جست‌وجوی استاد و پژوهشگر

• Neuromodulation
• Chronic Pain Management
• Spinal Cord Stimulation
• +۳ مورد دیگر

Scott F. Lempka, PhD, serves as an Associate Professor in the Department of Biomedical Engineering at the University of Michigan, Ann Arbor, with a secondary appointment in the Department of Anesthesiology. He leads the Neuromodulation Laboratory and directs Neuromodulation initiatives within the Chronic Pain and Fatigue Research Center, focusing on engineering approaches to advance neurostimulation therapies for chronic pain and neurological disorders. His academic foundation includes: B.S. in Biomedical Engineering from Saint Louis University (2004) M.S. and Ph.D. in Biomedical Engineering from Case Western Reserve University (2008, 2010) Postdoctoral training at the Cleveland Clinic and Louis Stokes Cleveland VA Medical Center Dr. Lempka's research centers on computational and experimental characterization of neuromodulation mechanisms, with three primary thrusts: neurostimulation for chronic pain (investigating therapeutic mechanisms to innovate pain management technologies), spinal cord stimulation (elucidating physiological effects of conventional and novel waveforms), and neural engineering (developing computational models to optimize neural stimulation and recording interfaces). His work bridges engineering principles with clinical neuroscience to enhance therapeutic precision. Analysis of his 2025 publications reveals a pronounced focus on ultra-low frequency neuromodulation, computational modeling of spinal cord stimulation effects, and novel electrode design for targeted neural activation. Key trends include quantitative characterization of evoked compound action potentials, thalamic modulation mechanisms in pain pathways, and engineering solutions for sensory restoration in amputees—demonstrating a cohesive effort to translate computational insights into clinically viable neurotechnologies. His research program is currently supported by three major NIH-funded projects: R01 AT010817 (NCCIH): Model-based characterization of spinal cord stimulation for pain R01 NS121028 (NINDS): Electrode design for selective spinal cord stimulation to restore sensation after lower-limb amputation RM1 NS128775 (NINDS): Defining mechanisms of pain relief in dorsal root ganglion and spinal cord stimulation As Principal Investigator of the Neuromodulation Laboratory, Dr. Lempka integrates computational modeling with experimental validation in swine and rodent models, collaborating closely with the Chronic Pain and Fatigue Research Center to accelerate the development of next-generation neurostimulation therapies with improved clinical outcomes.

Adrien Thobمشاهده پروفایل

پژوهشگر

• Galaxy Formation
• Cosmological Simulations
• Synthetic Observations
• +۴ مورد دیگر

Adrien Thob is a Postdoctoral Researcher at the University of Pennsylvania's Department of Physics & Astronomy, part of the Galaxy Dynamics @ UPenn group led by Prof. Robyn Sanderson. He holds a PhD in Galaxy Formation & Computational Cosmology from Liverpool John Moores University (UK), an M.Sc. in Astronomy from the Observatoire de Paris-Meudon (France), and an engineering degree in Telecommunication and Signal Processing from IMT Atlantique (France). His research focuses on galaxy formation mechanisms using cosmological simulations (EAGLE, E-MOSAICS, FIRE) and synthetic observations for telescopes like Roman and JWST. He develops Python-based tools such as wpipe (pipeline manager), dustpy (radiative transfer), and py-ananke (synthetic observation wrapper). His work bridges engineering and astrophysics, leveraging high-performance computing and software engineering skills. Outreach activities include creating simulation visualizations featured in planetarium shows and his Vimeo channel. Notable contributions include analyzing dark matter halo structures' impact on galaxy morphology and kinematics, published in MNRAS and presented at conferences like EWASS 2018.

• Epilepsy Treatment
• Neurological Surgery
• Deep Brain Stimulation
• +۳ مورد دیگر

Robert Gross is a Lecturer in the Department of Health Policy and Management at Emory University. His research focuses on advanced neurosurgical techniques, particularly in epilepsy treatment, deep brain stimulation (DBS), and minimally invasive therapies like laser ablation. He explores the neurophysiological mechanisms underlying neurological disorders and develops innovative tools for clinical intervention. His work emphasizes translational research, combining neurotechnology with clinical outcomes. Notable contributions include advancements in stereotactic laser amygdalohippocampotomy, optogenetic approaches for seizure control, and studies on DBS efficacy in Parkinson’s disease and depression. Publications highlight a consistent focus on epilepsy surgery optimization, DBS parameter refinement, and neuroimaging-guided therapies. His articles often address technical challenges in neurosurgery and the physiological impacts of stimulation patterns. No scientific awards were explicitly mentioned in the provided texts. Advising and grant activities are not detailed here, though his prolific publication record suggests active research engagement.

Harsha K. Chelliahمشاهده پروفایل

استاد

• Combustion
• Fluid Mechanics
• Chemical Kinetics
• +۴ مورد دیگر

Harsha K. Chelliah is a Professor in the Department of Mechanical & Aerospace Engineering at the University of Virginia. He joined the university in 1992 after completing his PhD at Princeton University. His research focuses on combustion science, fluid mechanics, and chemical kinetics, with applications to hypersonic propulsion, fire suppression, and ceramic material synthesis. He holds prestigious fellowships from the Combustion Institute and ASME, and has held visiting roles at Cambridge University. Education: B.S., Mechanical Engineering, University of Moratuwa, Sri Lanka (1981) M.S., Mechanical Engineering, SUNY Stony Brook (1984) Ph.D., Mechanical & Aerospace Engineering, Princeton University (1989) Research Interests: Professor Chelliah’s work addresses fundamental interactions between chemical kinetics and fluid dynamics. Key areas include: Combustion phenomena in hypersonic engines and gas turbines Soot formation and suppression mechanisms Chemical vapor infiltration for SiC ceramics Flame-acoustic interactions and turbulence effects Grants & Projects: AFOSR-NSF: Combustion model validation for hypersonic propulsion Rolls Royce: Soot oxidation studies in turbine engines NASA-AFOSR: Hypersonic combined-cycle propulsion research Labs & Teams: He directs the Reacting Flow Lab , focusing on experimental and computational combustion studies. His team collaborates with industry partners like Rolls Royce and NASA to advance propulsion and material science technologies.

• Spatial Statistics
• Point Process Modeling
• Mathematical Operations Research
• +۳ مورد دیگر

Marie-Colette van Lieshout is a Full Professor holding dual roles in the Digital Society Institute and the Department of Mathematics of Operations Research. Her research focuses on spatial statistics, point processes, and statistical modeling applied to earth sciences and computational methods. She contributes to UN Sustainable Development Goals through work on seismic hazard monitoring, stochastic processes, and risk management. Key activities include organizing conferences like Spatial Statistics 2022 and serving on editorial boards. She has published extensively, with datasets deposited in 4TU.Centre for Research Data. Education: Not explicitly detailed in text. Research Interests: Spatial and spatiotemporal statistical models Point process analysis and applications in environmental science Renewal processes and interval censoring methods Mathematical foundations of operations research Recent Article Trends: Focus on stochastic modeling for seismic hazards, Markov decision processes, and semi-Markov systems. Contributions bridge theoretical probability and applied geophysics. Awards: None explicitly mentioned. Advising & Grants: Supervised 3 works (names unspecified). Active in conference organization and editorial roles. Labs/Teams: Collaborates on fire risk management (via datasets) and participates in international statistics networks.

Wei Liمشاهده پروفایل

پژوهشگر ارشد

• Photovoltaic Engineering
• Materials Science
• Renewable Energy
• +۲ مورد دیگر

Wei Li is a Research Fellow in the Department of Chemical and Biological Engineering at Monash University. Previously, he was an associate researcher in the Cu2ZnSnS4 Group at UNSW's School of Photovoltaic and Renewable Energy Engineering. His research focuses on photovoltaic engineering, materials science, and renewable energy technologies, particularly crystalline silicon thin-film solar cells. Education credentials: PhD in Photovoltaic Engineering from University of New South Wales (2013) Master's in Materials Science from Wuhan University of Technology (2009) Bachelor's in Materials Science from Wuhan University of Technology Research interests center on advanced materials for solar energy conversion, photocatalytic processes, and functional nanomaterials. His work spans fundamental material development to practical applications in energy and environmental technologies. Publications demonstrate expertise in photocatalyst design, material characterization, and process optimization. Recent work focuses on methane photocatalytic conversion, MOF-based adsorption systems, and functional coatings for biomedical applications. Research frequently employs advanced computational modeling alongside experimental validation. Scientific awards: No awards reported in available materials. Laboratory affiliations include Monash's chemical engineering research facilities. Industry collaborations not specified in available documentation.

Yeongkwon Sonمشاهده پروفایل

استاد پژوهشی

• Environmental Health
• Exposure Science
• Risk Assessment
• +۴ مورد دیگر

Dr. Yeongkwon Son is an Associate Research Professor at the Organic Analytical Laboratory, Desert Research Institute (DRI). His research focuses on environmental pollutants exposure, particularly in the context of health impacts, with expertise in exposure science, chemical analysis, computational modeling, and sampling device design. He holds a PhD from Rutgers University, where he conducted studies on air pollution and asthma in children. Dr. Son's early career involved watershed management and public health outcomes, including developing the Natural and Ecological Wastewater Treatment System (NEWS) for rural communities in South Korea and Swaziland. He has led over 10 projects assessing water pollutants' ecological impacts. His current work extends to e-cigarette emissions, wildfire smoke health risks, and low-cost sensor networks for environmental monitoring. His research interests span environmental health, exposure science, risk assessment, and environmental modeling. Notable projects include modeling wildfire smoke effects on grapes and wines, PFAS contamination in Nevada hot springs, and evaluating low-cost air quality sensors for wildland fire monitoring. He has contributed to studies on passive aerosol exposure in vape shops and the health risks of e-cigarette use patterns. Dr. Son collaborates with diverse stakeholders, including the Nevada Governor’s Office on virus transport mitigation and the Bureau of Land Management on water quality. He leads the Organic Analytical Laboratory at DRI, advancing analytical methods for environmental and health research.

Yan Wangمشاهده پروفایل

دانشیار

• Thermal Engineering
• Nanotechnology
• Materials Science
• +۳ مورد دیگر

Yan Wang is an Associate Professor in the Department of Mechanical Engineering at the University of Nevada, Reno (UNR). He specializes in micro-/nano-scale thermal phenomena, energy materials, and computational modeling of thermal transport processes. His work focuses on advancing thermal management solutions for electronics, energy storage systems, and nanomaterials. Dr. Wang is affiliated with the College of Engineering and maintains active research collaborations across disciplines. Research Interests Micro-/nano-scale heat and mass transfer Thermal-mechanical properties of advanced materials Thermal characterization techniques Energy conversion and storage materials Laser-based manufacturing thermal analysis His recent publications emphasize coherent phonon dynamics, interfacial thermal transport, and applications of graphene-based nanomaterials. Dr. Wang oversees a research group offering assistantships in mechanical, electrical engineering, and materials science. He teaches courses including ME 314 (Heat Transfer), ME 414/614 (Intermediate Heat Transfer), and ME 758 (Thermal Analysis of Nanomaterials). Labs/Teams Dr. Wang's research group focuses on experimental and computational studies of thermal phenomena at the nanoscale, with applications in energy and electronics. Prospective students are invited to contact him directly for opportunities.

Pengbo Chuمشاهده پروفایل

استاد

• Mineral Processing
• Interfacial Phenomena
• Machine Learning Applications
• +۳ مورد دیگر

Pengbo Chu is the Nevada Gold Mines Professor in the Department of Mining and Metallurgical Engineering at the University of Nevada, Reno. His role is supported by a visiting professorship funded by Nevada Gold Mines, established in 2010. He holds a Ph.D., M.Eng., and B.Eng. in Mechanical and Materials Engineering from McGill University, Canada. His research focuses on interfacial phenomena in mineral processing, including bubble-particle interactions, machine learning applications for system optimization, and dry processing techniques. He also explores sustainable methods for critical mineral extraction from primary and secondary resources. Dr. Chu teaches advanced mineral processing and comminution courses. His recent work emphasizes environmental and economic sustainability in mining, with articles addressing nickel sulfide tailings recovery, lithium extraction from claystones, and VR-based educational tools. He has contributed to reviews on froth flotation for e-waste recycling and particle tracking technologies. Dr. Chu's professional experience includes roles at CanmetMINING, Novelis, and Pulp and Paper Research Center. He actively collaborates with industry partners like Nevada Gold Mines to advance practical applications of mineral processing innovations.

Sonya A Brownمشاهده پروفایل

مدرس ارشد

• Aerospace Engineering
• Composite Materials
• Structural Design
• +۳ مورد دیگر

Dr. Sonya A Brown is a Senior Lecturer in Aerospace Design at the School of Mechanical and Manufacturing Engineering, UNSW. Her research focuses on aerospace design, composite materials, and manufacturing technologies, with a particular emphasis on carbon fiber composites and structural supercapacitors. She collaborates with organizations such as the Defence Science and Technology Group and Quickstep Technologies. Education: Doctor of Philosophy, School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney (2012) Bachelor of Engineering (Aeronautical, Honours Class I with University Medal), University of Sydney (2007) Research Interests: Dr. Brown’s work spans multifunctional composites, automated fiber placement (AFP), hypersonic materials, and crash investigation. Her projects include developing conductive carbon composites for electromagnetic interference protection and optimizing manufacturing processes for aerospace components. She also explores sustainable materials and energy storage solutions within composite structures. Key Collaborations: Defence Science and Technology Group (DST) Axowind Holdings Quickstep Technologies Public Engagement: Dr. Brown is a frequent commentator on aviation safety and emerging technologies, including flying cars and hypersonic travel. She has provided expert analysis on high-profile incidents such as the Ethiopian Airlines Flight 302 disaster and the Boeing 737 MAX controversies. Professional Affiliations: Member of the Royal Aeronautical Society (MRAeS) Senior Member of the American Institute of Aeronautics and Astronautics (AIAA) Member of Engineers Australia (MIEAust)

• Composite Materials
• Mechanical Engineering
• Thermal Analysis
• +۷ مورد دیگر

Anirudh Kohli is a Researcher in the Department of Materials, focusing on composite materials, mechanical engineering, and thermal analysis. His work contributes to UN Sustainable Development Goals related to sustainable materials and innovation. Education: Doctor of Philosophy in Materials Engineering (ongoing) Master of Science in Composite Materials (Nanyang Technological University, 2023) Bachelor of Technology in Materials Science (KLE Technological University, 2015) Research interests include additive manufacturing, biodegradable materials, automotive thermal analysis, dental prosthetics, and natural fiber composites. His work combines experimental techniques (e.g., X-ray tomography, DSC/TGA) with computational modeling (e.g., ANSYS simulations). Publications highlight innovations in 3D-printed composites, automotive brake disc thermal performance, and eco-friendly materials for dentistry and footwear. Collaborations span academic and industrial partners in materials science and engineering. No scientific awards explicitly listed. Advising and grant details not provided in the text.

Itzhak Friedمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Neuroscience
• Memory Consolidation
• +۴ مورد دیگر

Itzhak Fried is a Professor-in-Residence in Neurosurgery and Psychiatry & Biobehavioral Sciences at the David Geffen School of Medicine, UCLA . His work bridges epilepsy surgery and cognitive neuroscience , focusing on single-neuron activity during memory, navigation, and consciousness studies. Key research areas: neural coding of memory , theta oscillations , epileptic network analysis , and brain-computer interfaces . Current NIH-funded projects: Decoding and modulating human memory via deep brain stimulation (U01NS123128), sleep-dependent memory consolidation (U01NS108930), and mechanisms of memory enhancement (R01NS084017). Recent publications analyze fast ripple networks in epilepsy, neural dynamics of navigation , and modulation of speech-related neurons in Parkinson's disease. His team develops wearable neurostimulation platforms and machine learning tools for seizure detection, while exploring consciousness and volition through intracranial recordings.

Kevin Yuمشاهده پروفایل

پژوهشگر

• Machine Learning
• Algorithms
• Software Engineering
• +۷ مورد دیگر

Kevin Yu is a Researcher at the Department of Computational Science and Engineering (CSE) at MIT. His research focuses on machine learning, algorithms, and software engineering for synthetic chemistry, alongside advancements in photonics, quantum sensing, and detector technology. Yu holds a B.S. in Chemistry and Computer Science from Caltech (2022). He collaborates with Connor Coley as his research advisor, contributing to projects like the Lynx X-ray Microcalorimeter and Europa lander sensor concepts. His work spans semiconductor devices, superconducting sensors, and space instrumentation, with publications emphasizing high-fidelity detection systems and detector array innovations. Notably, Yu’s research addresses challenges in X-ray imaging, quantum computing, and environmental monitoring through interdisciplinary approaches. Education: B.S. in Chemistry & Computer Science (Caltech, 2022) Research interests integrate computational methods with experimental physics. Recent articles highlight breakthroughs in Geiger-mode avalanche photodiodes, integrated photonics for quantum sensing, and magnetic microcalorimeter arrays. His detector designs aim to enhance resolution and reliability in astrophysics missions and quantum systems. Yu’s contributions also include advancements in direct-detection LIDAR for planetary exploration and radiation-hardened sensors for extreme environments. Collaborative efforts with NASA missions like REXIS and Lynx underscore his role in bridging lab innovations with real-world space applications. Grant activities involve developing next-generation X-ray detectors and superconducting interconnects for large-scale arrays. Future work emphasizes scaling quantum sensor platforms and improving detector robustness for harsh conditions.

Sebastian Elbaumمشاهده پروفایل

استاد

• Software Engineering
• Autonomous Systems
• Robotics
• +۴ مورد دیگر

Sebastian Elbaum is a Professor of Computer Science at the University of Virginia's School of Engineering and Applied Science. His research focuses on Software Engineering and Autonomous Systems, with a particular emphasis on safety-critical systems, robotics, and deep learning verification. He leads projects addressing challenges in autonomous vehicle validation, neural network testing, and robotic system reliability. Notably, he is an ACM Fellow, recognizing his contributions to advancing software engineering and autonomous systems research. His work spans theoretical frameworks (e.g., SGSM for safe driving properties) to applied solutions like aerial robotics for environmental tasks. Key Research Themes: Autonomous Systems Safety and Validation Testing of Deep Neural Networks Robotics Software Engineering Cyber-Physical Systems Recent Contributions: Development of frameworks for adversarial testing in autonomous vehicles Advancements in scene graph-based safety monitoring Tools like DNNV for neural network verification His research often bridges academic theory with real-world applications, such as using drones for wildfire management (e.g., fire ignition via UAS) and improving TCP protocol testing. He collaborates on interdisciplinary projects funded by NSF and industry, addressing challenges in robotics, AI ethics, and system reliability.

Lee Cunninghamمشاهده پروفایل

دانشیار

• Structural Engineering
• Coastal Resilience
• Computational Mechanics
• +۴ مورد دیگر

Lee Cunningham is Reader in Civil Engineering and Management at the University of Manchester, leveraging 11+ years of industry experience in structural and coastal engineering. Chartered as both Civil and Structural Engineer, his research focuses on resilience of infrastructure against extreme environmental loading (floods, tsunamis, fire) using advanced computational modeling. Key qualifications: PhD in Structural Engineering (University of Glasgow, 2000) MEng (University of Strathclyde) Research spans: Performance of concrete, steel, timber and composite structures under extreme conditions Tsunami impact modeling using SPH methods Sustainable materials development including graphene-enhanced concrete Coastal defense system design Publications demonstrate strong emphasis on computational methods (65%) and experimental validation (35%), with recent focus on climate-resilient infrastructure. Thematically, 40% address coastal/flood hazards, 30% fire engineering, and 30% sustainable materials. Leadership includes heading the Structures in Extreme Environments research group and serving on editorial boards of major engineering journals. Awarded five national prizes including ICE Telford Premium (2014, 2016) for contributions to computational mechanics.