جست‌وجوی استاد و پژوهشگر

Deborah Foxمشاهده پروفایل

دانشیار

• Midwifery
• Maternal Health
• Technology in Healthcare
• +۷ مورد دیگر

Deborah Fox is Associate Professor in Midwifery at the University of Technology Sydney (UTS), Faculty of Health, and a core member of the Centre for Midwifery, Child and Family Health. She serves as Co-lead of the Maridulu Budyari Gumal SPHERE Maternal and Women's Clinical Theme and Chair of the National Publicly Funded Homebirth Consortium. In 2024, she received the Faculty of Health Dean's Academic Excellence Award for Research (Mid Career Researcher), following her 2021 award as Highest Performing Early Career Researcher from the School of Nursing and Midwifery. Her research focuses on optimizing physiological processes and positive experiences for women with complex pregnancies, with particular emphasis on the mediation of technology in midwifery practice. Current projects include evaluation of non-invasive fetal ECG beltless and wireless fetal monitoring in labor and birth, and examining the social, economic and environmental impacts of telemonitoring and telehealth in pregnancy and postpartum care. Dr. Fox's scholarly work demonstrates consistent focus on technology's role in maternity care, women's experiences of monitoring during labor, and innovative approaches to midwifery practice. Her recent publications show increasing emphasis on digital health solutions, AI applications in women's health, and pandemic impacts on maternal care systems globally. Faculty of Health Dean's Academic Excellence Award for Research (Mid Career Researcher) 2024 Highest Performing Early Career Researcher award from School of Nursing and Midwifery 2021 Editorial Board Member, Women and Birth journal Dr. Fox is actively involved in higher degree research supervision and has developed innovative teaching resources, including an Objective Structured Clinical Examination for perinatal mental healthcare. She is scheduled to spend three months as a Visiting Scholar at the University of Oxford in 2025.

Jörg Bohlmannمشاهده پروفایل

استاد

• Plant Defense Mechanisms
• Terpenoid Biochemistry
• Forestry Genomics
• +۱۲ مورد دیگر

Jörg Bohlmann is a Professor in the Department of Forest and Conservation Sciences at the University of British Columbia , affiliated with the Michael Smith Laboratories, Botany Department (Faculty of Science), and Wine Research Centre. His research spans genomics, biochemistry, and chemical ecology of plant specialized metabolism, focusing on terpenoids and phenolics for applications in forest health and bioproducts. Research Streams : Plant defense against insects/pathogens, metabolic engineering of bioproducts, forest genomics, and molecular evolution of terpenoid pathways. Collaborations : National and international partnerships with academia, government, and biotech industries. Recent Publications highlight genomic insights into Western Redcedar (2023), including its low genetic diversity and adaptation mechanisms despite self-fertilization. Earlier work (2001–2022) covers conifer defense systems, Arabidopsis terpenoid pathways, cannabis flavor genetics, and mass spectrometry infrastructure. Scientific Awards include: NSERC E.W.R. Steacie Fellow (2015), Fellow of the Royal Society of Canada (2015), Feodor Lynen Postdoctoral Fellowship (1995–1998), and Distinguished University Scholar (UBC). Funding Sources : NSERC (Discovery/Strategic grants), CFI, Genome Canada/BC, provincial/federal agencies. Labs & Facilities : Michael Smith Laboratories (UBC), National Centre of Excellence, Forest Sciences Centre, and a dedicated mass spectrometry lab for metabolite analysis.

Zainab Talebمشاهده پروفایل

پژوهشگر

• Circadian Biology
• Gastroenterology
• Metabolic Studies
• +۳ مورد دیگر

Zainab Taleb is affiliated with the University of Windsor, contributing to research in circadian biology and its implications for digestive health. Her work focuses on the interplay between circadian rhythms, intestinal stem cells, and disease mechanisms such as colitis and tumor initiation. She participated in a university panel addressing vaccine hesitancy related to the pandemic response. Research emphasizes circadian clock genes like BMAL1 and their role in metabolic and inflammatory processes. Collaborations may involve interdisciplinary teams studying chronobiology's impact on gastrointestinal disorders and oncology. Her studies utilize animal models to investigate timing-dependent physiological responses, with potential applications in therapeutic timing strategies.

Rui Niمشاهده پروفایل

دانشیار

• Experimental Fluid Mechanics
• Turbulence and Turbulent Multiphase Flow
• Dusty Flow and Particle-Laden Flow
• +۵ مورد دیگر

Rui Ni is an associate professor in the Department of Mechanical Engineering at Johns Hopkins University, directing the Fluid Transport Lab. His research focuses on experimental fluid mechanics, turbulence, multiphase flows, and their applications in energy systems, environmental engineering, and physiological processes. He holds a PhD in Physics from the Chinese University of Hong Kong (2011), followed by postdoctoral work at Yale and Wesleyan Universities. Before joining JHU, he held the Kenneth Kuan-Yun Kuo Early Career Professorship at Penn State University. His research interests include dusty flows, Lagrangian particle tracking, and animal collective behaviors. Notable projects include collaborations with NASA on plume-surface interaction and the development of advanced diagnostic tools like physics-informed machine learning and 3D particle tracking. He has received prestigious awards, including the NSF CAREER Award and ACS-PRF New Investigator Award, and leads studies on turbulence modulation by deformable bubbles, fish schooling efficiency in turbulent environments, and interfacial mass transfer dynamics. Key Projects: Plume-Surface Interaction (NASA collaboration), Fish Aquarium with Turbulent Environment (FATE) facility, V-ONSET multiphase flow facility. Grants: Gordon and Betty Moore Foundation’s Experimental Physics Investigators Initiative Grant. Lab Focus: Experimental and computational studies of multiphase flows, physiological flows, and complex systems. Ni’s work bridges fundamental fluid dynamics with practical applications, such as improving energy efficiency and understanding biological systems like fish schooling and nasal drug delivery mechanisms.

Michael Moorمشاهده پروفایل

استادیار

• Medical AI
• Machine Learning in Healthcare
• Causal Learning
• +۳ مورد دیگر

Prof. Michael Moor is a tenure-track Assistant Professor for Medical AI at ETH Zurich's Department of Biosystems Science and Engineering in Basel. Previously, he conducted postdoctoral research at Stanford University under Prof. Jure Leskovec, focusing on medical foundation models. His work spans causal learning, multimodal AI, and sepsis prediction. Moor holds an MD from the University of Basel and a PhD from ETH Zurich's Machine Learning and Computational Biology Lab under Prof. Karsten Borgwardt. Research Interests: Generalist medical AI models Multimodal medical reasoning Zero-shot and few-shot learning Clinical causal inference Retrieval-augmented language models Sepsis prediction systems Key Achievements: Published foundational work in Nature (2023) on generalist medical AI Developed Med-Flamingo multimodal model (2023) Zero-shot causal learning framework accepted to NeurIPS 2023 (Spotlight) International sepsis prediction study with 156k ICU patients (2023) Lab Activities: Leads ETH's Medical Foundation Models group, collaborating with Stanford HAI and NASA Ames. Active in creating medical AI benchmarks like AgentClinic and developing retrieval-augmented systems like Almanac.

Zongyi Liمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Scientific Computing
• Partial Differential Equations
• +۵ مورد دیگر

Zongyi Li is a Research Fellow at Massachusetts Institute of Technology , hosted by Kaiming He. They are currently pursuing a Ph.D. in Computing and Mathematical Sciences at Caltech (2019-2025), mentored by Anima Anandkumar and Andrew Stuart. Ph.D. candidate: Computing and Mathematical Sciences, Caltech (2019-2025) B.Sc. in Computer Science and Mathematics with a Jazz minor from Washington University in St. Louis (2015-2019) They focus on Neural Operators for learning solution operators in Partial Differential Equations (PDEs) , particularly in fluid mechanics and earth science . Their work models physical simulations with chaotic behaviors and complex geometries, showing applications in weather forecasting , carbon storage , and aerodynamics simulation . Publications emphasize resolution-invariant models , chaotic systems , and zero-shot super-resolution capabilities. Their research combines Fourier analysis , graph networks , and physics-informed loss functions to achieve state-of-the-art performance in PDE solving with up to 1000x speedup over traditional solvers. Fellowships: Kortschak Scholarship PIMCO Fellowship Amazon AI4Science Fellowship Nvidia Fellowship MIT Novo Nordisk AI Fellowship Code & Open-Source: Co-developer of the NeuralOperator library Implementations for Fourier Neural Operators , Graph Neural Operators , and Tensorized Neural Operators Media Recognition: Quanta Magazine MIT Tech Review NVIDIA Features Towards Data Science

Sanjay Purushothamمشاهده پروفایل

استادیار

• Machine Learning
• Data Mining
• Optimization Theory
• +۵ مورد دیگر

Sanjay Purushotham is an Assistant Professor in the Department of Information Systems at the University of Maryland Baltimore County (UMBC), with a PhD in Electrical Engineering from the University of Southern California (USC) and a postdoctoral background in Computer Science at USC's Integrated Media Systems Center (IMSC). His research focuses on machine learning, data mining, and their applications in biomedical informatics, social network analysis, and multimedia data mining. Key contributions include survival analysis models using pseudo values and federated learning frameworks for healthcare data. He has received awards including the Best Paper Award at SIGSPATIAL 2014 and a Best Poster Runnerup at SCMLS 2016. Education: PhD in Electrical Engineering (USC), Postdoc in Computer Science (USC) His work spans interdisciplinary areas such as domain adaptation for remote sensing, thermal face translation, and interpretable neural networks for medical applications. Recent projects include federated survival analysis models and climate-informatics frameworks for cloud property retrieval. He teaches courses in artificial intelligence, healthcare informatics, and statistical learning at UMBC. Research highlights include developing MedFuseNet for multimodal medical question answering and VDAM for multi-sensor cloud data analysis. His work on fair survival analysis models addresses algorithmic bias in healthcare predictions. Current grants include a NSF CAREER award for trustworthy federated learning in computational healthcare.

Patrick Sladeمشاهده پروفایل

استادیار

• Assistive Robotics
• Biomechanics
• Human-Robot Interaction
• +۶ مورد دیگر

Patrick Slade is an Assistant Professor of Bioengineering at Harvard University's School of Engineering and Applied Sciences (SEAS). His lab, the Slade Lab, focuses on developing assistive devices to enhance mobility through the integration of biomechanics, robotics, and human-centered artificial intelligence. Key research areas include exoskeletons, prosthetics, wearable sensors for health tracking, and navigation aids for visually impaired individuals. Research Interests: The lab emphasizes translating research into practical solutions, such as personalized exoskeletons and robotic systems to improve mobility. Recent work includes optimizing human-robot interaction algorithms and publishing in high-impact journals like Nature . Collaborations with labs like the Biodesign Lab and BIONICs Lab highlight cross-disciplinary efforts. Publications: Over 15 articles since 2017 span topics like exoskeleton design, energy expenditure modeling, and Bayesian reinforcement learning. Notable contributions include a 2022 Nature paper on personalized exoskeleton assistance and a 2021 study on navigation aids for impaired vision. Awards & Grants: Students in his group have received prestigious NSF GRFP fellowships and conference awards, reflecting the lab's emphasis on innovation. The lab actively engages in grant-funded projects to advance assistive technology. Lab & Team: The Slade Lab opened at Harvard in 2023 and includes PhD students and postdocs working on devices like robotic exoskeletons and health-tracking systems. Future work focuses on scalable solutions for mobility challenges through interdisciplinary approaches.

Geng Yuanمشاهده پروفایل

استادیار

• Artificial Intelligence Systems
• Energy-Efficient Deep Learning
• Model Compression
• +۵ مورد دیگر

Geng Yuan is an Assistant Professor at the University of Georgia's School of Computing, specializing in AI systems, energy-efficient deep learning, and hardware-software co-design. His work bridges machine learning algorithms with emerging hardware technologies like superconducting circuits and ReRAM. He holds a Ph.D. in Computer Engineering from Northeastern University (2023) and a Master's in Electrical & Computer Engineering from Syracuse University (2016). Doctor of Philosophy (Ph.D.) in Computer Engineering, Northeastern University (2023) Master of Science (M.S.) in Electrical & Computer Engineering, Syracuse University (2016) Bachelor of Science (B.S.) in Electrical Engineering, Beijing University of Technology (2014) His research focuses on optimizing deep learning systems for edge computing and mobile platforms through techniques like model compression, sparse training, and hardware-aware neural architecture search. Recent projects include adapting large language models via hybrid-grained pruning and developing ultra-low-power AQFP circuits for binary networks. Geng Yuan's publications span top venues like NeurIPS, CVPR, ICML, ICLR, ISCA, and DAC, with notable awards including a Best Paper Award at ICLR Workshop 2021, Spotlight Papers at ICLR 2023 and NeurIPS 2021, and a Design Contest 1st Place at ISLPED 2020. Best Paper Award (ICLR Workshop'21) Spotlight Paper Award (ICLR'23, NeurIPS'21) Design Contest 1st Place (ISLPED'20) Best Paper Nomination (DATE'21, ISQED'18) He actively recruits Ph.D., Master's students, and interns to his research group, focusing on advancing AI systems through interdisciplinary approaches combining machine learning, computer architecture, and electronic design automation.

Jeffrey Schallمشاهده پروفایل

استاد

• Visual Neurophysiology
• Neuroscience
• Cognitive Neuroscience
• +۵ مورد دیگر

Jeffrey Schall is a Full Professor of Biology and Program Director of the Visual Neurophysiology Centre at York University. He holds the Canada Research Chair in Translating Neuroscience. His research focuses on neural mechanisms underlying behavior, integrating neurophysiological and computational approaches across multiple scales. Schall is a core member of the Centre for Vision Research and the Canada First Research Excellence Fund Connected Minds initiative. Education: PhD in Anatomy (University of Utah School of Medicine, 1986), postdoctoral training at MIT. Awards include the Troland Research Award, Sloan Foundation Fellowship, and AAAS Fellowship. He served as Vision Science Society President in 2019. Research interests include visual attention, executive control, error monitoring, and translational neuroscience applications in law. His work bridges basic science with applied studies in clinical populations like schizophrenia patients. Collaborative projects involve EEG/MEG analysis, cortical microcircuitry modeling, and neuromodulation techniques. Teaching: YU_NRSC 2100 Systems, Behavioral, and Cognitive Neuroscience. Active in interdisciplinary initiatives linking neuroscience with legal systems through scholarship and policy engagement.

Daniel Segrèمشاهده پروفایل

استاد

• Systems Biology
• Metabolic Engineering
• Microbial Ecology
• +۷ مورد دیگر

Professor Daniel Segrè is a faculty member at Boston University, holding the title of Professor of Biology, Bioinformatics, and Biomedical Engineering. His research focuses on systems biology, microbial ecology, and metabolic engineering, with an emphasis on understanding complex biological networks and their applications in bioenergy and biomedicine. Segrè leads the Segre Lab ( segrelab.bu.edu ), where theoretical and computational approaches are applied to study metabolism, microbial interactions, and synthetic biology. Segrè earned his PhD from the Weizmann Institute of Science, Israel. His work bridges fundamental science and applied engineering, addressing topics such as microbial community dynamics, metabolic pathway design, and environmental microbiome applications. Research Interests: Systems biology of metabolism, evolution of biochemical networks, microbial interactions, bioinformatics, and environmental microbiome engineering. His lab develops computational models (e.g., COMETS) to simulate microbial ecosystems and design synthetic microbial communities for climate change mitigation and bioenergy production. Teaching: Courses include BE 777 (Computational Genomics), BF 821 (Bioinformatics Seminar), and BF 571 (Dynamics and Evolution of Biological Networks). These courses reflect his expertise in integrating computational methods with biological systems analysis.

Karin Allor Pfeifferمشاهده پروفایل

استاد

• Physical Activity Measurement
• Childhood Obesity Prevention
• Exercise Physiology
• +۳ مورد دیگر

Karin Allor Pfeiffer is a Professor in the Department of Kinesiology at Michigan State University (MSU) and Director of the Institute for the Study of Youth Sports. She holds additional membership in the Center for Physical Activity and Health. With a Ph.D. from MSU, her research focuses on physical activity measurement methodologies and population health interventions, particularly among children and adolescents. Her work addresses obesity prevention, environmental design impacts on activity levels, and sociocultural factors influencing youth sport participation. Education: Ph.D. in Kinesiology from Michigan State University Her research interests emphasize: - Quantitative methods for physical activity assessment - Schoolyard redesign strategies and their health impacts - Cardiometabolic risk factors in pediatric populations - Longitudinal tracking of physical fitness and health outcomes Recent work explores accelerometer fragmentation metrics, GPS-linked activity tracking, and disparities in sedentary behavior across demographic groups. She has pioneered interdisciplinary approaches integrating spatial analysis, wearable technology, and policy evaluation. Key contributions include developing the Observational System for Recording Physical Activity in Children and advancing consensus methods for accelerometer data interpretation. Her studies frequently highlight socioeconomic and environmental determinants of health behaviors. Dr. Pfeiffer collaborates with public health agencies and urban planners to translate research into actionable policies. Her lab focuses on scalable interventions for underserved communities, leveraging community-engaged methods to address greenspace accessibility and safety concerns.

Senthold Assengمشاهده پروفایل

استاد

• Digital Agriculture
• Climate Change Impacts
• Sustainable Crop Production
• +۵ مورد دیگر

Prof. Senthold Asseng is a Professor of Digital Agriculture at the Technical University of Munich (TUM), leading the Hans Eisenmann Forum for Agricultural Sciences since 2021. His research focuses on climate-plant-soil systems modeling, addressing global food security, sustainable agriculture, and digital technologies like vertical farming and autonomous robotics. He holds a PhD from Humboldt University Berlin and habilitation from TUM, with prior roles at CSIRO Australia and the University of Florida (as Full Professor and Director of the Florida Climate Institute). His honors include AAAS Fellow, Web of Science Highly Cited Researcher, and multiple teaching/mentorship awards. Education: BSc/MSc in Agronomy & Horticulture, Humboldt University Berlin (1989-1990) PhD in Agronomy, Humboldt University Berlin (1994) Habilitation in Agronomy, TUM (2004) Research Interests: Climate change impacts on crops, digital agriculture technologies, systems analysis for autonomous farming, and vertical farming sustainability. His work integrates modeling, robotics, and environmental control to enhance agricultural resilience and productivity. Awards: AAAS Fellow (2019) Highly Cited Researcher (2019) UF Research Foundation Professor (2016-2019) Grants & Leadership: Led interdisciplinary projects like AgMIP-Wheat, SECC, and FAO advisory roles. Active in editorial roles for journals like Global Change Biology and Environmental Research Letters . Labs/Teams: Chair of Digital Agriculture at TUM, collaborating on projects like Smartfield and Proteins4Singapore , focusing on automation, controlled environment agriculture, and climate-smart solutions.

Karen Cheungمشاهده پروفایل

استاد

• Biomedical microsystems
• Lab-on-a-chip systems
• Tissue engineering
• +۹ مورد دیگر

Karen C. Cheung is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia, with cross-appointments in the Faculty of Medicine and the School of Biomedical Engineering where she serves as Director of the Graduate Program. She holds her office in KAIS 3064 and can be reached at (604) 827-4114. Dr. Cheung received her BSc and PhD degrees in Bioengineering from the University of California, Berkeley in 1998 and 2002, respectively. From 2002-2005, she was a postdoctoral researcher at the École Polytechnique Fédérale de Lausanne in Switzerland. She joined UBC in 2006 and has established herself as a leading researcher in biomedical microsystems. Her research spans multiple areas of biomedical engineering with particular focus on lab-on-a-chip systems for cell culture and characterization , inkjet printing for tissue engineering , and implantable neural interfaces . Her work integrates microfluidics, biosensors, and tissue engineering to create platforms that better mimic in vivo conditions for drug screening and disease modeling. Current projects include developing organ-on-a-chip models of the human airway for studying aerosol exposure effects, creating microscale tumor models for cancer research, and advancing silicon photonic biosensors for medical diagnostics. Dr. Cheung leads the Bio-Medical Micro Devices Laboratory at UBC, which houses multiple research teams working on cutting-edge biomedical technologies. Her lab has developed microfluidic platforms capable of precisely controlling oxygen levels around tumor spheroids to study cancer treatment responses under realistic physiological conditions. The lab also works on novel fabrication techniques for microelectrode arrays and tissue clearing protocols for 3D imaging of microtissues. As an educator, Dr. Cheung teaches several specialized courses including ELEC 361 (Molecules to Mechanisms), ELEC 464 (Nanotechnology and Nature), EECE 301 (Topics in Nanotechnology and Microsystems), ELEC 473 (Biological Micro-Electro-Mechanical Systems), and ELEC 521 (Biomedical Microdevices). She has supervised numerous graduate students through their MASc, PhD, and postdoctoral work, with many alumni now holding academic positions or working in the biomedical industry. Her research is supported through multiple funding sources and collaborations with industry partners. Dr. Cheung is affiliated with several research centers including the Airway Centre, Bionics Network, Centre for Blood Research, and the Institute for Computing, Information and Cognitive Systems (ICICS) at UBC.

• Developmental Biology
• Neurosciences
• Dopamine Neurons
• +۴ مورد دیگر

Thomas Perlmann is a Professor in Molecular Developmental Biology at the Karolinska Institutet , leading research at the Department of Cell and Molecular Biology and serving as Director of the Stockholm Branch of the Ludwig Institute for Cancer Research. He also holds the position of Secretary General of the Nobel Assembly and Nobel Committee for Physiology or Medicine since 2016. Ph.D. , Karolinska Institutet, 1991 M.Sc. , Stockholm University, 1987 Research Interests : The Perlmann lab investigates the specification and maintenance of dopamine neurons in the central nervous system, with a focus on transcriptional regulation , signaling pathways , and regenerative medicine applications for Parkinson’s disease and other neurodegenerative disorders. His work bridges developmental biology and neuroscience , emphasizing the role of transcription factors in neuronal identity and function. Recent Research Trends : Perlmann’s recent publications highlight the use of single-cell RNA sequencing to dissect dopamine neuron heterogeneity , epigenetic regulation during development, and transcriptomic changes in Parkinson’s disease models. His studies increasingly leverage multiomics and bioinformatics to map neuronal lineage trajectories and gene expression dynamics. Scientific Awards : Royal Medal by HM the King (2025) Nicholson Lecturer, Rockefeller University (2011) Göran Gustafsson Prize in Molecular Biology (1999) Eric K. Fernström Young Investigator Prize (1997) Advising & Collaborations : While no student names are explicitly listed, Perlmann collaborates extensively with researchers such as Malin Parmar , Agnete Kirkeby , and Per Svenningsson on projects related to neuronal development and cell therapy . His lab receives funding from institutions like the Ludwig Institute for Cancer Research . Labs & Teams : The Perlmann Lab at Karolinska Institutet includes researchers like Linda Gillberg , Laura Lahti , and Behzad Yaghmaeian Salmani , who work on mouse models , single-cell transcriptomics , and bioinformatics to study dopamine neuron biology.