Find Academic Supervisors

• Epilepsy
• Drug-Resistant Epilepsy
• Epilepsy Surgery
• +3 more

Juan Luis Alcala Zermeno, MD, serves as an Assistant Professor of Neurology at Columbia University Medical Center, specializing in drug-resistant epilepsy and surgical interventions. A native Spanish speaker, he practices at the Neurological Institute of New York and Columbus Circle locations, offering virtual visits for new patients with expertise in EEG interpretation and seizure disorder management. His educational journey includes: MD from Universidad de Guadalajara (2017) with Dean's Mention of Outstanding Academic Performance Internal Medicine Internship at Mayo Clinic (2019) Adult Neurology Residency at Mayo Clinic (2022) Clinical Neurophysiology Fellowship at Thomas Jefferson University (2023) Epilepsy Fellowship at Thomas Jefferson University (2024) Dr. Alcala's research centers on epilepsy surgery outcomes for drug-resistant cases unsuitable for resection, with particular focus on racial and socioeconomic barriers limiting access to these life-changing procedures. He employs mixed-methods approaches combining quantitative surgical outcome analysis with qualitative exploration of systemic healthcare disparities, aiming to develop equitable pathways to epilepsy surgery. His publication record (2018-2025) reveals evolving expertise from HIV comorbidity research to cutting-edge epilepsy neuromodulation studies. Recent work examines responsive neurostimulation, invasive device utilization disparities, and surgical prediction tools, demonstrating both clinical neurophysiology depth and health services research innovation. Professional recognition includes: Young Investigator Award from the American Epilepsy Society (2023) While specific grant funding isn't detailed in available sources, his research trajectory indicates active investigation into healthcare access barriers and surgical outcome optimization. His clinical practice at Columbia's Neurological Institute positions him at the forefront of translating research into improved epilepsy care pathways.

• Machine Learning
• Artificial Intelligence
• Data Analytics
• +9 more

Dr. Mukesh Prasad is an Associate Professor at the School of Computer Science , University of Technology Sydney (UTS). With expertise in Machine Learning , Artificial Intelligence , and Computer Vision , his research addresses applications in healthcare, biomedical science, and smart infrastructure. He holds a Ph.D. in Computer Science from National Chiao Tung University, Taiwan, and an M.S. in Computer and Systems Sciences from Jawaharlal Nehru University, India. Key research areas: Machine Learning, AI, Brain-Computer Interfaces, IoT, and Evolutionary Computation Industry experience: Principal Engineer at TSMC (2016-2017), Postdoctoral Researcher at National Chiao Tung University Dr. Prasad has secured competitive grants for AI applications in disaster response, conversational agents, and medical diagnostics. His work has been published in high-impact venues like IEEE , ACM Transactions , and Springer Nature , with over 200 peer-reviewed papers. He serves on editorial boards for journals including Frontiers in Neurorobotics and ACM Computing Surveys . Scientific Awards: Vice Chancellor Teaching and Learning Citation Award (2019) Alumni Fellowship for Ph.D. (2014) Golden Bamboo NCTU Fellowship (2010) Professional Members: IEEE (2011), ACM (2019)

JennyView profile

Professor

• Turbulent Combustion Modeling
• Computational Fluid Dynamics
• Rarefied Gas Kinetics
• +4 more

Professor Jenny leads the Jenny Research Group at ETH Zürich, specializing in turbulent reactive flows, rarefied gas kinetics, and biomedical fluid dynamics. Her work bridges fundamental research with industrial applications in energy systems and fluid mechanics. Develops advanced turbulence models (TDDM, hybrid LES/RANS) for multi-scale flows Pioneers data assimilation frameworks for RANS simulations using adjoint methods Advances particle-based stochastic algorithms for fractured porous media transport Her recent publications emphasize adaptive time integration techniques, probabilistic modeling of non-linear transport phenomena, and optimized simulation tools for hydrogen storage systems. The group's methodological innovations focus on reducing computational costs while maintaining physical accuracy through novel regularization strategies. Key applications include combustion device optimization, high-pressure tank filling analysis, and fractured reservoir simulations. Current projects integrate machine learning with traditional CFD methods to address challenges in droplet clustering, flame surface density propagation, and supersonic spray dynamics. The research framework spans from direct numerical simulations of fundamental flow physics to industrial-scale hybrid modeling implementations.

• Combustion Engineering
• Fluid Mechanics
• Aerodynamics
• +3 more

Franck Richecoeur is an Associate Professor at CentraleSupélec, specializing in experimental combustion and thermoacoustic phenomena. He holds a HDR (French post-doctoral degree) from the University of Rouen and has supervised PhD students like PIEYRE Amanda, MAZUR Marek, and TAO Wenjie. Education: PhD in High-frequency combustion instabilities (2006, École Centrale Paris), Master's (2003, University of Poitiers), Engineering degree (2003, ENSMA) Research Focus: Flame dynamics, combustion noise, ultrasound-based diagnostics, acoustic boundary conditions, and combustion instabilities in aerospace propulsion systems. Scientific Contributions: Over 20 peer-reviewed publications (e.g., Journal of Fluid Mechanics , Combustion and Flame ), with recent works on spray combustion dynamics, thermoacoustic optimization, and droplet evaporation diagnostics. Awards: Stanford Summer Program Fellowship (2012), AIAA Best Paper Award (2006) Teaching: Fluid mechanics, aerodynamics, and multidisciplinary project courses at École Centrale Paris.

Tamara McGavockView profile

Associate Professor

• Labor Economics
• Development Economics
• Gender Norms
• +5 more

Tamara McGavock serves as Associate Professor of Economics at Grinnell College (currently on leave with tenure) and holds concurrent appointments as Visiting Associate Professor at the University of Chicago's Center for the Economics of Human Development under Nobel laureate James Heckman, Visiting Scholar at the Federal Reserve Bank of Chicago, and Invited Researcher with the Abdul Latif Jameel Poverty Action Lab (J-PAL). Her research program sits at the intersection of labor and development economics, specializing in intra-household allocation dynamics and traditional gender norms surrounding caretaking. McGavock pioneers methodological innovations combining high-quality quantitative techniques with ethnographic insights, particularly through high-frequency phone surveys measuring time use, social norms perceptions, and behavioral nudges to increase men's childcare participation. Her work spans Sub-Saharan Africa with significant focus on Ethiopia, addressing critical issues including child marriage, female genital cutting, and unpaid labor distribution. McGavock's publication record shows consistent output in top journals including the Journal of Development Economics and Journal of Policy Analysis and Management , with recent work (2023-2025) emphasizing survey methodology innovations and gender norm interventions. Her current projects examine mental health impacts of care work redistribution, dietary diversity measurement, and stigma reduction in household labor participation. As an educator, she mentors undergraduate researchers at Grinnell College and presents regularly at major conferences including the American Economic Association meetings. Her collaborative work extends to partnerships with CARE Ethiopia, World Vision Ethiopia, and the World Bank Gender Group.

Koji MiwaView profile

Associate Professor

• Psycholinguistics
• Word Recognition
• Bilingualism
• +4 more

Dr. Koji Miwa is an Associate Professor at Nagoya University's Graduate School of Humanities, specializing in psycholinguistics with a focus on experimental approaches to understanding how language is processed in the mind. His academic journey includes a Ph.D. in Linguistics from the University of Alberta, followed by postdoctoral work at the University of Tübingen before joining Nagoya University in 2017. Ph.D. in Linguistics, University of Alberta (2007-2013) M.A. in Linguistics, University of Alberta (2004-2007) B.A., Mount Royal College (2002-2004) Dr. Miwa's research primarily investigates how complex words are represented and processed in the mind, with special attention to bilingual reading processes where two languages coexist in a single mind. His work employs sophisticated methodologies including eye-tracking technology to measure real-time cognitive processing during language tasks. He examines morphological decomposition, cross-linguistic influences, and the cognitive mechanisms underlying efficient language processing, with particular emphasis on Japanese-English bilingualism and morphographic scripts. His research consistently explores how humans process complex linguistic information effortlessly and efficiently, often at subconscious levels. Dr. Miwa's recent publications reveal an expanding research program that now includes metaphor comprehension, analogical reasoning, and event role conceptualization across languages. His work bridges theoretical linguistics with empirical cognitive science, often employing advanced statistical modeling techniques like generalized additive mixed models to analyze complex language behavior data. The ENglish Reading Online (ENRO) Project represents a significant contribution to large-scale data collection in second language reading research. Izaak Walton Killam Memorial Scholarship (2010) Roger S. Smith Undergraduate Researcher's Award (2006) As an educator, Dr. Miwa emphasizes balanced development across multiple dimensions of life and learning. His supervision style focuses on cultivating mindfulness, service, and knowledge in students. He serves on editorial boards for PeerJ, Frontiers in Psychology, and Studies in Language Sciences, contributing significantly to scholarly review processes. His research lab at Nagoya University maintains active international collaborations, particularly with researchers in Canada, Europe, and other parts of Asia. Dr. Miwa also maintains a thoughtful personal mission statement that emphasizes living a balanced life while considering fundamental questions about existence.

• Biomechanics
• Musculoskeletal Health
• Patient Handling
• +4 more

Dr. Anastasia Pavlova is a part-time Research Fellow in the School of Health Sciences at Robert Gordon University, with expertise spanning biomechanics, musculoskeletal health, and evidence synthesis. Her academic journey began with a 1st class BSc (Hons) in Sports and Exercise Science from Robert Gordon University (2006-2010), followed by a PhD in Medicine and Therapeutics from the University of Aberdeen (2010-2014), where she investigated intrinsic lumbar spine shape and biomechanics related to lifting and low back pain. Dr. Pavlova's research focuses on biomechanics and motion analysis , musculoskeletal health , patient handling techniques , low back pain , spine shape analysis using statistical shape modeling , and medical image analysis (MRI and DXA). Her work bridges clinical practice and research methodology, with a strong emphasis on evidence synthesis through systematic reviews and meta-analyses. Her recent publication record (2020-2024) demonstrates significant productivity with approximately 20 outputs focusing primarily on tendinopathy management, work-related musculoskeletal disorders among healthcare professionals, and fall prevention technologies. These publications reveal a methodological shift toward evidence synthesis while maintaining her biomechanics expertise. Dr. Pavlova currently supervises doctoral students, including Emma Hetricks pursuing a Doctor of Physiotherapy degree with research on movement during patient handling. She leads three active research projects: 1) physiotherapists' views on patient handling and work-related musculoskeletal disorders, 2) development of a prehabilitation program for total knee arthroplasty, and 3) supporting an NIHR-funded evidence synthesis project on exercise for tendinopathies. Her research team frequently includes collaborators such as Cooper K, Swinton P, Alexander L, and Morrissey D.

• nonparametric statistics
• Statistics of random processes
• numerical methods of stochastics
• +5 more

Denis Vitalievich Belomestny is a Leading Researcher at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE) in Moscow. He is affiliated with the Institute of Artificial Intelligence and Digital Sciences and the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis. Belomestny joined HSE in 2014 and has accumulated 11 years of scientific and teaching experience. His academic background includes a Candidate of Physical and Mathematical Sciences degree from Lomonosov Moscow State University (2002) and a specialty in Applied Mathematics from the same university (1998). Belomestny's research focuses on nonparametric statistics , statistics of random processes , numerical methods of stochastics , and financial mathematics . His work demonstrates a strong interdisciplinary approach bridging theoretical mathematics with practical applications in machine learning and artificial intelligence. He has made significant contributions to the analysis of stochastic differential equations, particularly McKean-Vlasov type models, and has developed innovative methods combining deep learning with traditional statistical techniques. His recent publication record shows a clear trend toward integrating deep neural networks with classical stochastic analysis. The 15 most recent articles reveal a growing emphasis on applying machine learning techniques to solve complex problems in statistical inference, particularly in areas like variance reduction, optimal stopping, and density estimation. His research spans both theoretical foundations and practical applications, with increasing focus on the intersection of probability theory and modern AI methodologies. Academic Work Allowance (2020–2021, 2019–2020) Bonus for an article in a foreign peer-reviewed scientific publication (2016–2018) Best Teacher of 2019 Belomestny has been actively involved in advising students and junior researchers, with numerous co-authored publications indicating his mentorship role. He is a key member of the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis, which received a significant grant from the Russian Science Foundation in 2018 (project No. 18-11-00132) led by Alexey Naumov, with Belomestny as a principal investigator. The laboratory focuses on high-dimensional data analysis and modern stochastic algorithms, positioning Belomestny at the forefront of research in these rapidly developing fields.

• Underground Hydrogen Storage
• CO2 Sequestration
• Enhanced Oil Recovery
• +6 more

Dr. Prashant Jadhawar is a Lecturer in Petroleum Engineering at the School of Engineering, University of Aberdeen, with 22+ years of combined academic and industry expertise. His multidisciplinary background spans Enhanced Oil/Gas Recovery (EOR/EGR), CO₂ sequestration, Reservoir Modelling, Flow Assurance, and pioneering work in Hydrogen Innovation. He leads industry-academic partnerships as Enterprise & Innovation Champion and serves as Principal Investigator for Net Zero Technology Centre (NZTC)-funded projects on hydrogen storage and pipeline transport. Education: PhD, MPhil, MEng, and BEng in Petroleum Engineering; Fellow of the Higher Education Academy (FHEA). Research Focus: Dr. Jadhawar's work centers on sustainable energy transition technologies. Key areas include: Terawatt-scale underground hydrogen storage in depleted reservoirs/aquifers Pipeline flow assurance for H₂/CO₂ blends and repurposing infrastructure CO₂ sequestration integrated with methane hydrate recovery Advanced EOR methods (low-salinity flooding, nanofluids, electromagnetic heating) His research bridges fundamental geochemistry and reservoir engineering with applied solutions for net-zero goals. Publication Trends (2023-2025): Recent articles demonstrate a strong focus on hydrogen storage optimization (aquifer dynamics, cushion gas selection, geochemical impacts) and sustainable hydrocarbon recovery (nanotechnology applications, ultrasonic treatments, salinity effects). Computational modeling and multiscale experimental validation are recurring methodologies. Awards & Honors: Keynote Speaker at International Conference on Oil and Gas for Energy Security (2024) Expert Panelist at Pravasi Bhartiya Divas, Government of India (2021) Invited keynote on Underground Hydrogen Storage at energy transition conferences globally Grants & Advising: Secured £4M+ funding including NZTC Hydrogen Innovation grants, PTDF awards, and GCRF support. Supervises 8+ PhD students in petroleum engineering and energy transition topics. Current projects include: Hydrogen/CO₂ pipeline transportation digital twins Geomechanical synergies in subsurface hydrogen storage Radio-frequency enhanced heavy oil recovery Collaborations: Partners with CSIRO (Australia), IIT Madras, MIT-WPU (India), and global industry consortia. Serves as Associate Editor for GeoEnergy Science and Engineering and technical committee member for SPE Offshore Europe.

• Astroparticle Physics
• Cosmic Neutrinos
• Multi-messenger Astronomy
• +4 more

Olga Botner is a Professor at the Department of Physics and Astronomy, specifically in the High Energy Physics division, at Uppsala University. Her research focuses on astroparticle physics, with particular emphasis on the exploration of the Universe through cosmic neutrinos, which are considered ideal astrophysical messengers due to their ability to travel unaffected by magnetic fields and unhindered by matter and radiation. She is an active member of the IceCube Collaboration, which operates the world's largest neutrino telescope, the IceCube Observatory located at the South Pole. Professor Botner's research interests center around astroparticle physics, particularly the exploration of the Universe with cosmic neutrinos that may have been created in the environments of black holes. Her work is crucial for multi-messenger astronomy, which combines observations of different cosmic messengers like photons, cosmic rays, gravitational waves, and neutrinos to gain a comprehensive understanding of astrophysical phenomena. Her research spans neutrino astronomy, dark matter detection, cosmic ray physics, and the development of advanced analysis techniques including machine learning applications in neutrino data analysis. The recent publications by Professor Botner demonstrate a strong focus on neutrino physics and astroparticle research. Her work spans multiple areas including neutrino oscillation studies, dark matter searches, cosmic ray anisotropy, multi-messenger astronomy, and the development of advanced instrumentation like the Radio Neutrino Observatory in Greenland (RNO-G). A significant portion of her recent work involves the application of machine learning techniques to neutrino data analysis, particularly convolutional neural networks for atmospheric neutrino oscillation parameter measurements. Her research also explores fundamental physics questions related to sterile neutrinos and potential beyond Standard Model physics. As a key member of the IceCube Collaboration, Professor Botner contributes to one of the most significant neutrino observatories in the world, located at the South Pole. This international collaboration involves researchers from numerous institutions worldwide working together to detect and study high-energy neutrinos from cosmic sources. Her work connects fundamental particle physics with astrophysical observations, bridging the gap between these two fields to address some of the most profound questions about our Universe.

Denis AkimovView profile

Researcher

• Nonlinear Optical Microscopy
• Raman Spectroscopy
• Coherent Anti-Stokes Raman Scattering
• +5 more

Dr. Denis Akimov is a Researcher at the Leibniz Institute of Photonic Technology (Leibniz-IPHT) in Jena, Germany, working within the Research Department of Spectroscopy/Imaging and the Molecular Imaging working group. His email contact is denis.akimov@leibniz-ipht.de and his office is located in building HG, room S47. Dr. Akimov's research focuses on advanced optical imaging and spectroscopy techniques, with particular expertise in nonlinear optical microscopy. His work spans several key areas including coherent anti-Stokes Raman scattering (CARS), surface-enhanced spectroscopy, plasmonics, and ultrafast laser techniques. He has made significant contributions to the development of molecular imaging approaches for biomedical applications, especially in cancer diagnostics. Analysis of his publication record from 2015-2025 reveals a strong emphasis on plasmon-enhanced nonlinear optical techniques, particularly using specialized grating structures like azimuthally chirped gratings and plasmonic Doppler gratings. His research demonstrates how plasmonic nanostructures can enhance light-matter interactions across multiple frequencies, with applications spanning from fundamental molecular dynamics studies to practical biomedical imaging solutions. A notable trend is his focus on spatially resolved enhancement effects in nonlinear spectroscopy and the development of methods to suppress background signals for improved molecular specificity. Dr. Akimov has collaborated extensively with Jürgen Popp and other researchers at Leibniz-IPHT, contributing to numerous high-impact publications in journals such as Laser & Photonics Reviews, ACS Nano, and Nano Letters. His work bridges fundamental optical physics with practical biomedical applications, particularly in cancer diagnostics where his multimodal imaging approaches show promise for improving surgical decision-making.

• Materials Science
• Photovoltaics
• Optoelectronics
• +3 more

Dr. Ivy M. Asuo serves as an Assistant Professor in the Department of Materials Science and Engineering at The Pennsylvania State University, specializing in energy materials synthesis for photovoltaic and optoelectronic applications. Her research focuses on halide perovskites, with emphasis on ambient processing techniques to enhance device stability and efficiency. Her academic foundation includes a PhD in Energy and Materials Science from Institut National de la Recherche Scientifique (INRS-EMT), Canada. She holds dual Master's degrees in Functionalized Advanced Materials Engineering (Erasmus Mundus Scholarship) from University of Augsburg, Germany and Grenoble Institute for Technology, France, an MSc in Materials Science and Engineering from African University of Science and Technology, Nigeria, and a BSc in Physics from University of Cape Coast, Ghana. Dr. Asuo's research centers on solution-processed perovskite devices, particularly solar cells and light-emitting diodes. She pioneers ambient fabrication methods to overcome moisture sensitivity, develops novel hole transport materials, and engineers interfaces for improved charge extraction. Her group investigates cation engineering in perovskites and explores cost-effective alternatives like CuSCN for commercial viability. Analysis of her 15 most recent publications reveals a dominant trend in ambient-processed perovskite devices, with 60% focused on solar cells and 25% on LEDs/photodetectors. Key themes include anti-solvent engineering, dopant-free transport layers, and stability enhancement through interfacial modification. Her work consistently targets scalable manufacturing while maintaining high efficiency. As an entrepreneur, Dr. Asuo co-founded Pi-Sol Technologies Inc. (now WattByWatt Inc., Canada) and DAMINY-EduNergy in Ghana, bridging academic research with commercial energy solutions. Her laboratory develops nanoplasmonic photodetectors and perovskite nanowire networks, utilizing techniques like inkjet printing and radio frequency sputtering for device fabrication.