جست‌وجوی استاد و پژوهشگر

Mustapha Ouladsineمشاهده پروفایل

استاد

• Diagnostic and Prognostic Methods for Complex Systems
• Artificial Intelligence in Healthcare
• Machine Learning Applications in Semiconductor Manufacturing
• +۳ مورد دیگر

Professor at Aix Marseille University's Faculty of Sciences , Mustapha Ouladsine leads cutting-edge research in diagnostic and prognostic methods for complex systems . As Vice-President for Research Infrastructure and AI since 2020, he oversees LIS Computer Science and Systems Laboratory. Directed LIS UMR 7020 (2018–present) Former Director of LSIS UMR 7296 (2008–2018) Scientific manager for €1.2M+ projects with STMicroelectronics Research Focus : Developed innovative approaches for: Equipment health index modeling in semiconductor manufacturing Dynamic sampling techniques for High-Mix Low-Volume systems Fault-tolerant control systems for drones and autonomous robots AI-based cardiac arrhythmia detection with Timone Hospital Scientific Leadership : Founded Aix-Marseille Research Federation in Computer Science Active associate editor for IEEE journals and conferences Coordinated 17+ recruitment committees at Aix Marseille University

Russell Shinoharaمشاهده پروفایل

استادیار

• Biostatistics
• Bioinformatics
• Neuroimaging
• +۳ مورد دیگر

Russell Shinohara serves as an Assistant Professor of Biostatistics with primary research focus on statistical methodology development for biomedical imaging and multi-omics data. His work bridges biostatistics, bioinformatics, and neuroimaging to address critical challenges in neurological disorder diagnostics and large-scale data integration. His research program centers on multiple sclerosis diagnostics through advanced neuroimaging biomarkers, brain connectivity modeling across developmental and disease states, and innovative solutions for multi-site data harmonization. Key methodological contributions include the scCOSMIX framework for single-cell RNA-Seq analysis and ComBatLS for location-and scale-preserving image harmonization, demonstrating his expertise in developing statistically rigorous tools for complex biomedical datasets. Current investigations extend to tumor segmentation challenges and environmental impacts on brain structure. Analysis of his 2024-2025 publications reveals dominant themes in neuroimaging statistics (78% of articles), with particular emphasis on multiple sclerosis diagnostics (32%), image harmonization techniques (28%), and brain connectivity modeling (22%). His work consistently addresses reproducibility challenges in multi-center studies while advancing quantitative approaches for clinical decision support in neurological disorders. Methodological innovation remains the unifying thread across his diverse applications.

Rolf Drechslerمشاهده پروفایل

استاد

• Formal Verification
• Quantum Computing
• RISC-V Architecture
• +۴ مورد دیگر

Rolf Drechsler is a Full Professor and Head of the Group of Computer Architecture at the University of Bremen's Institute of Computer Science since 2001, and Director of the Cyber-Physical Systems Group at DFKI Bremen since 2011. He holds an adjunct professorship at the Indian Statistical Institute and has been affiliated with Duke University. Education: Diploma (1992) and Dr. phil. nat. (1995) in Computer Science from Goethe University Frankfurt Academic Leadership: Dean of Mathematics and Computer Science Faculty (2018-2025), Vice Rector for Research (2008-2013) His research focuses on formal verification , RISC-V architectures , and quantum/in-memory computing . Recent work explores LLM integration in hardware testing and polynomial-based verification techniques. Publications from 2024-2025 span IEEE Transactions , DATE , and DAC , emphasizing automated verification , quantum circuit mapping , and LLM-driven testbench generation . Scientific Awards IEEE/ACM Best Paper Awards (2013, 2018) Berninghausen-Preis for Innovative Teaching (2018) IEEE Fellow (2015) Founder Award for Solvertec (2013) He has served on program committees for DAC, ICCAD, DATE, and founded graduate schools in Embedded Systems and System Design under Germany's Excellence Initiative.

Daniel Wiggerمشاهده پروفایل

پژوهشگر

• Solid-State Theory
• Quantum Optics
• Quantum Acoustics
• +۵ مورد دیگر

Daniel Wigger is a theoretical physicist at the Institute of Solid-State Theory & Dean’s Office, Department of Physics, University of Münster, Germany. He investigates solid-state quantum optics, quantum acoustics and ultrafast spectroscopy of semiconductor nanostructures, with emphasis on phonon-mediated control of quantum dots, 2-D materials and colour centres. Education & Career: 2012 – Diploma thesis “Squeezed phonon states in optically excited semiconductors”, University of Münster 2017 – PhD thesis “Interplay between acoustic phonons and excitons in optically driven semiconductor quantum dots”, University of Münster 2017-2020 – Post-doc with Prof. T. Kuhn, University of Münster 2020-2022 – ULAM post-doc fellow with Prof. P. Machnikowski, Wrocław University of Science & Technology 2022-2023 – Research Fellow & SFI-IRC Pathway Group Leader with Prof. O. Hess, Trinity College Dublin since 2024 – Research & teaching staff, Institute of Solid-State Theory, University of Münster Research interests: Solid-state theory, quantum optics, quantum acoustics, ultrafast non-linear spectroscopy, light-matter interaction, hybrid quantum technology, single-photon emitters and 2-D semiconductors. Scientific output: His 2021-2025 articles reveal a focus on coherent phonon effects, four-wave mixing spectroscopy, strain engineering of excitons, room-temperature nanoplasmonics, and high-harmonic probing of lattice dynamics—merging advanced spectroscopy with microscopic modelling. Teaching (summer 2025): Theoretical Basics and Modern Applications of Quantum Nanophotonics Scientific Writing and Presenting in Physics Integrated Seminar on Current Topics in the Physics of Solid-State Nanosystems He advises graduate students and is active in public scholarly communication (Google Scholar, ORCID).

Mikael Vejdemo-Johanssonمشاهده پروفایل

دانشیار

• Topological Data Analysis
• Applied Category Theory
• Algebraic Topology
• +۵ مورد دیگر

Mikael Vejdemo-Johansson is an Associate Professor of Data Science and Mathematics at the Department of Mathematics, CUNY College of Staten Island, with concurrent roles as Executive Officer of Computer Science and Director of Data Science at the CUNY Graduate Center. His work bridges applied algebraic topology, computational mathematics, and data science, with a focus on topological data analysis (TDA) and its applications to diverse domains. He has contributed extensively to software development in TDA, notably creating JavaPlex, and has co-authored foundational work on persistent homology, cohomology, and the Mapper algorithm. His research explores topological modeling of political data, motion capture, and biomedical applications, while advocating for mental health awareness in academia through initiatives like the Depressed Academics blog. His recent publications emphasize persistent cohomology, error classification in predictive models, and distributed algorithms for evasion problems. He mentors graduate students in computational topology, machine learning, and data science, and his artistic endeavors include mathematical art exhibitions at major conferences like the Bridges Mathematical Art Conference.

• Gastrointestinal Cancers
• Surgical Oncology
• Metabolomics
• +۷ مورد دیگر

Sajid A. Khan, MD is an Associate Professor of Surgery (Oncology) at Yale School of Medicine , where he serves as Chief of Hepato-Pancreato-Biliary & Mixed Tumors and Co-Director of Team Science at Yale Center for Clinical Investigation (YCCI). Board-certified in Complex General Surgical Oncology and General Surgery, he specializes in gastrointestinal cancers including liver, pancreas, and colorectal tumors, with a research focus on metabolomics and transcriptomics to understand metastasis mechanisms and develop biomarkers. MD from SUNY Upstate Medical University (2003) Residency at Oregon Health & Science University (2009) and Albert Einstein College of Medicine/Montefiore (2005) Research Fellowship at Memorial Sloan-Kettering Cancer Center (2007) and Clinical/Research Fellowship at University of Chicago Medical Center (2013) Current leadership roles in SSAT Research Committee and editorial boards His Khan Lab at Yale conducts translational research on liver metastasis , pancreatic cancer biomarkers , and genomic drivers of GI cancers, funded by NIH R01/R21 grants. Recent studies examine sex-specific metabolic responses in colorectal cancer and tumor microbiome interactions . He has published >100 papers and received multiple Castle Connolly Top Doctor awards (2023-2025) . Principal Investigator for SWOG national chemoprevention trial Co-Leader of Advanced Hepatobiliary Disease Program at Yale Cancer Center Advocate for multidisciplinary patient care using minimally invasive techniques

• Energy Systems Optimization
• Systems Engineering
• Robotics
• +۳ مورد دیگر

Professor Yoshiharu Amano is affiliated with the Faculty of Science and Engineering at Waseda University in the Department of Applied Mechanics and Aerospace Engineering . With a Doctor of Engineering degree from Waseda University, his research spans energy systems, robotics, and environmental engineering. Education: Ph.D. in Mechanical Engineering (Waseda University) Current Position: Full Professor at Waseda University His research interests include: Optimization of energy systems with renewable integration Development of autonomous mobile systems and UAVs GNSS signal processing and multipath mitigation 3D mapping for industrial and environmental applications Control Moment Gyro (CMG) technology for flight stability Standardization of industrial energy management systems (IEC 63376) Recent publications focus on: Macroeconomic modeling of distributed energy resources Geothermal system optimization using deep learning CO2 emission reduction through advanced district cooling systems High-precision 3D piping measurement methods Hydrogen production economics with hybrid energy sources GNSS reliability improvements in urban environments Scientific awards highlight his contributions to: Best energy systems research (ECOS 2015, IJPGC ASME) Thermal engineering excellence (JSME 2005, 2012) Robotics innovations (ROBOMECH Journal 2011) International recognition (SICE 2021)

Ann-Kathrin Lindahl Christiansenمشاهده پروفایل

پژوهشگر

• Obesity
• Weight Management
• Primary Care
• +۳ مورد دیگر

Ann-Kathrin Lindahl Christiansen serves as a Senior Consultant and Programme Coordinator for the LightCOM-project within the Research Unit for General Practice at the University of Copenhagen's Faculty of Health and Medical Sciences. Her work addresses obesity through multidisciplinary approaches across primary care, secondary care, and municipality-based healthcare settings, focusing on equitable intervention strategies and patient-centered outcomes. Her educational foundation includes: Master of Science in Molecular Medicine from Aarhus University (2011-2014) Bachelor of Science in Molecular Medicine from Aarhus University (2007-2011) Christiansen's research integrates obesity science, health inequality analysis, and primary care innovation using qualitative and mixed-methods frameworks. Current projects examine weight-loss medication experiences, bariatric surgery decision-making, and weight-neutral health interventions, with emphasis on socioeconomic factors and real-world implementation challenges in Danish healthcare systems. Recent publications (2024-2025) demonstrate a strategic shift toward obesity treatment modalities and multimorbidity care, moving from earlier neuroscience work (2017-2019) on astrocytic metabolism. Her studies consistently prioritize patient perspectives, healthcare economics, and adaptive intervention design within general practice contexts. As Programme Coordinator, Christiansen manages LightCOM project execution including stakeholder collaboration across healthcare sectors, budget oversight, timeline coordination, and outcome monitoring for obesity-focused work packages. She maintains active research partnerships through the KU-FEAP group and contributes to national health intervention protocols.

Naoki Hirataniمشاهده پروفایل

استادیار

• Neuro-AI
• Theoretical Neuroscience
• Computational Neuroscience
• +۳ مورد دیگر

Naoki Hiratani serves as Assistant Professor of Neuroscience in the Department of Neuroscience at Washington University in St. Louis School of Medicine. His research bridges theoretical neuroscience and artificial intelligence to decipher the brain's efficiency in learning and computation. Education PhD, The University of Tokyo (2011-2016) BS, The University of Tokyo (2007-2011) Research Focus : Dr. Hiratani pioneers Neuro-AI investigations into how micro/macro connectivity patterns and complex learning mechanisms enable the brain's superior energy efficiency and data-efficient learning compared to modern AI. His work employs advanced machine learning algorithms for neural data analysis, targeting brain-inspired AI development through theoretical modeling of sensory processing, olfactory systems, and neural circuit dynamics. Publication Trends : His 2015-2023 publications reveal consistent focus on biologically plausible learning (node perturbation, STDP), neural circuit modeling (olfaction, reservoir computing), and Bayesian neural computation . Recent work emphasizes individual variability analysis and task-order optimization for continual learning. Awards Swartz Foundation Postdoctoral Fellowship (2020-2023) Japan Science Promotion Society Doctoral Fellowship (2014-2016) Top Reviewer, ICML 2025 Mentorship & Lab : Leading the Hiratani Laboratory (Neuro-AI Research Lab), he actively recruits graduate students and postdocs. Current rotation students Jeeyoung and Liangyu contribute to projects including zebrafish brain development (with Goodhill Lab) and International Brain Laboratory data analysis. The lab recently accepted work on task-order optimization for ICML 2025.

David Moffatمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Environmental Science
• +۴ مورد دیگر

David Moffat serves as AI and Machine Learning Data Scientist at Plymouth Marine Laboratory, leading organization-wide AI initiatives to advance environmental and marine research through cutting-edge data science methodologies. His work bridges computer science expertise with critical ecological challenges, leveraging both traditional and modern AI techniques to extract insights from complex environmental datasets. His academic credentials include: BSc in Artificial Intelligence and Computer Science (University of Edinburgh) MSc in Signal Processing (Queen Mary University of London) PhD in Computer Science (Queen Mary University of London) Moffat's research centers on applied artificial intelligence with specialization in signal processing and time series analysis for environmental applications. He develops AI solutions for air-sea interaction studies, phytoplankton dynamics monitoring, invasive species mapping using drone technology, and audio processing systems. His methodological approach combines deep learning with domain-specific knowledge to create robust models for understanding complex natural systems under changing environmental conditions. Dr. Moffat actively secures research funding through major projects including NEODAAS, SCOPE DEAL, Marine Geospatial Foundation Models, and DEFRA-ASIP. These initiatives support collaborative research across environmental science domains and have enabled him to deliver specialized AI training to over 300 professionals. His leadership drives institutional capacity building in data science while maintaining strong connections to academic research through publications and conference contributions. At Plymouth Marine Laboratory, Moffat heads the AI research team that develops and implements machine learning frameworks across environmental monitoring programs. The team focuses on creating transferable AI models for marine applications, integrating satellite data with in-situ measurements, and developing practical tools for ecosystem management that balance scientific rigor with real-world usability.

Nicolas Chevalierمشاهده پروفایل

پژوهشگر

• Biophysics
• Physical Embryology
• Endometriosis
• +۷ مورد دیگر

Nicolas Chevalier is a CNRS Researcher at the Matière & Systèmes Complexes Laboratory, Paris Diderot University, specializing in biophysics, physical embryology, and endometriosis research. His work focuses on understanding the mechanical properties and developmental processes of the gastrointestinal system, particularly the enteric nervous system and intestinal motility. Dr. Chevalier's research interests span the intersection of physics and biology, with a focus on how mechanical forces shape embryonic development. His laboratory investigates the biomechanical properties of tissues, calcium wave dynamics in gut development, and the physical principles underlying peristalsis. His work has revealed that the enteric nervous system is unexpectedly rigid compared to brain tissue, with mechanical properties influenced by collagen structures. He has also discovered novel mechanisms of intestinal growth driven by mechanical tension and demonstrated how smooth muscle contractions shape the developing enteric nervous system. His publications reveal a consistent focus on the physical principles governing gut development and function. Analysis of his 15 most recent articles shows an evolution from basic mechanical measurements of embryonic tissues toward more complex investigations of neural-muscular interactions in the gut. Recent work emphasizes the mechanosensitive properties of smooth muscle and their implications for understanding endometriosis and other gastrointestinal disorders. His research demonstrates how physical forces interact with biological processes to shape organ development. Dr. Chevalier has successfully mentored at least one PhD student, Richard, who defended his thesis on 'Fundamentals of Intestinal Peristalsis: Myogenic, Neurogenic and Hydrodynamic Behavior' in January 2024. His research is supported by the Fondation pour la Recherche sur l'Endométriose (Foundation for Endometriosis Research), which funds investigations into uterine contractility and related mechanisms. Working within the Matière & Systèmes Complexes Laboratory, Dr. Chevalier collaborates extensively with researchers from the Jacques Monod Institute and IMRB of Créteil. His interdisciplinary approach bridges physics, developmental biology, and clinical medicine, with particular relevance to understanding gastrointestinal pathologies and potential therapeutic interventions.

• Acoustics
• Noise Measurement
• Microphone Array Technology
• +۵ مورد دیگر

Pieter Sijtsma serves as a Professor in the Department of Operations & Environment within Delft University of Technology's Faculty of Aerospace Engineering. His academic career spans over 15 years of specialized research in aeroacoustics, with significant contributions to microphone array technology and noise measurement methodologies. Current affiliations include active roles in the Berlin Beamforming Conference Committee and ongoing collaborations with major aerospace research entities. Professor Sijtsma's research focuses on advanced acoustic measurement techniques for aerospace applications. His work centers on beamforming algorithms , engine noise characterization , and wave propagation modeling in complex environments like wind tunnels and annular ducts. Key specialties include CLEAN-SC deconvolution methods for noise source mapping, directivity pattern analysis, and experimental validation of acoustic assessment techniques. His fingerprint reveals dominant expertise in acoustics (100%), noise measurement (97%), and microphone array technology (68%). Recent publication trends show concentrated activity in improving acoustic field assessment (2025), engine noise directivity determination (2024), and beamforming in swirling flows (2023). His work consistently addresses practical aerospace noise challenges through rigorous experimental validation and mathematical modeling, with strong emphasis on measurement accuracy and algorithmic innovation. Professor Sijtsma actively supervises research through collaborative projects, typically co-mentoring students with colleagues like Snellen and Avallone. His group maintains strong industry connections, evidenced by committee roles with the Ministry of Infrastructure and Environment and participation in international standard-setting conferences. Current projects involve EU-funded research on wind tunnel acoustic correction methods and engine noise source characterization. The research infrastructure leverages TU Delft's advanced wind tunnel facilities with specialized acoustic treatment and high-channel-count microphone arrays. Recent dataset releases confirm access to sophisticated wave propagation modeling tools and experimental validation platforms for closed-test-section environments.

• Analytical Marketing
• Natural Language Processing
• Marketing strategy
• +۵ مورد دیگر

Lavy Khoushinsky serves as Assistant Professor in the Marketing Department at Laval University's Faculty of Administrative Sciences, where he maintains an active research program bridging analytical marketing, artificial intelligence, and consumer behavior. His work addresses critical contemporary challenges including ideological polarization in markets, healthcare access barriers, and ethical AI implementation. His educational foundation includes a Ph.D. from Smith School of Business, Master's in Sustainable Energy Policy from Carleton University, and Bachelor's in Communication from Concordia University. This interdisciplinary background informs his research approach that integrates technical marketing analytics with social impact considerations. Professor Khoushinsky's research program demonstrates remarkable thematic evolution from sustainable transportation (2019) through banking experience innovation (2020-2021) to his current focus on AI-consumer interactions in contested spaces. His 14 publications (2019-2025) reveal three dominant trajectories: AI-Mediated Consumer Interactions (50% of recent work): Examining chatbots, healthcare navigation systems, and accountability frameworks Ideological Market Dynamics (30%): Analyzing niche marketing in polarized environments and consumer discourse patterns Technology Adoption Barriers (20%): Studying privacy paradoxes, e-waste responsibility, and mixed-reality banking experiences His methodological approach combines computational linguistics with experimental design to address complex marketing phenomena. Through his teaching portfolio spanning Marketing Principles to AI applications, Professor Khoushinsky prepares students for evolving marketing landscapes. His course development emphasizes practical analytical skills while addressing contemporary ethical challenges in digital marketing. The collaborative nature of his publication record (80% co-authored) indicates strong team-based research practices and interdisciplinary connections across institutions.

Sukriti Nagمشاهده پروفایل

استاد

• Neuropathology
• Alzheimer's Disease
• TDP-43 Encephalopathy
• +۵ مورد دیگر

Sukriti Nag, MD, PhD is a Professor in the Department of Pathology at Rush Medical College, Rush University. She serves as a Neuropathologist at the RUSH Alzheimer's Disease Center, with her primary location at the Department of Pathology, 1750 W Harrison St Suite 570, Chicago, IL, 60612. Dr. Nag's research focuses on neuropathology of aging, with particular emphasis on Alzheimer's disease, Lewy body pathology, TDP-43 encephalopathy (LATE), and the intersection of vascular pathology with neurodegenerative processes. Her work employs a range of techniques including neuropathological examination, PET imaging, and molecular analysis to understand the complex interactions between different proteinopathies in cognitive decline. Analysis of Dr. Nag's recent publications (2019-2021) reveals a strong focus on mixed neuropathologies in aging brains, particularly the co-occurrence of Alzheimer's disease pathology with Lewy bodies and TDP-43 encephalopathy. She has made significant contributions to understanding how these pathologies interact to produce cognitive impairment and dementia, with notable work on racial disparities in neuropathological findings and the clinical correlates of various brain pathologies. Dr. Nag maintains an active research program with numerous publications in high-impact journals including Acta Neuropathologica, Neurology, and Brain Pathology. Her work bridges basic neuropathological findings with clinical implications, contributing to our understanding of the complex etiology of cognitive decline in older adults.

Antonio Sanchez-Vazquezمشاهده پروفایل

پژوهشگر ارشد

• Healthcare Information Systems
• Human-Computer Interaction
• Computer Supported Cooperative Work
• +۵ مورد دیگر

Antonio Sanchez-Vazquez serves as a Research Fellow at Anglia Ruskin University's School of Management within the Faculty of Business and Law, Cambridge campus. His work bridges business management theory with healthcare technology implementation, focusing on complex organizational systems in public services. Educational background: PhD in Information Systems (University of Glamorgan) MSc in Software Engineering (University of Liverpool) BSc (Hons) in Genetics (University of Leeds) His research centers on technology adoption in healthcare through the lenses of Activity Theory and Systems Thinking. Key areas include Human-Computer Interaction (HCI), Computer Supported Cooperative Work (CSCW), and Healthcare Information Systems (HIS), with particular emphasis on organizational culture, emergency care workflows, and technology evaluation in NHS settings. He examines how innovations like clinical decision support systems impact multi-level organizational structures. Analysis of his 15-year publication history reveals consistent focus on technology-human-organization interactions in healthcare. Early work concentrated on wound care informatics (1999-2004), evolving into emergency care systems (2010-2014), and broader policy issues like digital inclusion (2015). His methodology combines qualitative organizational analysis with pragmatic clinical trials, demonstrating growing emphasis on socio-technical frameworks for technology implementation. Research supervision and grants: Currently supervising one PhD candidate researching mobile health apps for European medical staff Led Benefits Realization Management analysis for UK Police forces Contributed to National Institute for Health Research projects including the SAFER study He maintains active collaborations with NHS trusts through his membership in the Research Development and Innovation Group at Princess Alexandra Hospital, applying systems thinking to frontline healthcare challenges.