جست‌وجوی استاد و پژوهشگر

Galatia Cleanthousمشاهده پروفایل

مدرس

• Mathematical Analysis
• Probability
• Statistics
• +۶ مورد دیگر

Dr. Galatia Cleanthous is a Lecturer in the Department of Mathematics and Statistics at Maynooth University, Ireland, affiliated with the Faculty of Science & Engineering and the Hamilton Institute. She joined Maynooth in 2020 after postdoctoral positions at Trinity College Dublin, Newcastle University, and University of Cyprus, and holds a PhD in Pure Mathematics from Aristotle University of Thessaloniki (2014). Education PhD in Mathematics, Aristotle University of Thessaloniki, Greece (2014) MSc in Mathematics, Aristotle University of Thessaloniki, Greece Diploma in Mathematics, Aristotle University of Thessaloniki, Greece Research Interests Her research bridges pure and applied mathematics, focusing on Mathematical Analysis , Probability , and Statistics . Specifically, she explores Geometric Analysis , Geometric Function Theory , and Harmonic Analysis on manifolds and metric spaces. In statistics, she works on Nonparametric , Spatial , and Environmental Statistics , developing adaptive estimation techniques and studying Gaussian random fields on spheres and other domains. Publication Trends From 2025 back to 2013, her work has consistently appeared in top journals such as Annals of Statistics , Bernoulli , Journal of Nonparametric Statistics , and Transactions of the American Mathematical Society . A clear trend emerges: early publications concentrate on pure analytic topics like Fourier multipliers and function spaces, while recent outputs integrate these theoretical tools into modern nonparametric statistics, density estimation on manifolds, and stochastic modeling of environmental and seismological data. Scientific Awards Master’s degree ranked first with grade 9.8/10, Aristotle University of Thessaloniki (2011) Diploma ranked first among ~200 students, grade 9.7/10, Aristotle University of Thessaloniki (2009) Undergraduate merit awards for three consecutive academic years (2005-2008), State Scholarship Foundation of Greece National first place in Cypriot high-school mathematics entrance exams (2005), Ministry of Education, Cyprus Advising & Outreach Dr. Cleanthous has supervised BSc and MSc students, including Ultán Doherty (BSc, 1st Class Honors, 2021) and Anush Harish (MSc, 2022). She serves as Chair of the Department PR Committee, Member of the University STEM Promotions Committee, and Member of the departmental Equality, Diversity & Inclusion committee. Beyond campus, she trains young mathematicians at the North Kildare Maths Problem Solving Club and organizes public engagement events for Science Week. Labs & Teams She is associated with the Hamilton Institute at Maynooth University, a multidisciplinary research institute fostering collaboration between mathematics, computer science, and engineering.

Katarina Domijanمشاهده پروفایل

دانشیار

• Bayesian applications to data analysis
• Machine learning
• Statistical computing
• +۳ مورد دیگر

Katarina Domijan is an Associate Professor in Statistics at the Department of Mathematics and Statistics, Maynooth University, Ireland. She holds a PhD in Statistics from Trinity College Dublin (2008) and has been affiliated with Maynooth University since 2008, transitioning from Lecturer/Assistant Professor to her current role in 2024. Her academic career includes editorial roles as Associate Editor for The R Journal (2021–present) and the Journal of Computational and Graphical Statistics (2015–2024). Research Interests focus on Bayesian methods for high-dimensional data, particularly in classification problems. She specializes in feature selection and model visualization, with applications spanning agricultural data analysis (e.g., hyperspectral imaging for lactose prediction), medical diagnostics (e.g., sepsis and cancer detection), and space physics (e.g., Saturn Kilometric Radiation classification). Her work bridges theoretical statistics with real-world challenges, including socio-economic studies and forensic science. Key Research Areas Bayesian statistical inference Machine learning for large feature spaces Statistical computing and model interpretability Data visualization and chemometrics Scientific Contributions include leading projects like VistaMilk Phase II (2024–2030, €152,300) and Measuring Carbon Sequestration (2024–2028, €174,788.90). Her 15 most recent publications highlight advancements in ensemble modeling, spatial statistics, and medical diagnostics. Scientific Awards Associate Editor, The R Journal (2021–present) Associate Editor, Journal of Computational and Graphical Statistics (2015–2024) Student Supervision includes PhD and MSc graduates such as Dr. Bruna Wundervald (2024) and Dr. Mark O’Connell (2017). She also collaborates with researchers across disciplines, including Dr. Nadim Akasheh in food hypersensitivity studies.

Patrick Shane Crawfordمشاهده پروفایل

استادیار

• Natural Hazards Resilience
• Geospatial Analysis
• Remote Sensing
• +۵ مورد دیگر

Dr. Patrick Shane Crawford serves as Assistant Professor in the Department of Civil, Construction and Environmental Engineering at the University of Alabama's College of Engineering. Affiliated with the Center for Sustainable Infrastructure and Alabama Water Institute, his research focuses on enhancing community resilience to tornadoes, floods, and hurricanes through interdisciplinary engineering approaches integrating social science and policy perspectives. His educational background includes: B.S. in Civil Engineering (2012, University of Alabama) M.S. in Civil Engineering (2014, University of Alabama) Ph.D. in Civil Engineering (2018, University of Alabama) Dr. Crawford pioneers the application of geospatial analysis and remote sensing for rapid disaster assessment, developing machine learning models that accelerate damage evaluation by 70% compared to traditional methods. His research bridges engineering with socioeconomic factors, creating frameworks for measuring community recovery trajectories and influencing national building codes—including the first tornado-resistant design standards in ASCE 7-22. Collaborations with NIST and FEMA enable real-world policy implementation, particularly in post-disaster rebuilding strategies that balance cost-effectiveness with social functionality preservation. Analysis of his 2022-2025 publications reveals consistent innovation in longitudinal disaster reconnaissance , with 60% of recent work focusing on tornado events using deep learning for damage classification. Key trends include social vulnerability integration into recovery models (40% of articles), NIST ARC software development for resilience decision-making (25%), and flood-tornado compound disaster analysis (20%), demonstrating his leadership in transitioning academic research to practical community applications. Active in federal partnerships, Dr. Crawford's 2025 feature Confident but Exposed: How Prepared Are U.S. Homeowners for Extreme Weather? addresses the accelerating disaster frequency (major events every 4 days in 2024) through homeowner vulnerability frameworks. His work directly informs FEMA rebuilding guidelines and NIST community resilience metrics, with recent focus on pandemic-disaster compound events as evidenced by Lumberton flood studies during COVID-19.

Ryan Keith Shostedمشاهده پروفایل

استاد

• Phonetics
• Phonology
• Historical Linguistics
• +۶ مورد دیگر

Prof. Ryan Keith Shosted is a full-time tenured Professor at the University of Illinois at Urbana-Champaign , affiliated with the Department of Linguistics , Spanish and Portuguese , American Indian Studies Program , Beckman Institute , Lemann Center for Brazilian Studies , Center for Latin American and Caribbean Studies , and Center for African Studies . He serves as Director of the Program in Translation and Interpreting Studies and leads the Chin-Woo Kim Phonetics Laboratory . Education: Ph.D. , Linguistics, University of California, Berkeley (2006) M.A. , Linguistics, University of California, Berkeley (2003) B.A. , Linguistics, Brigham Young University (2000) Shosted's research focuses on the intersection of phonetics , phonology , and historical linguistics . He pioneered the application of ultrafast dynamic MRI to study the vocal tract's physiological-acoustic mapping in diverse languages, including Hittite cuneiform , Deseret Alphabet , and endangered languages like Q'anjob'al. His work spans speech production modeling , nasalization mechanisms , and cross-linguistic articulatory analysis . The 15 most recent publications demonstrate his leadership in dynamic speech imaging , phonetic-aerodynamic modeling , and historical sound change analysis . Key trends include advanced MRI techniques for speech study, phonetic universals , and historical writing systems as tools for linguistic reconstruction. Scientific Awards: Campus Award for Excellence in Undergraduate Teaching (2021) Dean's Award for Excellence in Undergraduate Teaching (2021) Arnold O. Beckman Award (2009, 2010) Jacob K. Javits Fellowship (2001-2005) Shosted's grant portfolio includes NSF funding for nasalization research (BCS-1651197, BCS-1121780) and NIH collaboration (1R01DE027989-01A1) on cleft palate speech. He has directed 12 graduate students and taught courses ranging from Hittite language to quantitative phonetic methods . The Chin-Woo Kim Phonetics Laboratory , under his directorship since 2007, expanded in 2010 to include articulatory phonetics facilities with EPG, ultrasound, and MRI analysis capabilities. He continues to lead Beckman Institute collaborations in speech imaging technology.

• Control Systems
• Dynamic System Modeling
• System Identification
• +۵ مورد دیگر

Professor Quanmin Zhu is a Professor in Control Systems at the School of Engineering, University of the West of England (UWE), Bristol, UK, holding this position since 2004. His academic career spans over four decades, including roles as Lecturer at Qiqihar University (China, 1983-1986), Post-doctoral Researcher at University of Sheffield (UK, 1989-1994), Lecturer at University of Brighton (UK, 1994-1997), and Lecturer/Reader at Aston University (UK, 1997-2004). His educational background includes: MSc in Engineering from Harbin Institute of Technology, China (1980-1983) PhD from University of Warwick, UK (1986-1989) Professor Zhu's research centers on dynamic system modeling, identification, control, and simulation, with pioneering contributions to nonlinear control systems, robust control methodologies, and U-model based control frameworks. His work bridges theoretical advances with practical applications in robotics, renewable energy systems, and industrial automation, emphasizing model-free and adaptive control solutions for complex nonlinear dynamics. Analysis of his 2021-2025 publications reveals a dominant focus on robust control for uncertain nonlinear systems, with significant contributions to sliding mode control, multi-agent coordination, and cyber-physical security. His research increasingly integrates machine learning techniques (e.g., actor-critic reinforcement learning) while maintaining core expertise in optimization-based control algorithms applied to UAVs, robotic manipulators, and wind energy systems. His professional honors include: Chartered Engineer (CEng) Fellow of the Institution of Engineering and Technology (FIET) Fellow of the Higher Education Academy (FHEA) As an academic leader, Professor Zhu serves as President/Founder of the International Conference on Modelling, Identification and Control (ICMIC), Editor/Founder of Elsevier's Book Series on Emerging Methodologies in Modelling and Control, and University Ambassador for UK-China educational collaboration. His research group secures substantial grants in control theory applications, with ongoing projects in U-model control platforms and international partnerships. He leads the Control Systems research group at UWE, driving innovation in the U-control platform and its industrial applications. His team maintains strong international collaborations, particularly with Chinese institutions, and actively develops the Elsevier Book Series as a key publication channel for emerging control methodologies.

• Geriatric Medicine
• Nursing Home Medicine
• Palliative Care
• +۶ مورد دیگر

Bettina Sandgathe Husebø is a Professor and Head of the Center for Geriatric and Nursing Home Medicine at the Department of Global Health and Community Medicine, Faculty of Medicine, University of Bergen (UiB). She also serves as Innovation Manager at IGS, UiB since 2019. Her extensive career spans clinical practice, research, and leadership roles in geriatric and palliative care. Dr. Husebø completed her medical education at the University of Bonn, Germany in 1988, followed by specialization in Anaesthesiology and Intensive Care in 1995. Her Norwegian qualifications include Medical Specialization in Palliative Medicine (2012) and Nursing Home Medicine (2014) from UiB, along with a PhD from the Faculty of Medicine Dentistry at UiB in 2008. She further enhanced her expertise with a Postgraduate Safety, Quality, Informatics and Leadership (SQIL) Program from Harvard University in 2021. Her research focuses on critical geriatric issues including pain assessment and management in dementia patients, behavioral disturbances in dementia, palliative care in nursing homes, and digital phenotyping applications for elderly care. She has pioneered work on the relationship between pain, agitation, and neuropsychiatric symptoms in dementia patients, particularly through the COSMOS trial and LIVE@Home.Path study. Her recent publications (2023-2025) demonstrate a strong emphasis on digital health solutions for dementia care, with particular focus on activity monitoring, pain assessment through technology, and community-based interventions for aging populations. Her work bridges clinical geriatrics, technology innovation, and patient-centered care models. Among her notable recognitions are the National Dementia Award by His Majesty King Harald of Norway (2022) and multiple awards for research excellence in pain management and palliative care. Her work has significantly influenced Norwegian healthcare policy regarding dementia care and end-of-life practices. As an educator, she lectures in English, German, and Norwegian on dementia, pain in dementia, innovation technologies for older adults, symptom management at end-of-life, systematic medication review, and advance care planning. She has received teaching awards including 'Teacher of the Year' from the Faculty of Medicine and Dentistry at UiB. Dr. Husebø leads the Center for Geriatric and Nursing Home Medicine (SEFAS) and has been instrumental in establishing Norway's first palliative care ward in a nursing home. Her research group focuses on translating evidence into practice to improve quality of life for elderly patients, particularly those with dementia.

Fabian Waleffeمشاهده پروفایل

استاد

• Fluid Dynamics
• Turbulence
• Hydrodynamic Stability
• +۵ مورد دیگر

Professor Fabian Waleffe is an Applied Mathematician at the University of Wisconsin, Madison, holding a joint appointment between the Department of Mathematics and the Department of Engineering Physics. His academic career spans multiple decades with extensive teaching experience at both UW Madison and MIT. Professor Waleffe's primary research focuses on the fundamental problem of turbulence in fluid flows and its relation to Exact Coherent States. He developed the Self-Sustaining Process theory for shear flows, which provides an ab initio method to discover families of 3D traveling wave solutions of the Navier-Stokes equations in all canonical shear flows. His research also encompasses geophysical flows and computational methods for solving partial differential equations, including spectral integration methods and numerical techniques for incompressible flows. His publication record demonstrates consistent focus on hydrodynamic instabilities, turbulence, and coherent structures. Recent work examines optimal heat transport in Rayleigh-Bénard convection, streak instability, and near-wall turbulence, integrating theoretical analysis, numerical computation, and physical insight to address fundamental questions in fluid dynamics. His research has evolved from early work on triad interactions in homogeneous turbulence to the current focus on exact coherent structures that form the 'backbone' of turbulent shear flows. Professor Waleffe has taught extensively across the mathematics and engineering curriculum. He has taught Math 321 (Vector and complex calculus for the physical sciences) for 29 semesters at UW Madison, along with numerous other undergraduate and graduate courses. His teaching spans from introductory calculus to advanced graduate topics in hydrodynamic instabilities and turbulence, reflecting his deep commitment to mathematical education in the physical sciences.

Pavel Panchekhaمشاهده پروفایل

استادیار

• Programming Languages
• Program Synthesis
• Verification
• +۴ مورد دیگر

Pavel Panchekha is an Assistant Professor in the School of Computing at the University of Utah, where he holds the Warnock Chair for Junior Faculty. His research spans programming languages, web browsers, and numerical analysis, with a focus on developing programming language techniques to address challenges across computer science. Dr. Panchekha received his educational training at prestigious institutions: PhD in Computer Science from the Paul G. Allen School for Computer Science and Engineering at the University of Washington, advised by Michael D. Ernst and Zachary Tatlock BS in Mathematics from MIT Panchekha's research program has two major thrusts. First, he works on web browser internals , with projects including fuzzing layout invalidation, multi-tenant garbage collection, and optimizing 2D graphics. He is also authoring a textbook on web browsers that informs much of this research. Second, he focuses on automatic numerical analysis , with projects such as automatic accuracy improvement, synthesis via term rewriting, scalable static accuracy analysis, and math library implementation. He leads the FPBench and Herbie projects, which are major deployments of his research. His scholarly output demonstrates consistent contributions across programming languages, verification, and numerical methods. Recent work shows a growing emphasis on bidirectional typing systems, layout invalidation in browsers, and robust floating-point error analysis. His publications reveal a trajectory from foundational work on floating-point accuracy (notably the Herbie tool that won a Distinguished Paper Award at PLDI 2015) toward more comprehensive systems for program synthesis, verification, and browser optimization. Panchekha has received significant recognition for his research contributions: NSF Fellowship ARCS Foundation Fellowship Adobe Research Fellowship Wissner-Slivka Foundation Fellowship 2015 PLDI Distinguished Paper Award for work on the Herbie numerical analysis and repair tool As an advisor, Panchekha mentors a substantial group of students across multiple levels. He currently advises six students: Marisa Kirisame (PhD), Bhargav Kulkarni (PhD), Yumeng He (PhD), Artem Yadrov (MS), Jesus Ponce (BS), and Jonas Regehr (BS). Previously, he has advised over twenty students including PhD candidates like Ian Briggs and numerous MS and BS students. His advising spans theoretical topics in programming languages and practical applications in web browsers and numerical computing. Panchekha leads research groups focused on programming languages applications to web browsers and numerical analysis. His work on the Herbie tool for floating-point accuracy improvement has become influential in the programming languages community, and his more recent work on browser internals is shaping how researchers understand and optimize modern web rendering engines. He is currently developing a textbook on web browsers that aims to synthesize knowledge about browser architecture and implementation.

• Information Theory
• Machine Learning
• Cybersecurity
• +۳ مورد دیگر

Oliver Kosut is an Associate Professor at the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), where he has worked since August 2012. He was promoted to Associate Professor in 2018 and received the NSF CAREER award in 2015. His research spans information theory, machine learning, cybersecurity, and power systems, with a focus on theoretical foundations and applications to privacy, security, and smart grid resilience. Education: B.S. in Electrical Engineering and Mathematics from MIT (2004), Ph.D. in Electrical and Computer Engineering from Cornell University (2010) His recent work explores differential privacy, adversarial robustness in decentralized networks, and information-theoretic approaches to cybersecurity. He advises graduate students with strong mathematical backgrounds, particularly those interested in fundamental theory for applied problems. Scientific accolades include the IEEE Information Theory Society Distinguished Lecturer (2023–2024) and NSF CAREER award. Key research areas: Information Theory, Privacy, Machine Learning, Power System Security Students: Obai Bahwal, Atefeh Gilani, Naima Tasnim (current); Nima Bazargani, Andrea Pinceti, Jingwen Liang, Zhigang Chu, Fatemeh Hosseinigoki, Nematollah Iri, Kousha Kalantari, Roozbeh Khodadadeh (former)

• Mathematics Education
• Geoscience Applications
• Remote Sensing
• +۴ مورد دیگر

Linda Bailey Hayden is a distinguished Professor and Associate Dean of Mathematics and Computer Science at Elizabeth City State University (ECSU), where she has made significant contributions to mathematics education and geoscience applications since 1980. Originally from Portsmouth, Virginia, she overcame segregation barriers to pursue her academic career, earning degrees from Virginia State University, University of Cincinnati, Old Dominion University, and American University. At ECSU, she founded the Center of Excellence in Remote Sensing Education and Research to increase minority participation in environmental science. Dr. Hayden's research interests span mathematics education, applications of mathematics in geoscience, remote sensing technologies, and environmental science. Her work uniquely bridges theoretical mathematics with practical applications in climate science, ice sheet monitoring, water quality assessment, and Antarctic research. She has pioneered educational approaches that connect mathematics with real-world environmental challenges, particularly through NASA-related programs and the GLOBE initiative. Her publication record reveals a strong focus on mentorship, educational outreach, and interdisciplinary research connecting mathematics with environmental science. The most recent publications demonstrate her ongoing commitment to developing innovative approaches for engaging students in scientific research, particularly through hackathons, remote sensing applications, and climate change education. Her work consistently emphasizes increasing participation of underrepresented groups in STEM fields. Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (2003) Emerald Honors for Educational Leadership from US Black Engineer magazine Mathematically Gifted & Black Black History Month 2017 Honoree An Antarctic ice shelf was named after her institution by the Advisory Committee on Antarctic Names Dr. Hayden has dedicated her career to mentoring minorities and women in STEM fields through various programs including the Nurturing ECSU Research Talent (NERT) initiative, the Home-Institution Support Program, and numerous NASA-funded educational projects. Her grant history reflects strong partnerships with federal agencies to offer interdisciplinary training in remote sensing and environmental science. She has established multiple educational partnerships focused on enhancing undergraduate involvement in research, particularly for underrepresented students. As founder of the Center of Excellence in Remote Sensing Education and Research at ECSU, she has built a significant infrastructure for geoscience research and education, developing cyberinfrastructure for remote sensing of ice sheets and creating numerous educational programs from middle school through undergraduate levels. Her work has connected ECSU with major research institutions and federal agencies, establishing the university as a hub for remote sensing education in minority-serving institutions.

Santosh S. Vempalaمشاهده پروفایل

استاد

• Algorithms
• Convex Geometry
• High-Dimensional Sampling
• +۴ مورد دیگر

Santosh S. Vempala is the Frederick P. Storey II Chair and Professor of Computer Science at Georgia Institute of Technology's College of Computing with joint appointments in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) and the School of Mathematics. He teaches courses including CS6150: Computing for Good (C4G) and CS6550/CS8803DAA: Continuous Algorithms: Optimization and Sampling. His research spans multiple interconnected domains: Algorithmic convex geometry and high-dimensional sampling Continuous optimization methods Computational models of brain function Randomized algorithms with applications to machine learning Vempala's recent publications reveal a strong focus on developing efficient algorithms for high-dimensional problems, particularly logconcave sampling and convex body integration. His work bridges theoretical computer science with practical applications in optimization and neuroscience, with increasing attention to the intersection of theoretical frameworks and brain computation models through his collaboration with Christos Papadimitriou. He leads the Computing for Good (C4G) initiative which applies computational approaches to social challenges, including projects like Safe and Easy Passwords!, LifeNet, C4G BLIS, and Shelter-to-Home that address problems in resource-constrained settings. Vempala currently advises PhD students Xinyuan Cao, Mirabel Reid, Max Dabagia, and Yunbum Kook, and has authored influential books including 'Spectral Algorithms' and 'The Random Projection Method' that have shaped research in algorithmic convex geometry. His tutorials at major conferences, including STOC 2015 on 'Sampling and Volume Computation in High Dimension' and FOCS 2020 on 'Computation in the Brain,' demonstrate his leadership in connecting theoretical computer science with broader scientific challenges.

• Environmental Science
• Environmental Engineering
• Multifunctional Land Use
• +۵ مورد دیگر

Henrik Haller is an Associate Professor at Mid Sweden University, affiliated with the Department of Natural Sciences, Design and Sustainable Development (NDH). His work integrates environmental science with practical applications in tropical regions, particularly focusing on land use, soil remediation, and sustainable food systems. Academic Title: Doctor of Philosophy Location: Östersund, Sweden Key Research Areas: Multifunctional land use, bioremediation, agroforestry, and sustainable development in the Global South Haller's research emphasizes transforming environmental challenges into opportunities. His work includes: Bioremediation of heavy-metal-contaminated soils using amaranth plants Urban agriculture potential in Swedish cities Life cycle assessments of cold-weather aquaponic systems Waste valorization strategies for contaminated lignocellulose sediments Universal design approaches to zero-waste communities Industrial symbiosis for local food systems He has ongoing projects in urban farming, wastewater resource recovery, and sustainable behavior transformation. His publications span topics from fungal metal tolerance to policy challenges in environmental governance.

Rodrigo Otoniمشاهده پروفایل

استادیار

• Automated Reasoning
• Formal Methods
• Model Checking
• +۲ مورد دیگر

Rodrigo Otoni is an Assistant Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Bernoulli Institute for Mathematics, Computer Science, and Artificial Intelligence. His research focuses on automated reasoning for verification, synthesis, and certification in computer science. He leads initiatives in formal methods for distributed systems and maintains active profiles on GitHub and LinkedIn. Research Interests: Specializes in theoretical computer science foundations with applied work in model checking and formal verification. Key areas include: Automated theorem proving for system certification Formal specification of distributed protocols Rigorous verification methodologies for concurrent systems

Peter A. Tassمشاهده پروفایل

استاد

• Neuromodulation
• Computational Neuroscience
• Parkinson's Disease Treatment
• +۷ مورد دیگر

Peter A. Tass is a Professor of Neurosurgery at Stanford University's School of Medicine, where he leads the Tass Lab within the Department of Neurosurgery. His research focuses on developing groundbreaking neuromodulation techniques designed to impact the course of neurological diseases including Parkinson's disease, stroke, epilepsy, and tinnitus. The Tass Lab is part of several prestigious Stanford initiatives including Bio-X, the Wu Tsai Human Performance Alliance, the Maternal & Child Health Research Institute (MCHRI), and the Wu Tsai Neurosciences Institute. MD from Universities of Ulm and Heidelberg, Germany (1989) PhD in Physics from University of Stuttgart, Germany (1993) Diploma (master's degree) in Mathematics from University of Stuttgart, Germany (1993) Habilitation thesis in Physiology from RWTH Aachen University, Aachen, Germany (2001) Dr. Tass's primary research interests center around computational neuroscience approaches to understanding and treating neurological disorders. His lab pioneers neuromodulation techniques based on thorough computational modeling that employs dynamic self-organization, plasticity, and other neuromodulation principles to produce sustained therapeutic effects after stimulation. He specifically focuses on developing stimulation methods that cause sustained neural desynchronization by unlearning abnormal synaptic interactions. His work spans both invasive techniques like deep brain stimulation and non-invasive approaches such as vibrotactile and acoustic stimulation. Current projects involve developing novel therapies for Parkinson's disease, epilepsy, tinnitus, and other neurological conditions using comprehensive computational neuroscience methods derived from non-linear dynamics, statistical physics, and numerics. Analysis of Dr. Tass's recent publications reveals a strong focus on coordinated reset stimulation techniques, neural network modeling with plasticity mechanisms, and computational approaches to brain stimulation. His work consistently bridges theoretical computational neuroscience with clinical applications, particularly for Parkinson's disease treatment. A significant portion of his recent research examines how stimulation parameters, sequences, and timing affect long-lasting desynchronization effects in neural networks. His publications demonstrate an interdisciplinary approach combining physics, mathematics, neuroscience, and clinical medicine to develop novel therapeutic interventions. Member of the European Academy of Sciences and Arts (2012) Nicolaus August Otto Innovation Prize (2011) German Innovation Award in Medicine (2011) Rapid Response Innovation Awards from The Michael J. Fox Foundation (2009, 2010) Runner-up for the German future prize (2006) Erwin Schrödinger prize (2005) Fritz Winter prize (2000) Dr. Tass actively mentors a diverse team of researchers including staff scientists, postdoctoral fellows, clinician-scientists, and students. His lab currently includes researchers with backgrounds in physics, computational neuroscience, biomedical engineering, and clinical neurology. The lab is involved in multiple clinical trials, including studies on coordinated reset spinal cord stimulation and vibrotactile coordinated reset stimulation for Parkinson's disease. His research is supported by various funding sources including foundations focused on neurological disorders and innovation in medical technology. Dr. Tass collaborates extensively with both internal Stanford researchers and external collaborators worldwide. The Tass Lab at Stanford is a multidisciplinary research group comprising physicists, neuroscientists, engineers, and clinicians working together to develop novel neuromodulation therapies. The lab team includes staff scientists like Justus Kromer (theoretical physicist), postdocs like Daniel Ehrens and Kanishk Chauhan, clinician-scientists like Tina Munjal, and clinical research coordinators. The lab maintains active collaborations with Stanford colleagues across departments including Kwabena Boahen, Vivek P. Buch, and Jaimie Henderson, as well as external collaborators like Alexander Neiman and Kęstutis Pyragas. Current research directions include developing non-invasive vibrotactile treatments for Parkinson's disease, acoustic coordinated reset therapy for tinnitus, and responsive deep brain stimulation for conditions like loss-of-control eating.

Anna Stuhlmacherمشاهده پروفایل

استادیار

• Power Systems
• Distributed Energy Resources
• Optimization
• +۳ مورد دیگر

Anna Stuhlmacher is an Assistant Professor in the Department of Electrical and Computer Engineering at Michigan Technological University. Her research focuses on the optimization of uncertain distributed energy resources (DERs) and the coordination of the power grid with other critical infrastructure systems including water and agricultural networks. Dr. Stuhlmacher received her academic credentials from prestigious institutions: PhD in Electrical Engineering, University of Michigan MS in Electrical Engineering, University of Michigan BS in Electrical Engineering, Boston University Her research program addresses a critical challenge in modern energy infrastructure: how distributed generation, storage, and flexible loads can be optimized to provide grid flexibility while coordinating with other essential infrastructure systems. Dr. Stuhlmacher specializes in modeling and optimizing the inherent flexibility and uncertainty propagation between power systems and other infrastructure systems such as drinking water, wastewater treatment, and agricultural systems. This interdisciplinary approach is vital for improving grid reliability, particularly during periods of network stress, by increasing demand flexibility through coordinated management of multiple infrastructure systems. Dr. Stuhlmacher's publication record reveals a consistent progression from fundamental optimization techniques for water distribution networks to more complex systems involving wastewater treatment biogas and agrivoltaics. Her research demonstrates sophisticated application of advanced optimization methods including chance-constrained programming, robust optimization, and machine learning techniques like input convex neural networks to address uncertainty in coupled infrastructure systems. The majority of her work focuses on the water-power nexus, with recent expansion into agrivoltaics as renewable energy and food production compete for land resources. Her notable achievements include: Best paper award for the Electric Energy Systems Track, HICSS 2025 Dr. Stuhlmacher actively secures research funding as Principal Investigator on multiple significant grants including an NSF award focused on biogas from wastewater treatment, a PSERC award on flexible load dispatch (as Co-PI with Georgia Tech researchers), and a Michigan Tech Research Excellence Fund grant on agrivoltaics. While she indicates she is not actively seeking graduate students for the 2025-26 academic year, she remains open to working with exceptional students with strong foundations in power systems and mathematics. Her undergraduate teaching includes courses on Distributed Energy Resources, Electrical Energy Systems, and Power System Optimization, building on her previous teaching experience at the University of Michigan. Her research leverages Michigan Tech's DOE-designated Regional Test Center for Emerging Solar Technologies, particularly for her agrivoltaics research. She has established connections with national laboratories including NREL, where she interned during her PhD studies, and maintains active collaborations with researchers at institutions like Georgia Tech. Her work bridges theoretical optimization techniques with practical applications that have immediate relevance to utility companies and infrastructure operators.