Find Academic Supervisors

Meagan WoodView profile

Assistant Professor

• Cognitive Psychology
• Aging and Cognition
• Memory Research
• +3 more

Dr. Meagan Wood is an Assistant Professor at Valdosta State University's Psychology Department. Her research focuses on cognitive aging, memory processes, and decision-making across the lifespan. She investigates topics such as semantic satiation in aging populations, Alzheimer's disease neuroimaging, and intergenerational dynamics. Her work also addresses applied areas like face mask attitudes during pandemics and academic entitlement in students. Dr. Wood has published extensively in journals covering cognitive neuroscience, gerontology, and educational psychology. Key research interests include aging cognition, neuropsychological mechanisms, and behavioral interventions. Her studies often employ fMRI techniques and behavioral experiments to explore how aging affects cognitive functions like memory encoding and attention. She has explored the impact of optimism on aging perceptions and designed intergenerational video game interventions to improve young adults' understanding of aging. Dr. Wood's publications span 2009 to 2023, reflecting a trajectory from early work on family arrangements and aging perceptions to recent studies on pandemic-related behavioral psychology. Though no awards are listed, her active research profile indicates ongoing contributions to cognitive aging research. No advising or grant details are available in the provided texts.

• Biomedical Engineering
• Cardiac Electrophysiology
• Neural Interfaces
• +5 more

Overview Amr Al Abed is a Senior Lecturer at the Graduate School of Biomedical Engineering, University of New South Wales . He specializes in computational modeling, biomedical instrumentation, and electrophysiology with a focus on cardiac and neural systems. His work bridges biocomputational simulations with experimental validation, emphasizing translational applications like gene therapy delivery, medical devices, and brain-machine interfaces. Education PhD in Biomedical Engineering (UNSW, 2012) Masters in Biomedical Engineering (UNSW, 2006) Bachelor of Medical Sciences (1st Class Honours, UNSW, 2004) Research Interests His research spans: Optrode Technology: Development of liquid crystal-based optrodes for neural and cardiac sensing. Gene Electrotransfer: Novel methods for targeted DNA/RNA delivery using conductivity-clamped electric fields. Computational Cardiology: Multi-physics models of heart mechanics and fluid dynamics for surgical planning and device design. Neural Interfaces: Bidirectional stimulation/detection systems for retinal and neural prosthetics. Publications His 2023-2025 work highlights advancements in flexible electrode arrays , motorless robotic systems , and deep tissue gene delivery . Key themes include biomedical device innovation, computational modeling of cardiovascular systems, and neurotechnology. Grants & Labs Leads projects on liquid crystal optrodes and electrotransfer systems. Collaborates with labs focused on neural interfaces and cardiac electrophysiology. Active in IEEE and SPIE conferences with over 70 peer-reviewed publications.

Tianbai XiaoView profile

Researcher

• Numerical Analysis
• Applied Mathematics
• Kinetic Theory
• +7 more

Tianbai Xiao is a Researcher at the Karlsruhe Institute of Technology (KIT) within the Department of Mathematics and Steinbuch Centre for Computing. His work spans mesoscopic science , uncertainty quantification , and scientific machine learning , focusing on multi-scale, multi-physics problems in flow transport. His research in kinetic theory addresses nonlinear partial differential equations, hyperbolic conservation laws, and the unified modeling of continuum/rarefied flows. He develops high-performance numerical algorithms like the Unified Gas-Kinetic Scheme (UGKS) and Kinetic.jl (a finite volume toolbox for scientific computing). Current projects include mesoscopic science , stochastic data science , and physics-informed neural networks . He contributes to open-source tools including FluxReconstruction.jl for advection-diffusion methods and Langevin.jl for stochastic kinetic modeling. Publications cover Journal of Computational Physics , Engineering Fracture Mechanics , and Entropy , with preprints on arXiv in 2025 addressing force-driven flows and hybrid peridynamics. Teaching activities include the Introduction to Kinetic Theory lecture at KIT, and mentoring in the CAMMP (Computational and Mathematical Modeling Program) to develop problem-solving skills through real-world modeling tasks. He advocates for problem-based learning where students translate non-mathematical problems into mathematical language.

• Statistical Mechanics
• Soft Matter Theory
• Liquid Crystals
• +12 more

Professor Mikhail Osipov is a leading academic in the Department of Mathematics and Statistics at the University of Strathclyde, UK, within the Faculty of Science. His research centers on the theoretical physics of soft matter, particularly liquid crystals and related materials. He is actively involved in international collaborations and has led significant research initiatives such as the Materials World Network and the EPSRC-funded program at the Newton Institute. Research Interests: His expertise spans statistical mechanical theories of soft matter with emphasis on liquid crystals, mesogenic polymers, and anisotropic fluids. He has made foundational contributions to the molecular and phenomenological theory of thermotropic and lyotropic liquid crystals, ferroelectric ordering, cholesteric twisting, elasticity, flexoelectricity, rheology, surface, dielectric, and optical properties. His recent work includes bent-core liquid crystals, cholesteric lyotropics, and polymer nanocomposites. The recent publications reflect a strong trend in understanding ferroelectric nematic phases, thermodynamic modeling, electrostatic interactions, and phase transitions using advanced molecular and continuum theories. His interdisciplinary work bridges physics, materials science, and applied mathematics, particularly in modeling unconventional smectic and nematic phases. Scientific Awards: Frederiks Medal (2018) Hilsum Medal (2015) Merkator Guest Professor Award (2008) Research Leadership and Grants: Professor Osipov has served as Principal Investigator on multiple international and national projects, including those funded by the Leverhulme Trust, Russian Science Foundation, and German Science Foundation. He was the UK PI in a multinational Materials World Network and organized a major 6-month program at the Isaac Newton Institute. His research has significant implications for electro-optic devices, holography, beam steering, and chirality detection. Professional Engagement: He is actively involved in the scientific community as Section Editor-in-Chief for the Crystals journal (Liquid Crystals section), delivers invited and keynote talks globally, and participates in major conferences. His professional activities include over 100 recorded events, including organizing symposia and serving on editorial and scientific boards.

• Civil procedure
• Litigation dynamics
• Empirical legal studies
• +4 more

William H. J. Hubbard is an Assistant Professor of Law at the University of Chicago Law School, where he conducts rigorous empirical research at the intersection of law, economics, and judicial systems. His scholarly work examines civil procedure through quantitative methodologies, with particular focus on litigation dynamics, pleading standards, and cross-jurisdictional court comparisons. Professor Hubbard's research interests encompass several critical domains in contemporary legal scholarship: Civil procedure and litigation dynamics Empirical analysis of judicial behavior and court efficiency Law and economics applications to procedural rules Settlement negotiation strategies and strategic behavior in litigation Comparative analysis of court systems across jurisdictions Technological solutions to judicial administration challenges His scholarly contributions reveal sophisticated methodological approaches that bridge doctrinal legal analysis with economic theory and statistical testing. Hubbard's work frequently employs large datasets to test theoretical models of litigation behavior, particularly examining how procedural rules affect substantive justice outcomes across different judicial systems. Professor Hubbard maintains an active research agenda with significant publications in leading law and economics journals. His work has been widely accessed through SSRN, with notable papers like 'The Supreme Court of India: An Empirical Overview of the Institution' receiving over 2,000 downloads, demonstrating substantial engagement from the academic community. His scholarly collaborations span multiple continents, working with researchers at Tel Aviv University, Cornell Law School, National Law University Delhi, and other international institutions. This global network reflects the transnational relevance of his research on judicial systems and procedural rules, particularly his comparative work analyzing U.S. federal courts alongside systems in Taiwan and India.

C. Brenhin KellerView profile

Assistant Professor

• Geochronology
• Geochemistry
• Continental Crust Evolution
• +4 more

C. Brenhin Keller is an active Assistant Professor in the Department of Earth Sciences at Dartmouth College since 2019, previously serving as a Postdoctoral Fellow at the Berkeley Geochronology Center and UC Berkeley (2016-2019), and Visiting Scientist at Lawrence Livermore National Laboratory (2016-2019). His research integrates computational, field, and geochronological methods to investigate continental crust formation and its coevolution with Earth's biosphere and surface systems. Education: B.S. summa cum laude in Science of Earth Systems, Cornell University (2010) M.A. in Geosciences, Princeton University (2012) Ph.D. in Geosciences, Princeton University (2016) Dr. Keller's work centers on geochronology and statistical geochemistry , with expertise in zircon dating, crustal evolution modeling, and Bayesian inversion techniques. He develops open-source computational tools like Chron.jl for eruption age modeling and StatGeochem.jl for geochemical resampling, addressing fundamental questions about Earth's history through innovative data-driven approaches. Recent publications show strong emphasis on Bayesian methodologies , zircon trace element analysis , and interdisciplinary connections between solid Earth processes and paleoenvironments. His work spans volcanic-plutonic systems, Great Unconformity studies, and planetary science applications, frequently appearing in high-impact journals like Nature and PNAS. Scientific awards: James B. Macelwane Medal (AGU, 2024) Donath Medal (GSA, 2024) Hisashi Kuno Award (AGU, 2023) Class of 1962 Faculty Fellowship (Dartmouth, 2023) Computational Science Graduate Fellowship (DOE, 2012-2016) He mentors graduate students including Jannitta Yao, Reina Harding, and Alexander Cox, with alumni such as Gailin Pease (M.S. 2021). His research has been supported by DOE and Princeton fellowships, and he actively contributes to open science through software development and large collaborative projects like the Sedimentary Geochemistry and Paleoenvironments Project. Dr. Keller leads a computational geoscience research group developing Julia-based tools for geochronology and geochemistry. His team conducts fieldwork globally across glacial, volcanic, and tectonic settings, including Antarctica, the Himalayas, and North American Cretaceous-Paleogene boundary sites, while maintaining strong connections with Lawrence Livermore National Laboratory.

Peyman MostaghimiView profile

Professor

• Computational Fluid Dynamics
• Pore-Scale Modeling
• Multiphase Flow in Porous Media
• +7 more

Professor Peyman Mostaghimi is a Professor of Minerals and Energy Resources at the University of New South Wales (UNSW) Sydney within the Faculty of Engineering, School of Civil and Environmental Engineering. He joined UNSW in 2014 after completing postdoctoral research at Imperial College London, where he focused on multiphase flow and transport in porous media. Professor Mostaghimi earned his PhD from Imperial College London and holds an MSc in Mechanical Engineering with specialization in Fluid Mechanics along with dual BSc degrees in Mechanical and Chemical (Reservoir) Engineering from Sharif University of Technology. His educational background has provided a strong foundation for his interdisciplinary research at the intersection of engineering, geoscience, and computational methods. His research spans computational fluid dynamics, natural gas extraction, subsurface reservoir simulation, pore-scale modeling of displacement processes, and flow and transport in porous media with applications to energy extraction, mineral recovery, subsurface hydrology, and environmental studies. Mostaghimi's work integrates advanced computational techniques with experimental validation to address complex challenges in subsurface resource management. He has pioneered approaches combining machine learning with traditional numerical methods to enhance the accuracy and efficiency of digital rock physics simulations. His recent publications (2024-2025) demonstrate a strong focus on multi-scale modeling approaches, bridging pore-scale phenomena to continuum-scale applications. His research group has made significant contributions to understanding multiphase flow in porous media, hydrogen storage, CO2 sequestration, and mineral characterization using cutting-edge imaging and computational techniques. The trend shows increasing integration of machine learning and deep learning techniques with traditional physics-based modeling to solve complex subsurface engineering problems. Professor Mostaghimi has received international recognition including being ranked among the world's top 2% scientists in Energy by Stanford University (2020). He serves as a Council Member for the International Society for Porous Media and as an Associate Editor for the Journal of Petroleum Science and Engineering. His professional affiliations include active membership in SPE (Society of Petroleum Engineers), InterPore, AGU (American Geophysical Union), and IAMG (International Association for Mathematical Geosciences). As director of the MUTRIS research group (http://mutris.unsw.edu.au), Professor Mostaghimi leads a team investigating multiphase flow and transport in porous media. His research has significant implications for energy transition technologies including carbon capture and storage, hydrogen storage, and sustainable mineral extraction. The group's work combines experimental techniques like X-ray micro-CT imaging with advanced computational methods to develop predictive models of subsurface processes.

Pamela VocaleView profile

Researcher

• Applied Physics for Architecture
• Energy Efficiency in Buildings
• Sustainable Design
• +7 more

Pamela Vocale is a fixed-term Researcher in the Department of Engineering and Architecture at the University of Parma, actively engaged in teaching and research related to applied physics and energy efficiency in architectural and urban contexts. She teaches courses such as Applied Physics for Architecture, Energy Efficiency for Sustainable Design, and Systems for Sustainable Building across multiple degree programs including Architecture Regeneration Sustainability and Sustainable Design for Food Systems. Research Interests: Her work centers on thermal engineering, particularly in microchannel heat transfer, building thermophysics, and sustainable energy systems. She investigates slip flow, viscous dissipation, and rarefied gas dynamics in microchannels, as well as solar-assisted air-conditioning and building energy retrofitting. These topics are crucial for advancing energy-efficient and environmentally responsive architectural design. The recent publications highlight a strong focus on microscale thermal systems and sustainable building technologies, with a trend toward numerical modeling and performance optimization under non-ideal boundary conditions. Her research bridges mechanical engineering principles with architectural applications, emphasizing sustainability and efficiency. Scientific Awards: No awards listed in the provided text. Advising and Grants: There is no information available regarding student advising or research grants. However, her collaborative publications suggest active research engagement with colleagues such as Morini G. L. and others in thermal and environmental engineering. Labs and Teams: While specific lab affiliations are not mentioned, her research on microchannels and building energy systems likely involves computational and experimental work within the Department of Engineering and Architecture at the University of Parma, possibly linked to thermal sciences or sustainable design research groups.

Diana Angoso de GuzmánView profile

Associate Professor

• Contemporary Art
• New Materialisms
• Material Anthropology
• +9 more

Diana Angoso de Guzmán is an Associate Professor at Nebrija University in the School of Communication and Arts, Department of Aesthetics and Theory of the Arts. She also holds an academic position at the Complutense University of Madrid (UCM), where she is a researcher in the SU+MA (Museum + University) group. Her work bridges contemporary art history, material theory, and cultural anthropology, with a focus on the philosophical and symbolic dimensions of artistic materials. PhD in Contemporary Art History, Complutense University of Madrid (cum laude) Diploma in Conservation-Restoration, Istituto per l'Arte e il Restauro, Florence Her research centers on new materialisms, material agency, heritage conservation, and the cultural meanings of materials—especially gold—in contemporary art. She explores how artists engage with materiality as a performative and political force, drawing from theorists such as Rosi Braidotti, Timothy Ingold, and Jane Bennett. Her interdisciplinary approach includes philosophy, anthropology, and art market studies. The analysis of her recent publications reveals a consistent focus on materiality, value, and embodiment in art. She investigates how materials like gold transcend mere aesthetic function to become active agents in socio-political discourse, particularly in relation to economic systems, identity, and ecological thought. Her work often examines the intersection of myth, science fiction, and posthumanism in visual culture, reflecting a deep engagement with contemporary theoretical debates. First Prize for Innovative Research and Presentation Delivery, Case Western Reserve University Friends of Art (2013) Diana Angoso de Guzmán is actively involved in academic mentoring and pedagogical innovation, particularly through experiential learning models such as student-led curatorial projects. She has directed the Master’s in Art Market and Art Management at Nebrija University and continues to supervise academic theses and collaborative research. She has also participated in EU-funded projects such as 'Innovation Strategies in Cultural Mythocriticism AGLAYA-UCM.' Her research is disseminated through peer-reviewed journals, edited volumes, exhibition catalogs, and international conferences, demonstrating a sustained and influential scholarly presence in the field of contemporary art history. She is affiliated with the ETCC Nebrija Research Group on Transversal Studies in Contemporary Creation and contributes to interdisciplinary dialogues on art, conservation, and cultural theory.

Luigi PreziosiView profile

Professor

• Biomathematics
• Biomechanics
• Cancer modeling
• +13 more

Luigi Preziosi is a Full Professor in the Department of Mathematical Sciences "GL Lagrange" (DISMA) at Politecnico di Torino , where he conducts interdisciplinary research at the intersection of mathematics, biology, and engineering. He is a member of the Interdepartmental Center PolitoBIOMed Lab and actively contributes to doctoral programs in Complex Systems for Quantitative Biomedicine at both Politecnico di Torino and the University of Turin. Research Interests: Mathematical modeling of cancer, focusing on tumor growth, cell invasion, and vascular network formation. Mechanics of cell aggregates, tissue growth, and multiphase modeling incorporating adhesion and stress relaxation. Biomechanics of cellular systems, including cell motility, durotaxis, and response to mechanical stretch. Engineering applications such as windblown sand mitigation, avalanche dynamics, soil mechanics, and composite materials manufacturing. His recent publications highlight a strong trend in multiscale and multiphase modeling , particularly in simulating tumor spheroids, cellular reorientation under mechanical stimuli, and the role of the extracellular matrix in cancer progression. These works integrate biomechanics with kinetic and continuum models to understand complex biological behaviors. Scientific Recognition: Fellow, Accademia dei Lincei (2016–present) Corresponding Member, Interuniversity Center for Mathematics Applied to Biology (CIMAB) (2010–present) Editorial and Academic Service: He holds editorial positions in several leading journals, including Mathematics in Engineering (President of Editorial Committee), PLOS ONE , Journal of Theoretical Biology , and Mathematical Medicine and Biology . He has led major research projects funded by the Italian PRIN and EU H2020 programs, such as SMaRT and DERMA. Advising and Research Leadership: He has supervised PhD students including Gabriele Fioretto and Claire Claude Yvonne Alamichel , and leads research groups focused on mathematical physics and biomedical modeling. His work bridges theoretical development with practical applications in oncology and environmental engineering. Laboratories and Research Networks: He is affiliated with the PolitoBIOMed Lab and has participated in international research networks such as M3CS-TU TH, SMaRT, and mcrtn, fostering collaboration in mathematical biosciences.

Kim A. SharpView profile

Associate Professor

• Computational Biophysics
• Protein-Ligand Interactions
• Molecular Dynamics
• +7 more

Kim A. Sharp is an Associate Professor in the Department of Biochemistry and Biophysics at the Perelman School of Medicine, University of Pennsylvania. He is also Chair of the Graduate Group in Biochemistry and Molecular Biophysics and affiliated with the Genomics and Computational Biology program. Education: BSc.Hons. in Biophysics, Leeds University, 1978 Ph.D. in Chemistry, University of British Columbia, 1985 Dr. Sharp's research centers on understanding molecular recognition processes involving proteins, ligands, drugs, and nucleic acids using theoretical and computational methods. His work emphasizes Poisson-Boltzmann electrostatics , molecular and Brownian dynamics , and Monte Carlo simulations . Key areas include protein-ligand binding energy calculations, simulation of proteins in reverse micelles, viral genome packaging, and novel computational approaches to analyze protein shape. The published works reflect a strong focus on computational biophysics and molecular energetics , particularly in quantifying electrostatic contributions to binding, solvation effects, and macromolecular shape descriptors. His research bridges physical chemistry principles with biological applications, especially in nucleic acid interactions and drug binding. Scientific Awards: No awards explicitly listed in the source text. Dr. Sharp advises graduate students through the Biochemistry and Molecular Biophysics Graduate Group. While specific grants are not mentioned, his sustained publication record in top-tier journals indicates active funding and research leadership. He maintains a laboratory focused on developing and applying advanced computational tools to fundamental problems in molecular biophysics.

Danielle GermanView profile

Associate Professor

• Social determinants of health
• Harm reduction
• HIV/AIDS
• +12 more

Danielle German, PhD, MPH, is an Associate Professor in the Department of Health, Behavior and Society at the Johns Hopkins Bloomberg School of Public Health. She serves as Vice-Chair for Inclusion, Diversity, Anti-Racism, and Equity in her department and leads the LGBTQ Public Health Certificate Program. Her research is centered on the social and structural determinants of health among marginalized populations in Baltimore and across Maryland. PhD, Johns Hopkins Bloomberg School of Public Health, 2009 MPH, Emory University Rollins School of Public Health, 1998 BA, Rutgers University, 1996 Dr. German’s research focuses on drug use, harm reduction, HIV/AIDS, mental health, LGBTQ health, and social networks. She employs mixed methods—qualitative and quantitative—to explore how social stability, stigma, and structural factors influence health behavior and disease transmission. Her work emphasizes community-engaged and applied research, often in partnership with public health departments and community organizations. Her research portfolio includes major surveillance and implementation science projects such as BESURE (Baltimore’s CDC National HIV Behavioral Surveillance) and SEADS (Statewide Ethnographic Assessment of Drug Use and Services). Recent publications highlight trends in xylazine exposure, polysubstance use, HIV stigma, transgender health, and mental health among sexual minority women. Her work increasingly integrates social network interventions and telemedicine to improve access to care in underserved areas. Excellence in Teaching Award (2014–2017, 2019–2022) Ruth L. Kirchstein National Research Service Pre-Doctoral Training Award (2005–2009) Sir Arthur Newsholme Scholarship (2004–2008) Delta Omega Society (2009) Johns Hopkins SOURCE Service-Learning Community Fellow (2016) Dr. German has extensive experience mentoring students and training early-career researchers through federally funded programs. She has served as Principal Investigator and Co-PI on multiple grants focused on behavioral surveillance, harm reduction, and health equity. Her leadership in mixed methods research and LGBTQ health has positioned her as a key figure in public health research and education. She is actively involved in community-based research teams and collaborates widely across disciplines and institutions. She leads or contributes to several research labs and teams, including the Lighthouse Studies at Peer Point Center for Public Health and Human Rights, the Johns Hopkins Center for AIDS Research (JHU CFAR), and the Mixed Methods Research Training Program for the Health Sciences. These teams focus on interdisciplinary, community-responsive research to address structural barriers to health.

Jonathan ElseyView profile

Research Fellow

• Atmospheric Science
• Radiative transfer
• Atmospheric spectroscopy
• +7 more

Dr. Jonathan Elsey is a Visiting Research Fellow in the Department of Meteorology at the University of Reading, where he serves as Postdoctoral Research Assistant on the EU-funded MAPP (Metrology for Aerosol oPtical Properties) project. His work focuses on quantifying aerosol optical properties using the UK Met Office SOCRATES radiative transfer code within a Monte Carlo framework to reduce uncertainties in radiative forcing calculations. Previously, he held a Postdoctoral Research Assistant role on the ASPIC project analyzing laboratory data at the Rutherford Appleton Laboratory. His educational background includes a PhD funded by the NERC SCENARIO Doctoral Training Partnership with CASE sponsorship from the National Physical Laboratory, centered on deriving water vapour continuum absorption between 1-5 microns using atmospheric spectroscopic measurements. Dr. Elsey's research spans critical atmospheric radiation processes, with emphasis on water vapour continuum absorption in atmospheric windows, aerosol direct radiative effects, and solar spectral irradiance discrepancies. His work integrates Fourier Transform spectroscopy with radiation model development to address Earth's energy budget uncertainties and climate change impacts. Key methodological approaches include laboratory data analysis, Monte Carlo frameworks, and high-resolution radiative transfer code development (e.g., RFM-DISORT). His recent publications (2017-2022) demonstrate consistent focus on spectroscopic validation of water vapour continuum models and reconciliation of solar irradiance measurements, contributing to improved climate modeling accuracy. These works bridge laboratory experiments, atmospheric observations, and radiative transfer theory across near-infrared and visible spectral regions. Best Oral Presentation, 15th AMS Conference on Atmospheric Radiation (2018) University of Reading Department of Meteorology PhD Poster Presentation Prize (2016) As Principal Investigator on EU MAPP and ASPIC projects, Dr. Elsey manages significant research funding from the European Union and UK's Natural Environment Research Council. His collaborations include the UK Met Office, National Physical Laboratory, and international institutions like the University of Oklahoma. Though no formal students are listed, he actively mentors through seminar leadership as former Lunchtime Seminar chair. He operates within the Department of Meteorology's Radiation Group, utilizing specialized facilities including the Dr Carbon Atmospheric Observatory and Rutherford Appleton Laboratory instrumentation for spectroscopic measurements. Current work involves Monte Carlo uncertainty quantification for aerosol radiative effects, with future directions targeting improved continuum models for next-generation climate simulations.

Zahra Ebrahimi MamaghaniView profile

Researcher

• Approximate Computing
• Reconfigurable Accelerator Design
• In-Network Computing for 5G/6G
• +3 more

Zahra Ebrahimi Mamaghani is an academic researcher affiliated with the Embedded Systems team at the Faculty of Electrical Engineering and Information Technology, Ruhr University Bochum. Her work focuses on approximate computing, reconfigurable accelerators, and energy-efficient embedded systems. She completed her B.Sc. and M.Sc. at Sharif University of Technology (Iran) and is a PhD student at TU Dresden. She managed the X-DNet (BMBF-funded, collaborating with Huawei) and GREEN-DNN (acatech/BMDV-funded) projects, emphasizing distributed and in-network computing for 5G/6G applications. Education: B.Sc. and M.Sc. in Electrical Engineering, Sharif University of Technology, Iran PhD Candidate at TU Dresden (Cfaed Institute, 2018–2024) Research Projects: ReAp (DFG, 2018–2021) Relearning (ESF, 2021–2023) X-ReAp (DFG, 2023–2025) X-DNet (BMBF, with Huawei) GREEN-DNN (acatech/BMDV) Research Interests: Approximate computing, energy-efficient edge-to-cloud systems, SW/HW co-design, and reconfigurable architectures for 5G/6G. Her recent publications emphasize cross-layer approximation techniques, energy-efficient CGRAs, and distributed computing frameworks for multi-kernel applications. She advises students on topics like approximation of ML models for high-throughput systems, requiring expertise in FPGA programming (Verilog/VHDL), Python, and ML frameworks like TensorFlow/PyTorch. Her lab focuses on embedded systems and collaborates with industry partners like Huawei. She holds a notable position in managing interdisciplinary projects bridging academia and industry, particularly in sustainable computing for next-generation networks.

Dan J HillView profile

Researcher

• Applied Mathematics
• Dynamical Systems
• Partial Differential Equations (PDEs)
• +5 more

Dr. Dan J Hill is a Hooke Research Fellow at the University of Oxford's Oxford Centre for Industrial and Applied Mathematics (OCIAM). He holds a PhD from the University of Surrey and previously held an Alexander von Humboldt Fellowship at Saarland University. His research focuses on dynamical systems and PDEs applied to physical and biological problems, with an emphasis on localized patterns in continuum models, such as ferrofluids, dryland vegetation, and Turing instability-driven phenomena. His work bridges theoretical mathematics with real-world applications, addressing questions in fluid dynamics, ecological modeling, and symmetry-driven pattern formation. Recent publications explore dihedral patterns, vegetation models, and ferrofluid surface dynamics. Education: PhD in Applied Mathematics from the University of Surrey Awards: Alexander von Humboldt Fellowship His research group at OCIAM investigates nonlinear systems, leveraging numerical methods and analytical techniques to study pattern formation in complex systems.