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مدرس ارشد
Dr. Natalie Enninghorst is a Senior Lecturer at the University of Newcastle, School of Medicine and Public Health, within the Faculty of Health and Medicine. She serves as the discipline representative for Year 5 MD and Deputy Convener of the Master of Traumatology, focusing on trauma research and surgical education at both postgraduate and undergraduate levels.
Dr. Sven Lautenbach is a Professor and Chief Scientist at the Institute of Geoinformatics, University of Heidelberg , affiliated with the HeiGIT research group. His work bridges geospatial analysis, environmental modeling, and public health, with a focus on urban systems and land-use decision-making. Current role: Chief Scientist at HeiGIT gGmbH Key affiliations: Department of Geoinformatics, University of Heidelberg Research Interests : Lautenbach's interdisciplinary research addresses: Trade-offs in land use decisions and ecosystem services Health geography and spatial epidemiology Application of machine learning and AI to urban geospatial data Open data quality assessment (OpenStreetMap, social media) Climate adaptation strategies for urban environments Vector-borne disease risk modeling Publication Trends : Recent work emphasizes: Geo-social media for pandemic early warning systems Deep learning for infrastructure mapping (e.g., road surfaces) Flood impact analysis on urban accessibility Heat stress mitigation in pedestrian routing Multi-modal urban human dynamics during crises Open data quality evaluation for humanitarian applications Project Leadership : Lautenbach directs initiatives including: myGreen: Urban green space analysis Climate Change and Spatial Epidemiology Summer School OPERAs/FP-7: Ecosystem science-policy integration CONNECT: Biodiversity-ecosystem service synergies
مدرس ارشد
Tony Boston is an Honorary Senior Lecturer at the Fenner School of Environment & Society at the Australian National University. With extensive expertise in geographic information systems, remote sensing, and machine learning applications for environmental data, he contributes significantly to earth science research and environmental monitoring initiatives across Australia. His educational background includes: PhD from the Australian National University (awarded November 8, 2024) Graduate Diploma in Computing Studies from the University of Canberra (awarded April 22, 1993) Bachelor of Science (Honors) from the Australian National University (awarded May 9, 1984) Tony's research focuses on the application of earth observations, in situ data, and AI foundation models for environmental monitoring and prediction. His work particularly emphasizes water resources management, land cover mapping, and environmental change detection through advanced machine learning techniques. He has developed expertise in integrating diverse data sources to create comprehensive environmental information systems that support evidence-based decision making in natural resource management, with a strong emphasis on developing national and international data standards. His recent publications demonstrate a consistent focus on applying convolutional neural networks and other machine learning approaches to environmental remote sensing data, particularly Landsat imagery. These works show an evolution from basic plant identification experiments to sophisticated land cover and vegetation mapping systems with practical applications for environmental monitoring across Australia. His research bridges the gap between theoretical machine learning advancements and practical environmental management needs, with increasing emphasis on temporal stability and accuracy in land cover classification. Tony has extensive professional experience, having served over 25 years in executive roles within the Australian Public Service, including positions at the Department of the Environment, National Library of Australia, and Bureau of Meteorology. At the Bureau of Meteorology, he was responsible for developing a national database of surface and groundwater information that underpins the Water Information Program established under Part 7 of the Water Act 2007. As co-chair of the WMO/OGC Hydrology Domain Working Group from 2013 to 2024, he made significant contributions to the development of WaterML2 international standards for hydrological data exchange.
Dr. C James Sung is a Professor of Pathology and Laboratory Medicine at Brown University . He specializes in gynecological pathology , breast pathology , and cytopathology , with a focus on tumor pathology and diagnostic applications like the Pap smear . Research Highlights: Investigates HPV-related lesions and gynecological cancers . Explores histological grading and molecular markers in breast and endometrial cancers. Contributes to cytology testing standards and diagnostic accuracy studies. Recent Publications analyze trends in K-ras mutations , mucinous differentiation , and HPV testing across various female cancers, emphasizing tumor biology and diagnostic innovation. Teaching Initiatives include a Chinese Medical Elective for medical students, focusing on Mandarin language skills for clinical communication with Chinese-speaking patients.
Michael S. Torbenson, M.D. is a Professor of Laboratory Medicine and Pathology at Mayo Clinic in Rochester, Minnesota. He serves as a Consultant in the Division of Anatomic Pathology within the Department of Laboratory Medicine and Pathology, focusing his expertise on liver and biliary pathologies with over 250 peer-reviewed publications. Dr. Torbenson's educational background includes: MD from University of Chicago (1995) BS from University of Minnesota Duluth (1991) Fellowship in GI Pathology at The Johns Hopkins Hospital (2001) Fellowship in Liver/Transplant at University of Pittsburgh Medical Center (2000) Residency in Pathology at University of Pittsburgh Medical Center (1999) His laboratory pioneered the discovery of CpG islands in the hepatitis B virus genome and demonstrated viral gene regulation through DNA methylation. Dr. Torbenson has authored five books on liver pathology including comprehensive texts on liver biopsy interpretation and liver tumors, and contributed to the WHO Blue Books on gastrointestinal and liver tumors. His research spans molecular characterization of liver tumors, viral hepatitis mechanisms, and clinicopathological correlations essential for precision medicine approaches. Analysis of Dr. Torbenson's publication record shows consistent contributions to hepatobiliary pathology with increasing emphasis on molecular diagnostics, non-invasive assessment techniques, and translational applications. His work bridges traditional histopathology with genomic and imaging modalities to improve diagnostic accuracy and therapeutic targeting for liver diseases. Dr. Torbenson has received significant professional recognition: President of the Roger C. Haggit Gastrointestinal Pathology Society (2019-2020) President of the Hans Popper Hepatopathology Society (2016-2018) Member of the United States and Canadian Academy of Pathology (2013-present) Active participation in the Gnomes Society (2011-present) and Laennec Society (2007-present) Dr. Torbenson leads major National Cancer Institute-funded initiatives including the Mayo Clinic Hepatobiliary SPORE project (2018-2025) as Co-PI, and previously directed the Fibrolamellar HCC project and Biospecimen and Pathology Core. His research program maintains extensive tissue biospecimen collections that support multiple collaborative projects investigating hepatobiliary cancer mechanisms and diagnostic markers. Through his leadership in anatomic pathology, Dr. Torbenson oversees a multidisciplinary research team that integrates histopathological analysis with molecular techniques to advance understanding of liver diseases. His work directly impacts clinical practice through improved diagnostic criteria and classification systems used worldwide.
Jeffrey P. Weiss is Professor and Chair of the Department of Urology at SUNY Downstate Health Sciences University, with over 15 years in this role. He specializes in Neuro-Urology and Urodynamics , focusing on nocturia and its clinical implications. Dr. Weiss also serves as Staff Urologist at Veterans Affairs NY Harbor Healthcare System. PhD in Health Sciences (2020), Ghent University MD (1978), University of Pittsburgh School of Medicine AB in Biochemistry/History of Art (1974), Cornell University His research explores nocturia's etiology in diverse contexts including benign prostatic enlargement , nocturnal polyuria syndrome , and hypertension . Recent work addresses diuretic therapy , urinary symptom analysis , and population-specific treatment paradigms . Publications reflect trends in urodynamic diagnostics and nocturia management , emphasizing clinical trials and disease classification . Awards include FACS (Fellow of the American College of Surgeons). Dr. Weiss has shaped urology education, mentoring medical students and residents nationally.
Albin Gustav Sandelin is a Professor in the Department of Biology at the University of Copenhagen, specializing in bioinformatics and RNA biology. With a PhD in Functional Genomics from Karolinska Institute (2004) and an MSc in Molecular Biology from Stockholm University (2000), his career spans roles at institutions including RIKEN Yokohama Institute and Tokyo Medical and Dental University. His research focuses on Gene regulation mechanisms Transcription start site dynamics RNA sequencing methodologies Promoter architecture analysis Cancer microenvironment interactions . Recent publications highlight his work in pancreatic cancer adaptation to acidic environments (2024-2025), TLDR-seq for RNA analysis, and JASPAR database development. He supervises PhD students including Eivind Valen and Eric Man-Hung, with a history of teaching bioinformatics courses at Karolinska Institute and Copenhagen University. Key collaborations involve institutions in Japan, Canada, and Sweden, with ongoing contributions to open-access genomic resources like JASPAR.
Ilian Bonev is a Professor in the Department of Systems Engineering at École de technologie supérieure (ETS) in Montreal, Canada. He holds a B.Eng. from Technical University of Sofia, Bulgaria, an M.Sc. from Gwangju Institute of Science and Technology (GIST), South Korea, and a Ph.D. from Université Laval. He leads the Control and Robotics Laboratory (CoRo) at ETS, focusing on precision robotics, industrial robotics, and parallel robot design. His research interests include: Industrial robotics and automation Robot calibration Precision robotics Parallel robot design Analysis of robot singularities Intelligent and autonomous systems Innovative materials and advanced manufacturing Prof. Bonev's recent publications demonstrate a strong focus on robot calibration techniques, precision machining with industrial robots, and analysis of collaborative robot systems. His work often involves developing novel calibration methods using various metrology equipment like laser trackers, ballbars, and photogrammetry systems. He has made significant contributions to understanding robot singularities and improving the accuracy of industrial robots for applications in aerospace and medical fields. His notable awards include: 2012: CA Excellence Award for Emerging Researcher from École de technologie supérieure 2009-2019: Canada Research Chair (Tier 2) in Precision Robotics Prof. Bonev has supervised numerous graduate students through doctoral theses, dissertations, and various research projects. His laboratory, CoRo, is equipped with state-of-the-art equipment including industrial robots and a full range of metrology equipment such as FARO laser tracker, FARO arm, Renishaw ballbar, and Renishaw interferometry system. The CoRo laboratory focuses on applied research in collaboration with industry, with major projects in robot calibration, parallel robotics, robotic machining, and redundant robots. Prof. Bonev has developed several innovative robot calibration methods that have been implemented in industry at companies like Messier-Dowty and GE Aviation.
پژوهشگر
Marcel Aach is a researcher at the Jülich Supercomputing Centre (JSC) within Research Centre Jülich, focusing on high-performance computing (HPC) and artificial intelligence (AI) integration. His work spans hyperparameter optimization, quantum-classical hybrid systems, and scalable deep learning architectures. Research Focus: AI-driven CFD simulations, medical imaging analysis, and edge AI optimization Infrastructure: Leverages JSC's HPC systems for large-scale computational tasks Recent publications highlight his contributions to resource-adaptive AI training, turbulent flow prediction using GRU models, and enhancing CT data accuracy for respiratory simulations. His work intersects HPC scalability, machine learning efficiency, and interdisciplinary applications. While no scientific awards are explicitly documented in the provided texts, his research demonstrates technical leadership in merging classical and quantum computing paradigms for AI optimization.
Lindsay Frazier serves as an Attending Physician at Dana-Farber/Boston Children's Cancer and Blood Disorders Center, holding dual academic appointments as Associate Professor of Epidemiology at Harvard T.H. Chan School of Public Health and Professor of Pediatrics at Harvard Medical School. Her clinical focus centers on pediatric germ cell tumors with extensive involvement in clinical trials, biology, and epidemiology research. Dr. Frazier completed her medical education at Dartmouth Medical School (1984), pediatrics training at Boston Children's Hospital (1985-1989), and earned a graduate degree from Harvard School of Public Health (1993). She is board certified in Pediatric Hematology-Oncology. Her research program spans germ cell tumor epidemiology, international clinical trial design, and translational studies. She leads the Malignant Germ Cell International Collaboration (MaGIC), which has merged clinical trial data from 25 years across multiple countries to develop comprehensive risk classification systems. Her epidemiology expertise informs cohort studies including the Growing Up Today Study involving 27,000 participants. Analysis of her recent publications reveals strong emphasis on international collaboration in germ cell tumor research, risk stratification refinement, biomarker development (particularly miR-371a-3p), and addressing disparities in adolescent and young adult oncology. Her work spans basic science through clinical application with significant contributions to treatment de-escalation strategies and surveillance protocols. Dr. Frazier has chaired multiple Children's Oncology Group protocols including leadership of the germ cell tumor committee since 2007. She co-founded MaGIC to integrate international data and currently serves as editor for a Springer book on Pediatric Germ Cell Tumors. Her clinical work focuses on optimizing care for patients with germ cell tumors while minimizing long-term treatment effects. She directs translational research efforts linking clinical data with banked biological specimens through MaGIC, collaborating with researchers like Dr. Amatruda on genomic analyses of germ cell tumors. Her work bridges epidemiology, clinical oncology, and molecular biology to advance understanding of germ cell tumor pathogenesis and treatment.
Ivan Kolev Koichev is a Professor at the Department of Software Technologies within the Faculty of Mathematics and Informatics at Sofia University 'St Kliment Ohridski'. He serves as the Director of the MSc program in Information Retrieval and Knowledge Discovery and Head of the Department of Software Technologies Education. His research spans Artificial Intelligence, Machine Learning, Natural Language Processing, and Information Retrieval. MSc in Applied Mathematics (1988), Sofia University PhD in Computer Science (1998), Bulgarian Academy of Sciences Postdoc Fellowships at GMD Germany (1999-2002) and Robert Gordon University UK (2002-2005) His work focuses on adaptive learning systems, fact-checking, author obfuscation, and community question-answering frameworks. Key publications address concept drift adaptation, political debate analysis, image claim verification, and credible news detection. He collaborates extensively with researchers like Preslav Nakov and Momchil Hardalov. He has contributed to SemEval-2016 Task 3 and developed the LEAF multiple-choice question generation system. His research integrates linguistic analysis, credibility assessment, and algorithmic innovation across multidisciplinary domains.
Edward Golob is a Professor of Psychology in the College for Health, Community and Policy at the University of Texas at San Antonio (UTSA), where his research bridges cognitive psychology with critical healthcare and military applications. His work focuses on spatial cognition, attention mechanisms, and perceptual processes in both healthy and neurologically impaired populations. His academic foundation includes: Postdoctoral Fellow, University of California, Irvine Ph.D. in Experimental Psychology, Dartmouth College B.A. in Psychology, Capital University Dr. Golob's research program investigates spatial hearing in 360° environments , attentional modulation under sensory constraints , and cognitive mechanisms in medical diagnostics . His recent work demonstrates how hearing protection devices impair military personnel's spatial awareness and how targeted training can mitigate these deficits. In radiology, he pioneers eye-tracking methodologies to quantify expertise and reduce diagnostic errors. His studies on auditory attention reveal fundamental asymmetries between front and back spatial processing, while his work on listening effort identifies distinct fatigue and mood dimensions that impact communication. Analysis of his 2023-2025 publications shows a consistent pattern of translational cognitive science - taking laboratory findings into real-world settings like radiology suites and military operations. His research integrates machine learning with psychophysical methods to develop objective assessment tools, particularly in visual search optimization and spatial hearing rehabilitation. The cross-cutting theme is enhancing human performance through cognitive training and technology-assisted feedback. His professional recognition includes: Psychonomic Society Fellow (2017) While specific grant details and current advisees aren't documented in the source material, his active publication record in high-impact journals like Military Medicine and the Journal of the American College of Radiology indicates ongoing research leadership. His work directly addresses compliance barriers in hearing protection and diagnostic accuracy challenges in medical imaging through empirically validated interventions.
Kristen Mariko Meiburger is an Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. She is a member of the PolitoBIOMed Lab , focusing on biomedical engineering research. Research Interests: Medical image processing, photoacoustic imaging, ultrasound technologies, and AI-driven diagnostic systems. Her work bridges industrial and information engineering with clinical applications. Recent Publications highlight advancements in photoacoustic uncertainty quantification, high-frequency vascular imaging, machine learning for muscular dystrophy analysis, and optoacoustic/ultrasound reconstruction techniques. Scientific Awards: Premio di Laurea GNB (2011) Premio di Qualità (2014) Key Projects: ImPACT-AI (2023-2025) AI-VASCUES (2023-2025) REAP (2021-2024) H2020-ICT (EU-funded) PhD Students: Bruna Cotrufo, Alen Shahini, Federico Sinnona, Matteo Salvi, Giulia Rotunno, Francesco Branciforti, Francesco Marzola.
Mojtaba Naghdyzadegan Jahromi is a postdoctoral researcher at the University of Oulu in the Hydrosystems Engineering & Management (HEM) research group within the Water, Energy, and Environmental Engineering Research Unit . He holds a Ph.D. in Agriculture-Water Engineering from Shiraz University (2023) and has previously worked at Shiraz University, Ghent University, and Georg-August University of Göttingen. B.Sc. and M.Sc. in Water Engineering , Shiraz University Ph.D. in Agriculture-Water Engineering , Shiraz University His research focuses on crop modeling , remote sensing , and machine learning for agricultural and environmental applications. Recent work includes wheat yield prediction , inland water body depletion analysis , and precision agriculture techniques. Publications span journals like European Journal of Agronomy and Water , book chapters on remote sensing and machine learning, and conferences including EGU and Tropentag. Ph.D. Student Travel Grant (2021), Ministry of Science, Iran Student Travel Grant (2017), ICTP, Italy Tropentag 2015 Grant Award He has contributed to interdisciplinary projects involving Google Earth Engine , MODIS data , and GLEAM evapotranspiration models , with applications in water resource management and climate change impact assessment.
Dr. Muhammed Akif YENİKAYA is an Assistant Professor (Dr. Öğretim Üyesi) at Kafkas University's Faculty of Economics and Administrative Sciences, Department of Management Information Systems. Since 2020, he has held roles including Research Assistant (2020-present), Assistant Director of the Research and Application Center (2022-2024), and Director of the Research and Application Center (2024-present). He advises the Kafkas University Techno Informatics Club. Education PhD in Computer Engineering, Maltepe University (2019-2022) MSc in Computer Engineering, İzmir University of Economics (2016-2018) MSc in Occupational Health and Safety, Kafkas University (2024) Bachelor's in Management Information Systems, Anadolu University (2019-2022) Bachelor's in Western Languages and Literatures, Kafkas University (2022) Associate Degree in Graphic Design, Istanbul University (2022) Research Focus Yenikaya's research integrates artificial intelligence with practical applications across healthcare, agriculture, energy, and management. His work emphasizes deep learning models for medical diagnostics (e.g., retinal and X-ray analysis), sustainable agriculture via IoT-based hydroponic systems, and AI-driven waste management. He also explores organizational digital transformation, technology adoption, and digital leadership strategies in business contexts. Publications Overview His 24 publications demonstrate a strong focus on AI/ML applications in healthcare (e.g., diabetic retinopathy detection, skin cancer diagnosis), sustainable technology (hydroponics, energy efficiency), and digital leadership. Recent work shows increased emphasis on convolutional neural networks and cross-disciplinary solutions for environmental and industrial challenges. Awards and Grants UBYT-2024 Award from TÜBİTAK (2024) Project: Hydroponic Home Agricultural Production System (2023-2025, Project Lead) Project: Digital Content and AR Applications for Climate Change Education (2024, Trainer) Teaching and Advising Teaches courses including Artificial Intelligence , Database Systems , and Mobile Programming at undergraduate/graduate levels. Advises MSc student Rafet Doğrukartal on a QR-code-based inventory management system (2025).
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