جست‌وجوی استاد و پژوهشگر

• Pain Management
• Cancer Pain
• Neuromodulation
• +۴ مورد دیگر

Daniel W. Odell, MD is a Clinical Associate Professor in the Department of Anesthesiology at the University of Utah School of Medicine. He maintains dual clinical appointments at the University of Utah Health system and Huntsman Cancer Hospital, specializing in pain management and anesthesiology within the Supportive Oncology and Survivorship program. His practice focuses on complex cancer pain cases and advanced neuromodulation techniques, serving patients across Salt Lake City clinical sites including the Pain Management Center and Huntsman Cancer Institute South Clinic. Dr. Odell's educational journey includes foundational training in biomedical engineering and microbiology, followed by medical education and specialized clinical training: Bachelor of Science in Biomedical Engineering (minor in Chemistry) from Utah State University Associate of Science in Microbiology from Brigham Young University-Idaho Doctor of Medicine from Medical College of Wisconsin Transitional Internship at Wheaton Franciscan – St. Joseph Campus Residency and Chief Residency in Anesthesiology at University of Utah School of Medicine Fellowship in Pain Medicine at University of Utah His research program centers on revolutionizing cancer pain management through innovative intrathecal drug delivery systems, spinal cord stimulation, and evidence-based cannabis applications. Current investigations address critical gaps in understanding radiotherapy interactions with implanted pain devices, optimizing opioid-sparing protocols, and developing precision approaches for refractory cancer pain. This work directly informs his clinical practice where he implements cutting-edge neuromodulation strategies to minimize systemic opioid exposure while maximizing quality of life for oncology patients. Analysis of his 15 most recent publications reveals a dominant research trajectory focused on intrathecal drug delivery optimization (60% of works), with significant contributions to neuromodulation techniques (25%) and cannabinoid therapeutics (10%). His scholarship demonstrates consistent methodological rigor through prospective case series, retrospective analyses, and systematic reviews that bridge basic science with clinical implementation. The publications collectively underscore a strategic shift toward reducing opioid dependence in cancer pain management while addressing device-related complications in irradiated tissues. Dr. Odell maintains dual board certification from the American Board of Anesthesiology in both Anesthesiology and Pain Medicine subspecialty. His clinical excellence is reflected in exceptional patient satisfaction metrics (4.9/5 from 137 reviews), with consistent praise for his compassionate communication, technical expertise, and personalized approach to complex pain scenarios. Within the University of Utah's academic ecosystem, Dr. Odell contributes to medical education through clinical supervision and has authored authoritative book chapters in The Hospice Companion. His collaborative work with multidisciplinary teams at Huntsman Cancer Institute integrates pain specialists, oncologists, and palliative care providers to develop comprehensive survivorship programs. Current initiatives focus on refining antiplatelet management protocols for cancer patients undergoing neuromodulation procedures and investigating wound healing implications of novel targeted therapies.

• Pain Medicine
• Cancer Pain
• Anesthesiology
• +۵ مورد دیگر

Dr. Jill Sindt is a Clinical Associate Professor of Anesthesiology at the University of Utah, providing specialized pain management services at the University of Utah Pain Management Center and Huntsman Cancer Institute's Supportive Oncology and Survivorship Clinic. Board certified in Anesthesiology and Pain Medicine, she focuses on cancer pain and chronic pain through procedural, pharmacological, and non-pharmacological interventions, maintaining exceptional patient satisfaction ratings (4.9/5 from 129 reviews). Education: B.A., Spanish Language and Literature (Summa Cum Laude), Colorado State University M.D., University of Colorado School of Medicine Transitional Internship, Intermountain Medical Center Residency in Anesthesiology, University of Utah Fellowship in Pain Medicine, University of Utah NIH Summer Research Fellowship in Pediatric Nutrition, University of Colorado Health Sciences Center Research Focus: Dr. Sindt's work centers on optimizing cancer pain management through intrathecal drug delivery systems, neuromodulation, and opioid conversion strategies. Her research addresses critical challenges including lead migration complications, radiotherapy interactions with implanted devices, and reducing systemic opioid dependence while maintaining effective analgesia. She emphasizes evidence-based protocols for complex pain scenarios in immunocompromised cancer patients. Publication Trends: Analysis of her 15 most recent publications reveals consistent innovation in interventional pain management for oncology. Key themes include refining intrathecal morphine conversion ratios (100:1), quantifying complications of celiac plexus neurolysis, and integrating neuromodulation into palliative care frameworks. Her work bridges clinical practice with guideline development, notably through NCCN Cancer Pain Guidelines contributions. Clinical Excellence: Patients consistently highlight Dr. Sindt's compassionate expertise in managing complex pain conditions, with testimonials emphasizing her ability to tailor treatments to individual needs while navigating medication interactions and side effects. Her dual clinical roles enable seamless integration of pain management within comprehensive cancer care pathways.

Catie Changمشاهده پروفایل

استادیار

• Biomedical Imaging
• Image Processing
• Neuroscience
• +۵ مورد دیگر

Catie Chang is an Assistant Professor at Vanderbilt University , holding dual appointments in the Department of Electrical and Computer Engineering and the Department of Computer Science . She leads the Neuroimaging & Brain Dynamics Lab , focusing on advancing neuroimaging methodology through interdisciplinary collaboration with neuroscience, engineering, and medicine. Research Interests : Dynamic brain states and functional connectivity EEG-fMRI signal integration Physiological basis of neuroimaging signals Machine learning for multimodal data Aging and autonomic brain-body interactions Selected Article Trends : Recent publications emphasize autonomic coupling , aging studies , multimodal integration , and machine learning applications in neuroimaging. Her work bridges biomedical engineering and cognitive neuroscience to develop tools for disease biomarkers. Scientific Awards : OHBM Early Career Investigator Award (2023) Sally and Dave Hopkins Faculty Fellow (2023) Lab Leadership : Mentored 8 PhD students and postdocs, including Haatef Pourmotabbed (F31 Fellow), Shiyu Wang , and Kim Rogge-Obando . Lab members have received multiple accolades at conferences like OHBM, MICCAI, and ISBI.

Dakai Zhuمشاهده پروفایل

استاد

• Dependable computing
• Low-power computing
• IoT (Internet of Things)
• +۳ مورد دیگر

Dakai Zhu is a Professor, Assistant Department Chair, and Graduate Advisor of Record for PhD programs in the Department of Computer Science at the University of Texas at San Antonio (UTSA). He holds the Kay and Steve Robbins Faculty Teaching Fellowship Award in Computer Science, reflecting his commitment to education and research excellence. His research focuses on dependable and low-power computing, IoT innovations, real-time embedded systems, and cloud computing performance management. Education: Ph.D. in Computer Science, University of Pittsburgh M.E. in Computer Science and Technology, Tsinghua University B.E. in Computer Science and Technology, Xi'an Jiaotong University Dr. Zhu's work emphasizes sustainable computing frameworks for AI-driven healthcare applications, energy-efficient fault-tolerant systems, and privacy-preserving IoT solutions. His recent research includes real-time health monitoring using wearable sensors (e.g., PPG-based heart rate analysis), cybersecurity for cyber-physical systems, and optimization of embedded systems for assistive technologies like power wheelchair control. He also investigates scheduling algorithms for multiprocessor systems and cloud resource management to enhance reliability and energy efficiency. His publications span topics from AI-enabled health frameworks to fault-tolerant scheduling strategies, showcasing a blend of theoretical rigor and practical applications. Awards highlight his contributions to teaching and interdisciplinary research bridging computer science with healthcare and embedded systems.

David Grayمشاهده پروفایل

استاد

• Transport Policy
• Sustainable Transportation
• Remote and Rural Transport
• +۳ مورد دیگر

Professor David Gray is a Professor of Transport Policy and Academic Strategic Lead for Research at Robert Gordon University's School of Creative and Cultural Business. His work focuses on transport in remote, rural, and island communities, climate change impacts, and Scottish transport policy. He leads projects addressing sustainable transport solutions, energy efficiency in housing, and autonomous vehicle implementation. Research Interests: Transport policy and planning in rural/remote areas Low-carbon mobility and energy transitions Public engagement in transport initiatives Socio-cultural impacts of transport infrastructure Key Projects: Stronghouse: Community approaches to energy-efficient retrofitting PAV: Planning for Autonomous Vehicles in the North Sea Region Impact Accelerator: Storytelling and heritage initiatives Advising & Grants: Supervises PhD students on topics like sustainable tourism strategies and island games evaluation Secured funding for projects like Green Passenger Transport in Rural Areas (€6M+) Labs/Teams: Active in the Transport & Energy Policy Group and collaborates with interdisciplinary teams across the Scottish Centre for Evidence-based Multi-professional Practice.

• Quantum Computing
• Machine Learning
• Computational Neuroscience
• +۳ مورد دیگر

Johnson Thomas is a Professor in the Department of Computer Science at Oklahoma State University, with affiliations in both the Stillwater and Tulsa campuses. His research focuses on Quantum Computing, Machine Learning, and Computational Neuroscience, with notable work on quantum circuit optimization and spiking neural networks. He holds degrees from the University of Reading (PhD, 1995), University of Edinburgh (MSc, 1983), and University of Wales (BSc, 1982). His teaching spans advanced topics in databases, quantum computing, and programming languages. Recent courses include *Quantum Computing*, *Advanced Topics in Information Systems*, and *Discrete Mathematics for Computer Science*. He has also advised doctoral students and led research in distributed systems and security. Research interests include quantum algorithms, neurocomputational models, and causal inference. His work bridges theoretical foundations with practical applications, such as ROS security frameworks and NIRS-based forage quality prediction. Over 20 funded projects highlight his expertise in big data, autonomous systems, and sensor networks. Publications emphasize quantum circuit design, medical ML interpretation, and computational neuroscience. Collaborations include interdisciplinary projects with healthcare and agricultural sectors. His contributions advance both theoretical computer science and applied technologies.

• Applied Mathematics
• Control Theory
• Intelligent Transportation Systems
• +۳ مورد دیگر

Jianping Gao is a Professor in applied mathematical modeling and control systems, with significant contributions to vehicular networks, privacy protection algorithms, and nonlinear dynamical systems. His work spans interdisciplinary domains including intelligent transportation, federated learning, and biomechanical engineering. Core Research Areas : Mathematical modeling of chemotaxis and ecological systems Secure computation offloading in vehicle edge networks Federated learning optimization for Internet of Vehicles Privacy-preserving algorithms in social networked transportation Recent Trends : 2025 publications focus on dynamic gradient compression strategies and 3D radar sensing for autonomous vehicles 2024 work emphasizes blockchain-based privacy methods and Gaussian process vehicle state estimation 2023 studies include comprehensive surveys on social IoV security and contraflow control optimization The most frequent co-authors include Ling Xing (13 collaborations), Honghai Wu (12), Huahong Ma (8), and Kaikai Deng (4), indicating sustained interdisciplinary team efforts.

Andrea S. Bertkeمشاهده پروفایل

دانشیار

• Virology
• Neuroscience
• Infectious Diseases
• +۴ مورد دیگر

Andrea S. Bertke, PhD, is an Associate Professor in the Department of Population Health Sciences at the Virginia-Maryland College of Veterinary Medicine, Virginia Tech. Her research focuses on neurotropic viruses, particularly herpes simplex viruses (HSV-1/HSV-2) and SARS-CoV-2, investigating molecular mechanisms of latency, reactivation, and neuronal pathogenesis. She explores how stress hormones and neurotrophic factors influence viral behavior in sensory and autonomic neurons, while also studying SARS-CoV-2 survival on food surfaces and its neurological impacts. Education: PhD in Emerging Infectious Diseases, Uniformed Services University of the Health Sciences (2007) BS in Microbiology, Bowling Green State University (2001) Research Interests: Molecular mechanisms of HSV latency/reactivation; HSV neuronal tropism; SARS-CoV-2 neuroinvasion and foodborne survival; development of antivirals targeting latency; zoonotic disease transmission. Her work bridges virology, neuroscience, and public health, with emphasis on translational applications. Professional Contributions: Active member of the Society for Neuroscience, American Society of Microbiology, and American Society of Virology. Her publications span 2007–2025, addressing HSV biology, SARS-CoV-2 dynamics, and neurotropic virus pathogenesis. Recent work highlights viral survival in food systems and neuronal infection pathways. Labs/Teams: Leads research on neurotropic viruses and zoonotic disease interfaces. Collaborates on One Health approaches to emerging viral and vector-borne diseases.

Sergio Araujo-Estradaمشاهده پروفایل

مدرس

• Control Systems
• Robotics
• Aerospace Engineering
• +۳ مورد دیگر

Sergio Araujo-Estrada is a Lecturer in Control and Robotics at the Department of Aeronautics and Astronautics, University of Southampton. His research focuses on developing bio-inspired techniques to enhance the functionality and trustworthiness of robotic systems, particularly Unmanned Vehicles (UAVs), in air/water environments. He emphasizes improving control systems through modeling and applying natural principles to engineering challenges. Education: BEng in Aerospace Engineering (National Polytechnic Institute, Mexico), MSc in Electrical Engineering (CINVESTAV-Mexico), PhD in Aerospace Engineering (University of Bristol, 2017). Postdoctoral research at the University of Bristol before joining Southampton in 2022. Teaching: Leads the Mechanics of Flight module and supervises CubeSat group design projects. Current PhD students include Sourish Mukherjee, Merle Jill Weniger, and Bailey Rodney McAtee. Research Interests: Bio-inspired flight control, UAV dynamics, distributed sensing, wing-morphing technology, and simulation-to-real transfer techniques. Key Projects: Wind tunnel testing of bio-inspired UAVs, reinforcement learning for flight control, and legal frameworks for drone applications in construction. Labs/Teams: Member of Computational Engineering and Design Group, collaborating on interdisciplinary robotics and aerospace engineering initiatives.

• Control
• Optimization
• Data Science
• +۳ مورد دیگر

Victor Zavala Tejeda is the Baldovin-DaPra Professor in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison and a senior computational mathematician at Argonne National Laboratory. He holds a B.Sc. from Universidad Iberoamericana (2003) and a Ph.D. from Carnegie Mellon University (2008), both in chemical engineering. His research focuses on control, optimization, data science, and their applications to energy and environmental systems. He has received numerous awards, including the NSF and DOE Early Career awards, PECASE, and the Vilas Mid-Career Award. His work spans sustainable energy systems, plastic recycling technologies, and process automation. Education: PhD in Chemical Engineering, Carnegie Mellon University (2008) B.Sc. in Chemical Engineering, Universidad Iberoamericana (2003) Research interests: Control systems and optimization for energy infrastructure Data-driven modeling of chemical processes Design of sustainable plastic recycling methods Integration of machine learning in process operations Notable awards include the Harvey Spangler Award (2024), Vilas Mid-Career Award (2023), and the Presidential Early Career Award (2019). His recent publications address challenges in circular economy, energy storage, and computational topology for material analysis. Teaching and advising involve advanced courses in chemical engineering and special topics in process systems engineering. His research group collaborates on projects related to decarbonization, waste-to-energy systems, and autonomous manufacturing processes.

• Collective Behavior
• Evolutionary Game Theory
• Cooperation Dynamics
• +۳ مورد دیگر

Dr. Mohammad Salahshour is a Research Fellow at the Department of Collective Behavior, Max Planck Institute of Animal Behavior in Konstanz, Germany. His work focuses on understanding collective behavior, evolutionary game theory, and ecological dynamics across biological and robotic systems. Research interests include the mechanisms behind swarm intelligence, predator-prey interactions, cooperation dynamics in heterogeneous populations, and the interplay between ecological resources and evolutionary processes. He explores these themes through agent-based modeling, game theory frameworks, and interdisciplinary approaches. Recent work highlights contributions to understanding how noise impacts cooperation, the evolution of moral norms, and the adaptability of robot swarms in dynamic environments. His studies often bridge ecological observations with theoretical models to uncover universal principles governing collective systems. Labs/Teams: Active in the Department of Collective Behavior, collaborating on projects involving animal behavior, robotics, and computational ecology.

William Hayesمشاهده پروفایل

استادیار

• Preferential choice
• Reinforcement learning
• Naturalistic decision making
• +۴ مورد دیگر

William Hayes is an Assistant Professor in the Department of Psychology at Binghamton University, leading the Decision Research and Modeling (DReaM) lab. His research focuses on cognitive processes in decision making, particularly how context influences choice behavior and the computational mechanisms underlying experience-based decisions. Techniques employed include large-scale online experiments, eye-tracking, mouse-tracking, and computational modeling. He is currently accepting graduate students for Fall 2024. Education: Postdoc, Indiana University PhD, University of South Carolina MA, University of North Carolina Wilmington BS, North Greenville University Research Interests: Preferential choice and reinforcement learning Naturalistic decision making Hierarchical Bayesian models Machine learning methods applied to decision processes His work explores how people encode past outcomes and adapt behaviors for long-term rewards, with recent studies addressing attribute comparability, attention dynamics, and biases in large language models. The DReaM lab emphasizes interdisciplinary approaches to understanding decision mechanisms in complex environments. Lab/Team: The DReaM lab combines experimental psychology with computational methods to investigate decision-making systems, focusing on contextual influences and adaptive learning processes. Grants & Advising: While specific grants are not listed, his active student recruitment and publication record suggest ongoing research funding and mentorship roles. No awards are explicitly mentioned in the provided materials.

• Inflammation Biology
• Autonomic Neuroscience
• Cardiovascular Physiology
• +۵ مورد دیگر

Ângela Raquel Amaro Leal is an Assistant Professor at the Egas Moniz Higher School of Health (ESSEM) and a researcher at the University of Lisbon's Cardiovascular Center (CCUL). She holds a PhD in Biomedical Sciences (2020) and a Master's in Neuroscience (2014) from the University of Lisbon. Her research focuses on inflammation, autonomic nervous system dysfunction, sepsis, and neurotoxicity mechanisms, combining animal models with translational approaches. She is actively involved in the Tracking3C and NEVERMIND projects, addressing cardiotoxicity and mental health in chronic diseases. Education: PhD in Biomedical Sciences (2020), Master in Neuroscience (2014), Degree in Pathology (2010) Key Projects: Tracking3C (FCT-funded), NEVERMIND (EU H2020) Research Themes: NF-κB pathway in sepsis, lead toxicity, doxorubicin-induced cardiotoxicity, cognitive training in epilepsy She has authored over 15 peer-reviewed articles, including studies on lead's neurocardiovascular effects and doxorubicin's dose-dependent toxicity. Her work bridges basic science and clinical applications, with a focus on improving patient outcomes in chronic and neurodegenerative diseases. Awards include an FCT PhD fellowship (2012).

Yiannis Papadopoulosمشاهده پروفایل

استاد

• Safety of AI
• Dependable Artificial Intelligence
• Safety of Machine Learning
• +۶ مورد دیگر

Professor Yiannis Papadopoulos is a leading academic in safety-critical systems and Dependable AI at the University of Hull's School of Computer Science, Faculty of Science and Engineering. His roles include teaching modules on Software Engineering, Digital Disruption, and Safety-Critical Systems. He holds a DPhil from the University of York and has over 25 years of research experience. Education: PhD/DPhil in Computer Science, University of York (2000) MSc in Advanced Manufacturing Technology, Cranfield University (1993) BSc/MSc in Electrical and Computer Engineering, Aristotle University of Thessaloniki (1991) Research Interests: Dependable AI, Safety of Machine Learning, and Autonomous Systems Model-Based Safety Engineering (HiP-HOPS method) Applications in Automotive, Aerospace, and Offshore Energy Generative Art and Philosophy-inspired Research Environments Publications: Recent work focuses on LLM safety, fairness in AI, and offshore wind maintenance. Key contributions include the Andromeda framework for safety assurance and the SafeML method for statistical safety monitoring. His research bridges bio-inspired AI with formal safety analysis, impacting industries globally. Grants & Projects: SESAME (EU H2020): Safety of Multi-Robot Systems (£482k) DEIS H2020: Dependability Engineering (£461k) EPSRC Edge AI Hub: Safety of Edge-AI (£214k) Academic Garden: His DEIS research group fosters a collaborative environment emphasizing ethical research and student well-being. Notable initiatives include Stoic philosophy seminars and interdisciplinary projects like the Timaeus digital art studio.

Christian W. Pesterمشاهده پروفایل

دانشیار

• Materials Science
• Polymer Chemistry
• Surface Engineering
• +۵ مورد دیگر

Dr. Christian W. Pester is an Associate Professor in the Department of Materials Science and Engineering at the University of Delaware. He holds courtesy appointments in the Chemistry Department and previously served as the Thomas K. Hepler Early Career Professor in Chemical Engineering at Penn State University. His research focuses on advanced functional surfaces, heterogeneous photocatalysis, self-healing coatings, and chemical recycling of PET plastics. Pester has been recognized with awards including the NSF CAREER Award (2022) and the TOSOH Award (2024). He earned a Diploma in Polymer Chemistry from the University of Bayreuth and a PhD from RWTH Aachen, followed by postdoctoral work at UCSB and Humboldt-funded research in Germany. His lab develops light-driven polymerization techniques, antimicrobial coatings, and sustainable materials solutions. Education: Diploma in Polymer and Colloid Chemistry, University of Bayreuth (Germany) PhD in Chemistry, RWTH Aachen University (Germany), 2013 (summa cum laude, Borchers Medal) Research Highlights: Pioneered oxygen-tolerant surface-initiated PET-RAFT polymerization for functional coatings Developed photocatalytic systems for organic synthesis and wastewater treatment Engineered self-healing polymer coatings with rapid micron-scale repair capabilities NSF-funded work on PET plastic recycling via hydrolysis Grants & Awards: NSF CAREER Award (2022) ACS Polymers Au: Rising Star (2023) RSC Emerging Investigator (2023) Over 20 patents and 100+ peer-reviewed publications Labs/Teams: Active in the Pester Research Group at UD, collaborating with institutions like TU Braunschweig and Leibniz Institute for Resilience Research on mental health in academia and materials innovation.