately 100 publications and provided significant editorial leadership as longtime member of the Journal of Muscle Research and Cell Motility board and former Journal of Biological Chemistry associate editor. His research program has been continuously funded through NHLBI intramural mechanisms, supporting multidisciplinary investigations using biochemical, genetic, and advanced imaging approaches. The Section on Molecular Cell Biology operates as a collaborative hub employing cell biological, biophysical, and transgenic methodologies. Current work integrates single-molecule imaging with physiological models to dissect molecular complexes connecting motor proteins to specific cargoes, with particular emphasis on regulatory mechanisms in immune cell function.

Mi-Hea ChoView profile

Professor

• Online marketing
• Tourist behavior
• Tourism Information
• +2 more

Mi-Hea Cho is a Professor in the Department of Hospitality and Tourism Management at Sejong University in Seoul, South Korea, where she has maintained an active academic position since 2003. Her scholarly contributions span nearly two decades with recent publications extending through 2023, demonstrating sustained engagement in tourism research. Education: B.A. from Hanyang University (1986) M.A. from Sejong University (1990) Ph.D. from Pennsylvania State University (2001) Research Focus: Professor Cho's research centers on Online marketing , Tourist behavior , and Tourism Information systems. Her work explores the intersection of digital technologies and tourism experiences, with particular emphasis on smart tourism applications, cross-cultural differences in tourism marketing, and the psychological aspects of tourist decision-making. She has developed significant expertise in how smartphone applications and digital platforms transform tourism information search and consumer behavior. Publication Trends: Professor Cho's scholarly output reveals an evolution from traditional tourism marketing topics toward increasingly technology-focused research. Her recent work (2021-2023) prominently features smart tourism technology, pandemic-related tourism behavior, and comparative international studies across Korea, the United States, China, and Colombia. She frequently employs cross-cultural comparative methodologies, examining how nationality and cultural background influence tourism website evaluation, technology adoption, and risk perception. Research Recognition: h-index of 8 according to Scopus metrics 543 total citations Recipient of Korea Sanhank Foundation Research Fund support Research Activities: Professor Cho maintains an active research program with consistent publication output, averaging approximately one research paper per year. Her work demonstrates strong international collaboration, particularly with researchers in the United States and Colombia. She has contributed to both theoretical frameworks and practical applications in tourism marketing, with studies directly addressing industry challenges related to digital transformation and cross-cultural marketing strategies.