جست‌وجوی استاد و پژوهشگر

• Surgical Education
• Trauma Surgery
• Surgical Critical Care
• +۴ مورد دیگر

Kristin Oliveira, MD, is an Assistant Professor in the Department of Surgery at Yale University School of Medicine, specializing in General Surgery, Trauma, and Surgical Critical Care. She serves as Program Director for the General Surgery Residency Program following her role as Associate Program Director. Dr. Oliveira completed her medical degree at the University of Texas Southwestern Medical School (2008) and a Surgical Critical Care Fellowship at Yale (2016). Her research focuses on surgical education, including resident training and end-of-life communication. She has published extensively on topics like surgical resident financial well-being, nonoperative appendicitis management, and critical care epidemiology. Dr. Oliveira actively participates in committees such as the Quality and Safety Committee of the Surgical Intensive Care Unit and the Graduate Medical Education Committee. She received the prestigious C. Elton Cahow Teaching Award in 2020. Clinically, she provides care at Yale New Haven Hospital’s Surgical Intensive Care Unit and Chapel Street campus, prioritizing care for underserved populations.

Kshitij Sabnisمشاهده پروفایل

مدرس

• Experimental Aerodynamics
• High-Speed Aerodynamics
• Vehicle Aerodynamics
• +۷ مورد دیگر

Kshitij Sabnis is a Lecturer in Aerospace Engineering at the School of Engineering and Materials Science, Queen Mary University of London. He serves as Admissions Lead and Outreach & Recruitment Lead for Aerospace Engineering, and Deputy Director of Industrial Engagement (Graduate Attributes). He is affiliated with the Centre for Intelligent Transport and conducts experimental research in high-speed aerodynamics. Education: PhD in Experimental Aerodynamics, University of Cambridge Master’s in Physics Dr Sabnis's research focuses on experimental aerodynamics across various speed regimes, particularly shock/boundary-layer interactions, vortex dynamics, and supersonic flows. His work involves wind tunnel experiments on simplified models to understand complex fluid mechanics in applications ranging from racecar wings to supersonic aircraft intakes. He employs advanced diagnostics and develops novel experimental setups to enhance physical insight into flow phenomena. His recent publications (2019–2025) reflect a strong emphasis on high-speed flow behavior, including shock-induced separation, vortex interactions, and nacelle aerodynamics. Key themes include flow control, wind tunnel design, and validation of turbulence models. His work bridges fundamental fluid dynamics with practical aerospace engineering challenges. Scientific Awards: FHEA (Fellow of the Higher Education Academy) Dr Sabnis actively supervises PhD students and leads externally funded research projects. He has secured grants from EPSRC and the Royal Society, supporting work on schlieren imaging enhancement and small-scale wind turbines for rural energy. He teaches advanced aerodynamics modules and contributes to curriculum and industrial engagement. He leads a research group focused on experimental high-speed aerodynamics and is involved in developing new diagnostic techniques and test rigs. His team investigates vortex interactions and aerodynamic performance under extreme flow conditions.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Maciej Zięba is an academic researcher affiliated with the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, specifically within the Department of Artificial Intelligence . His work spans machine learning, deep learning, and computer vision, with a focus on hyperspectral imaging, autonomous systems, and 3D modeling. Recent research includes uncertainty-aware sensor deployment for autonomous vehicles, low-light image enhancement algorithms, and probabilistic regression frameworks for tabular data. He has co-authored publications on flow-based models, hypernetworks, and neural radiance fields (NeRF) applied to 3D face rendering. Contact: maciej.zieba@pwr.edu.pl

Guofeng Caoمشاهده پروفایل

دانشیار

• GIScience
• GeoAI
• Geostatistics
• +۱۰ مورد دیگر

Guofeng Cao is an Associate Professor in the Department of Geography at the University of Colorado . His research integrates GIScience , GeoAI , geostatistics , and remote sensing to develop advanced methodologies for analyzing heterogeneous geospatial data and modeling complex spatiotemporal patterns. Focus areas: Uncertainty-aware geographic knowledge discovery, land cover/land use dynamics, spatiotemporal bias analysis, geospatial cyberinfrastructure development Applications: Natural hazards, environmental science, public health, global change studies Recent publications emphasize generative adversarial networks for climate downscaling, neural processes for uncertainty modeling, and fusion transformers for disaster assessment. His work combines deep learning with Bayesian inference to address scalability challenges in geospatial data processing. Scientific Recognition : NASA and USDA grants for spatiotemporal research Advising : Mentoring graduate students in geospatial data science Laboratory : Leads the STAR lab (Spatiotemporal Pattern Analysis & Research)

Kate Farrahiمشاهده پروفایل

دانشیار

• Machine Learning
• Digital Health
• Human Sensing
• +۳ مورد دیگر

Dr. Kate Farrahi is an Associate Professor in the ECS department at the University of Southampton, where she leads research in the Vision, Learning and Control (VLC) Group. Previously, she was a Research Assistant at the Idiap Research Institute and earned her PhD in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL). Her work focuses on the intersection of machine learning and digital health, particularly in developing human sensing methods using vision and wearable technologies. She currently supervises four PhD students in Computer Science and actively accepts new PhD applications. Her research interests span machine learning applications in healthcare, including wearable device analytics, epidemiological modeling via AI, and drug discovery through generative methods. She has been recognized with a Best Paper Award (2022) and contributes to interdisciplinary research groups such as the Institute for Life Sciences and Centre for Machine Intelligence. Her work bridges computational methods with real-world health challenges, emphasizing practical deployment of AI solutions in clinical and public health contexts. Research Groups: Vision, Learning and Control; Institute for Life Sciences; Centre for Health Technologies; Centre for Machine Intelligence Key Collaborations: Cross-disciplinary projects combining computer science with biomedical engineering and public health

• Seismology
• Geophysics
• Antarctic Ice Sheet Dynamics
• +۳ مورد دیگر

Dr. Thanh-Son Pham is an ARC DECRA Research Fellow in the Geophysics Department at The Australian National University’s Research School of Earth Sciences. His research focuses on using seismic waves to study Earth’s interior structures, from polar ice sheets to the inner core. He has pioneered methods like teleseismic P-wave coda autocorrelation and coda correlation wavefield analysis, leading to breakthroughs such as detecting J-waves in the inner core and identifying an innermost inner core layer. His work has been featured in Science , Nature Communications , and international media. He holds a PhD from ANU (2019) and has supervised research projects on Antarctic seismology and earthquake source physics. Awards include the 2024 Zatman lectureship from SEDI. Current projects include probing Antarctic ice sheets via correlation seismology and advancing machine learning tools for deep Earth studies. Education: PhD in Geophysics (ANU, 2019), Graduate Diploma in Earth System Physics (ICTP, 2015), BSc in Applied Mathematics (Hanoi University, 2013) Research interests span seismic source inversion, Antarctic ice dynamics, and inner core anisotropy. His 2024 articles address Hunga Tonga eruption mechanics and PKIKP wave analysis using deep learning. Media highlights include BBC, NYT, and ANU press releases.

Senthil Murugan Ganapathyمشاهده پروفایل

استاد

• Integrated Photonic Devices
• Point-of-Care Diagnostics
• Lab-on-a-Chip
• +۷ مورد دیگر

Professor Senthil Murugan Ganapathy is a Professor at the Optoelectronics Research Centre (ORC) at the University of Southampton, where he serves as Head of the Integrated Photonic Devices Group and Deputy Head of School (ORC) - Education. He also holds an Adjunct Professor position at the Indian Institute of Technology - Madras, Chennai, India. His research focuses on integrated photonic devices for biomedical and environmental applications, with particular expertise in Mid-IR materials and devices for point-of-care diagnostics. Professor Ganapathy received his Ph.D. in Photonic Materials in 2001 from the Indian Institute of Science, Bangalore. Following his doctorate, he completed post-doctoral fellowships at the University of Bordeaux, France (2001-2005) and Toyota Technological Institute, Japan (2001-2005) before joining the University of Southampton in April 2005. His research spans photonic materials to photonic systems, with current focus on Mid-IR/high-contrast materials and devices for biomedical sensing , on-chip spectroscopy , on-chip nanoscopy , environmental monitoring , and optical communication applications . He has made pioneering contributions in the field of novel optical microresonators and established a major Mid-IR characterization facility worth approximately £1M, which is unique for waveguide spectroscopy in the 2-13 μm spectral region. Recent publications demonstrate a strong trend toward biomedical applications of photonics, particularly in point-of-care diagnostics for conditions like neonatal respiratory distress syndrome. His work increasingly integrates photonics with data science approaches to enhance diagnostic capabilities, with multiple publications on liposome analysis, biomarker detection, and on-chip spectroscopy systems. Notable recognitions include: Dean's Award for 2012/2013 for "Outstanding Contributions in Teaching" for MSc (Photonic Technologies) Fellow of The Higher Education Academy of the UK Professor Ganapathy actively mentors the next generation of photonics researchers, currently supervising six PhD students. He has secured over £8 million in research funding as Principal Investigator and Co-Investigator, supporting projects including "MISSION (Mid-Infrared Silicon Photonic Sensors for Healthcare and Environmental Monitoring)" funded by EPSRC. His research group includes Dr. Aneesh Vincent Veluthandath and Dr. Waseem Ahmed, working collaboratively on cutting-edge photonic device development. He leads the Integrated Photonic Devices Group at the ORC, which operates the major Mid-IR characterization facility and has developed rapid bedside tests for diagnosing neonatal respiratory distress syndrome in premature babies, as featured in news outlets like News Medical and The Engineer.

Rosalyn Moranمشاهده پروفایل

استاد

• Computational Neuroscience
• Computational Psychiatry
• Neurodegenerative Diseases
• +۵ مورد دیگر

Professor Rosalyn Moran is a Professor of Computational Neuroscience and Deputy Director of King's Institute for Artificial Intelligence at King's College London. She holds roles in the Department of Neuroimaging and School of Neuroscience within the Institute of Psychiatry, Psychology & Neuroscience. Her research focuses on computational neuroscience, computational psychiatry, and neurology, particularly integrating brain connectivity with algorithmic principles like the free energy principle. She explores neurotransmitter roles in decision-making and disease modeling, with applications in artificial intelligence and neurodegenerative disorders. Moran serves as an editor for Neuroimage and collaborates with leading institutions. Key projects include global neuroimaging initiatives (UNITY) and low-field MRI advancements in low-resource settings. Her work bridges Bayesian inference, AI, and neurobiology, with recent emphasis on pediatric neuroimaging and treatment-resistant psychosis. Education & Research Interests Rosalyn Moran's research spans computational psychiatry, neuroimaging techniques, and AI applications in healthcare. Her lab investigates serotonin and dopamine signaling, brain connectivity patterns, and predictive coding frameworks. Notable contributions include modeling NMDA receptor dysfunction in encephalitis and developing super-resolution MRI methods for global health contexts. Grants & Collaborations Funded projects include MRC Human Functional Genomics (2024-2028), NIHR Maudsley BRC (2022-2027), and Gates Foundation initiatives for low-field MRI enhancement. Collaborators include Karl Friston (UCL), Read Montague (Virginia Tech), and Klaas Enno Stephan (University of Zurich). Recent events include presenting the Free Energy Principle's role in generative AI (May 2023). Labs & Teams Her lab focuses on computational psychiatry and AI-driven neuroimaging solutions, collaborating with the King’s Global Health Institute to advance medical imaging accessibility in low-income regions.

Shiri Azenkotمشاهده پروفایل

دانشیار

• Accessibility
• Human-Computer Interaction
• Assistive Technology
• +۴ مورد دیگر

Shiri Azenkot is an Associate Professor of Information Science at the Jacobs Technion-Cornell Institute, Cornell Tech, Cornell University, where she directs the Enhancing Ability Lab. She also serves as an affiliate faculty member in the Computer Science Department at the Technion--Israel Institute of Technology. Her research leverages artificial intelligence to design enabling systems that promote equity and improve quality of life for marginalized populations, with a current focus on visual impairments. Her educational background includes a PhD in Computer Science & Engineering from the University of Washington, advised by Richard Ladner and Jacob Wobbrock. Azenkot's research centers on intelligent interactive systems that enhance perception and ability for people with disabilities. She investigates perceptual abilities and behaviors to design novel systems for navigation, STEM learning, and socialization. Her work spans accessibility, human-computer interaction, and the application of AI/XR technologies to create inclusive solutions for blind and low-vision populations, addressing critical gaps in assistive technology. Recent publications reveal strong trends in developing real-time AI-powered assistive tools for low-vision users, accessible STEM education through tactile interfaces, and examining social dynamics of disability in digital spaces. Her work bridges technical innovation with deep user-centered design, particularly in XR accessibility through co-founded initiatives like XR Access. Scientific awards include: NSF CAREER Award NSF CRII Award 10-year Impact Award at MobileHCI Google Faculty Award Azenkot has advised students including Yuhang Zhao (now Assistant Professor at University of Wisconsin-Madison), Lei, and Danielle. Her research is funded by NSF, AOL, Verizon, and Facebook. She co-founded XR Access and leads the Enhancing Ability Lab, which conducts user studies and develops systems like Markit/Talkit and Livefonts. Current projects include XR accessibility REU programs and symposiums advancing industry-academia collaboration. She directs the Enhancing Ability Lab at Cornell Tech and co-leads XR Access, driving community initiatives to make augmented/virtual reality accessible while mentoring the next generation of accessibility researchers through funded REU programs and industry partnerships.

• Plant Developmental Biology
• Epigenetics
• Plant Genetics
• +۵ مورد دیگر

Ueli Grossniklaus is an Ordinary Professor at the University of Zurich within the Faculty of Mathematical and Natural Sciences , affiliated with the Department of Plant and Microbiology . His work focuses on plant developmental biology, particularly epigenetic and genetic mechanisms governing reproduction and adaptation. Key Courses: Epigenetics, Plant Biology Workshop, Group Seminars on Current Research Laboratory Techniques: Advanced methods in plant cell mechanics, transcriptomics, and genome editing Research Interests span plant epigenetics, reproductive biology, and the interplay between environmental stress and genetic regulation. He investigates: Mechanistic control of gametogenesis and fertilization Epigenetic contributions to plant adaptation Evolutionary implications of asexual reproduction Biophysical forces in plant cell growth Publication Trends (2025–2018) reveal expertise in: Arabidopsis and fern model systems Epigenetic regulation (DNA methylation, histone dynamics) Apomixis and hybrid seed failure mechanisms Biomechanics of pollen tubes and carnivorous plants Genome editing tools (CRISPR) and long-read sequencing Scientific Collaborations include interdisciplinary projects on: Microfluidic devices for plant cell analysis Gene drive ecology and ethics 3D imaging of plant reproductive structures Advising and Grants focus on mentoring through research internships in developmental biology, genetics, and systems biology. His lab engages in: Epigenetic response to environmental stress Cell wall mechanics in reproduction Computational modeling of plant growth Laboratory Teams integrate plant biologists, bioengineers, and computational scientists to study: Mechanistic gene regulation Evolutionary developmental biology Microrobotics for cellular force measurement

Zheshen Zhangمشاهده پروفایل

استاد

• Quantum Engineering
• Quantum Computing
• Quantum Communication
• +۴ مورد دیگر

Prof. Zheshen Zhang is a Professor in the Department of Electrical and Computer Engineering at the University of Michigan College of Engineering . He leads the Quantum Engineering Lab , focusing on harnessing quantum mechanical resources like entanglement to advance sensing, communication, and computing systems. Academic Rank: Professor Institution: University of Michigan School: College of Engineering Department: Electrical and Computer Engineering Research Interests: His work spans quantum engineering, emphasizing: Quantum computing architectures using continuous-variable cluster states Quantum communication via entanglement-assisted protocols Quantum sensing for precision metrology and dark matter detection Hybrid photonic circuits with Scandium Aluminum Nitride and Silicon Nitride Application of machine learning to quantum information processing Publications Trends: Recent articles highlight: Advances in integrated photonics for scalable quantum devices Development of entanglement-enhanced sensors for covert and precision applications Exploration of exceptional points in optical cavities for metrology Quantum network prototypes enabling open-access quantum computing Machine learning integration with quantum data acquisition

Saud Alhusainiمشاهده پروفایل

استادیار

• Neurology
• Movement Disorders
• Parkinson's Disease
• +۴ مورد دیگر

Saud Alhusaini MD PhD is an Assistant Professor of Neurology at the Warren Alpert Medical School of Brown University and serves as a Neurologist/Movement Disorders Specialist at Rhode Island Hospital. His research integrates imaging genomics and multimodal brain imaging approaches to investigate neurological disorders including Parkinson's disease, essential tremor, and epilepsy. He is affiliated with the Carney Institute for Brain Science and collaborates extensively with clinicians, geneticists, electrophysiologists, MRI specialists, neuropsychologists, and data scientists. Education: PhD from the Royal College of Surgeons in Ireland (RCSI) MSc in Neuroscience from Trinity College Dublin MD from University of Dublin, School of Medicine Adult neurology residency at McGill University/Montreal Neurological Institute Clinical research fellowship at Yale School of Medicine Clinical fellowship at Stanford University Medical Center Dr. Alhusaini's research focuses on identifying key endophenotypes and subclinical biomarkers to elucidate the underlying mechanisms of complex neurological conditions. His work spans multiple areas including movement disorders, epilepsy, and brain structure genetics. He has made significant contributions to understanding the genetic architecture of brain structures through his involvement with the ENIGMA consortium, which conducts large-scale collaborative analyses of neuroimaging and genetic data across institutions worldwide. An analysis of his publication record reveals a consistent pattern of high-impact research at the intersection of neurology, genetics, and advanced imaging techniques. His recent work demonstrates particular expertise in Parkinson's disease genetics, epilepsy network analysis, and movement disorder diagnostics. The breadth of his research, spanning from basic genetic mechanisms to clinical applications, highlights his comprehensive approach to understanding neurological disorders. Dr. Alhusaini has received funding from the Rhode Island Research Foundation, Brown Physicians, Inc., and Advance RI-CTR to support his research initiatives. His collaborative approach is evident through his numerous multi-institutional projects and extensive co-author network across Brown University departments including Neurology, Neurosurgery, and Pathology and Laboratory Medicine.

Tiffany Hoمشاهده پروفایل

استادیار

• Cognitive Neuroscience
• Adolescent Neurodevelopment
• Depression
• +۵ مورد دیگر

Dr. Tiffany Ho is an Assistant Professor in the Department of Psychology at the University of California, Los Angeles (UCLA). She is also affiliated with the Cognition, Affect, and Neurodevelopment in Youth (CANDY) lab, where she leads research on adolescent neurodevelopment, depression, and the neurobiological impacts of early adversity. Her work integrates neuroimaging, psychophysiology, and immunology to understand how stress and adversity shape brain circuits underlying emotion and behavior during adolescence. Education: Ph.D. in Psychology, University of California, San Diego B.A. in Cognitive Science, University of California, Berkeley Postdoctoral Fellowship in Clinical Neuroscience, University of California, San Francisco Postdoctoral Training in Affective Science, Stanford University Research Interests: Dr. Ho’s research focuses on understanding how brain circuits underlying thoughts, emotions, and behaviors change during adolescent development. She investigates how experiences of adversity and perceptions of stress shape neurodevelopment, and how these changes impact the etiology, course, and treatment of depression. Her lab uses a multimodal approach, including behavioral, cognitive, endocrine, immune, and neuroimaging techniques, and leverages big data and global initiatives to identify robust brain imaging markers associated with depression and related conditions. Grants and Funding: Her research has been generously funded by the Klingenstein Third Generation Foundation and the National Institute of Mental Health . Publications and Impact: Dr. Ho has published extensively in high-impact journals, with over 100 peer-reviewed articles. Her recent work includes studies on the effects of COVID-19 on adolescent mental health, the role of inflammation in depression, and the use of machine learning to classify major depressive disorder using neuroimaging data. She is also a key contributor to the ENIGMA consortium, a global initiative aimed at understanding brain alterations in psychiatric disorders.

Arie E. Kaufmanمشاهده پروفایل

استاد

• Computer Graphics
• Visualization
• Virtual Reality
• +۴ مورد دیگر

Arie E. Kaufman is a Distinguished Professor in the Department of Computer Science at Stony Brook University, serving as Chief Scientist of the Center of Excellence in Wireless and Information Technology (CEWIT) and Director of the Center of Visual Computing (CVC). He additionally holds a Distinguished Professorship in Radiology, with a 40+ year career at Stony Brook since joining in 1985 and chairing the CS department from 1999-2009. His seminal research spans computer graphics, visualization, and virtual reality with biomedical applications, pioneering breakthroughs including 3D Virtual Colonoscopy (FDA-approved colon cancer screening), Cube hardware architectures (commercialized as VolumePro), the Reality Deck (1.5 billion-pixel immersive display), and foundational work in volume visualization. His interests focus on real-time rendering, medical imaging, and immersive analytics, with recent work integrating machine learning for healthcare and environmental risk visualization. Recent publications demonstrate continued leadership in high-resolution immersive displays (Silo), XR analytics with LLMs, storm surge visualization, and neural reconstruction techniques. His work bridges theoretical innovation with practical applications, particularly in pancreatic cancer prognosis and disaster preparedness. Major honors include: IEEE Visualization Career Award (2005) Fellow of the National Academy of Inventors (2017) ACM Fellow (2009) IEEE Fellow (1998) Long Island Technology Hall of Fame (2013) European Academy of Sciences membership (2002) As PI on 100+ research grants, Kaufman's work has generated 300+ refereed papers, 40+ patents, and extensive media coverage (New York Times, Science, Wall Street Journal). He leads the Center of Visual Computing with focus on translational research, including VolVis software (5,000+ installations) and Reality Deck deployments for big data analytics. His lab develops cutting-edge visualization infrastructure for medical diagnostics and environmental modeling, with current projects advancing immersive storm surge analytics, neural structure extraction, and VR-based risk communication systems. Future work emphasizes AI-enhanced visualization for precision medicine and climate resilience planning.

• Clinical exercise physiology
• Medical and health aspects of master athletes
• Prevention and rehabilitation of chronic disease
• +۶ مورد دیگر

Mike Climstein serves as a Lecturer in Human Sciences within the Faculty of Health at Southern Cross University (SCU), where he coordinates the Master of Clinical Exercise Physiology program and acts as Deputy Academic Integrity Officer. He concurrently holds an adjunct Associate Professor position in the Physical Activity, Lifestyle, Ageing and Well-being Research Group at the University of Sydney and directs SCU's Aquatic Based Research initiative. His academic credentials include a PhD in Exercise Science & Human Performance from Oregon State University (1990), an MSc in Exercise Science from Utah State University (1986), and a BSc in Biology from Utah State University (1982). Climstein's research spans clinical exercise physiology with emphases on master athletes' health, chronic disease rehabilitation, sports injury surveillance (particularly surfing), cardiac rehabilitation, smart textile monitoring, and osteoporosis. His work integrates technology-driven health solutions with population-specific exercise interventions, notably for aging populations and athletes. Analysis of his recent publications reveals three dominant trends: 1) AI applications in dermatological diagnostics (e.g., melanoma detection systems), 2) physiological adaptations in aging populations through martial arts and aquatic exercise, and 3) epidemiological studies of chronic conditions in master athletes and occupational groups. These reflect his dual focus on technological innovation and practical health interventions. His scientific recognition includes: Fellowship by Sports Medicine Australia (FASMF) Fellowship by American College of Sports Medicine (FACSM) Fellowship by Exercise and Sports Science Australia (FAAESS) Climstein actively supervises 4 PhD and 2 Master's students while co-supervising 6 Doctor of Physiotherapy candidates. His research program is supported by 38 grants totaling over $7.8 million AUD, including studies on aquatic rehabilitation and smart textile monitoring. As Director of Aquatic Based Research, he leads interdisciplinary teams investigating water-based exercise interventions for chronic disease management, with ongoing projects in cardiac rehabilitation and osteoporosis prevention.