Find Academic Supervisors

• Wireless Communications
• Signal Processing
• Massive MIMO
• +3 more

Nikolaos Kolomvakis is a researcher in the Division of Communication Systems at KTH Royal Institute of Technology in Sweden. He is also a visiting researcher at Ericsson AB in Stockholm. Previously, from 2017 to 2023, he held positions as Systems Engineer and Senior Researcher at Ericsson. His research focuses on wireless communications and signal processing, particularly on developing baseband physical-layer algorithms for distributed/cell-free massive MIMO, holographic MIMO, and large intelligent surfaces. Education: Ph.D. in wireless communications from Chalmers University of Technology , supervised by Prof. Mats Viberg with co-supervision from Prof. Thomas Eriksson and Prof. Michail Matthaiou M.Sc. in information technology & electrical engineering from ETH Zurich (2012) Research Interests: Wireless communications Signal processing Distributed/cell-free massive MIMO Holographic MIMO Large intelligent surfaces Publications: Recent work includes analyzing nonlinear distortion in large arrays and active reconfigurable intelligent surfaces (2025) Exploring spatial frequencies in near-field communications (2025) Investigating 6G performance through gigantic MIMO (2025)

• Neuroscience
• Cognitive Science
• Visual Perception
• +7 more

Dr. Ben Harvey is an Associate Professor (with Ius Promovendi) in the Perception Group of the Department of Experimental Psychology at Utrecht University, Netherlands, within the Faculty of Social and Behavioural Sciences. He is based at the Helmholtz Institute and can be contacted at b.m.harvey@uu.nl. Harvey completed his DPhil at Oxford University with Professor Oliver Braddick in 2009, followed by postdoctoral work with Professor Serge Dumoulin at Utrecht. In 2015, he moved to Coimbra on a starter grant from the Portuguese Foundation for Science and Technology before returning to Utrecht in 2016 as an Assistant Professor. He was promoted to Associate Professor in 2019 and has led his own research group since 2015. Harvey's research focuses on characterizing sensory and cognitive systems in the human brain, particularly neural responses and computations within these systems. His work combines cutting-edge neuroimaging approaches with computational modeling and behavioral experiments. Initially studying the early visual system as a model of neural processing, he extended invasive animal neurophysiological approaches to non-invasive human neuroimaging. His recent work investigates neural responses underlying cognition in the human association cortex, examining how visual space and number processing differs between cultures and in clinical disorders. His fingerprint reveals expertise in Functional Magnetic Resonance Imaging, Numerosity, Receptive Field, Visual Cortex, Population Receptive Field, Nerve Potential, Early Visual Cortex, and Topographic Maps. His publication record demonstrates significant impact, with works like 'Topographic representation of numerosity in the human parietal cortex' (2013) receiving over 360 citations. His research spans visual neuroscience, with emphasis on how the brain processes visual information, attention mechanisms, and numerical cognition, revealing generalized quantity processing systems in the human brain. Award for highest-rated abstract (2013) Brain Centre Rudolph Magnus Research Award (Best Paper of the Year) (2014) Causal link between cortical organization and conscious perception: human fMRI and electrophysiology (2009, 2010) Harvey has been actively engaged in knowledge dissemination, with multiple invited talks at institutions including INSERM in Paris (2016) and the University of Parma (2015). His research has received significant media attention, with interviews on National Public Radio (NPR) USA, Livescience.com, and Science Magazine in 2013. Beyond academic publications, he writes popular science articles exploring the relationship between visual neuroscience and visual arts. As part of the Helmholtz Institute Experimental Psychology research program, Harvey collaborates widely to investigate visual space and number processing across different populations, contributing to our understanding of how these cognitive functions vary between cultures and in clinical disorders.

Ngoc Thanh NguyenView profile

Professor

• Computational Collective Intelligence
• Knowledge Integration
• Data Mining
• +6 more

Ngoc Thanh Nguyen is a Full Professor at Wroclaw University of Science and Technology where he serves as Head of the Department of Applied Informatics. He holds the prestigious title of Professor granted by the President of Poland and has been recognized as a Distinguished Scientist of ACM since 2009. He serves as Editor-in-Chief of both the Journal of Information and Telecommunication (JIT) and the Vietnam Journal of Computer Science (VJCS), and chairs the IEEE SMC Technical Committee on Computational Collective Intelligence. His research spans computational collective intelligence, knowledge integration, data mining, social media analysis, and sentiment analysis. Professor Nguyen has pioneered significant methodologies in spatial data clustering within network space, inter-sequence pattern mining, and graph neural network applications. His work bridges theoretical computer science with practical applications in intelligent information systems, demonstrating particular expertise in handling complex spatial and sequential data structures. His research has evolved from foundational pattern mining techniques to sophisticated neural network approaches for geospatial and social data analysis. The analysis of his recent publications reveals a strong focus on spatial data analysis in network environments, with significant contributions to clustering algorithms, graph neural networks, and pattern mining. His work consistently addresses efficiency challenges in data processing while expanding into emerging areas like Vietnamese language processing and topological data analysis. The research demonstrates a clear trajectory from traditional data mining techniques toward more sophisticated AI-driven approaches that incorporate spatial relationships and network topologies. Distinguished Scientist of ACM (2009) ACM Distinguished Speaker (2009-2013) IEEE Distinguished Visitor (2009-2013) Title of Professor granted by the President of Poland Professor Nguyen has supervised over 20 PhD students to completion and currently mentors several ongoing doctoral candidates. His academic leadership extends to founding two major conference series: the Asian Conference on Intelligent Information and Database Systems (ACIIDS) and the International Conference on Computational Collective Intelligence (ICCCI), which have become significant venues in their respective fields. His collaborative network spans multiple institutions, particularly with Yeungnam University as evidenced by several co-supervised PhD projects. As founder and chair of the IEEE SMC Technical Committee on Computational Collective Intelligence, he leads an international community of researchers advancing this specialized field. His departmental leadership at Wroclaw University of Science and Technology positions him at the center of applied informatics research and education in Poland, with particular emphasis on computational intelligence applications.

Kristian SevdariView profile

Research Fellow

• Electric Vehicle Grid Integration
• Vehicle-to-Grid Systems
• Renewable Energy Integration
• +6 more

Kristian Sevdari is a Postdoctoral Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU). He was born in Kucove, Albania, in 1995, and holds a B.Sc in electrical engineering from the Polytechnic University of Tirana (2016), an M.Sc from UiT Norges arktiske universitet, Norway (2020), and a Ph.D. from DTU (February 2024). Since 2020, he has been working at DTU on multiple projects including Solar-Move, AHEAD, FLOW, EV4EU, ACDC, and FUSE. His research focuses on renewable energy integration and electric vehicle grid integration, with specific expertise in vehicle-to-grid systems, power system dynamics and stability, prosumers and flexible demand, wind power integration, and smart grid technologies. His work contributes to UN Sustainable Development Goals related to sustainable energy and climate action. Dr. Sevdari's recent publications demonstrate a strong trend toward solving practical challenges in EV-grid integration, with emphasis on bidirectional charging technologies, harmonics analysis, battery second-life applications, and smart charging strategies for residential and urban environments. His research bridges theoretical control approaches with experimental validation across multiple European contexts. Best paper award at 2024 IEEE Transportation Electrification Conference & Expo Best paper award of the IEEE PES ISGT-Europe 2021 conference As a supervisor, he has guided multiple Master's theses on topics including telematics integration for EV cost reduction, open charge point protocol implementation, vehicle-to-grid testing, and compatibility testing for EV ecosystems. He is actively involved in the IEEE PES Task Force on electric vehicle grid integration and IEA Task 53, and is the founder of IEEE REST conferences, Qendra SUSALB, and EkoVolt.

Krisztina Kis-KatosView profile

Professor

• Applied Development Economics
• Political Economy
• Effects of (De-)Globalization
• +11 more

Krisztina Kis-Katos serves as Professor for International Economic Policy at the University of Göttingen's Department of Economics, a position she assumed in 2016. She holds prominent leadership roles including Chairwoman of the Standing Field Committee of Development Economics of the German Economic Association (Verein für Socialpolitik) and Chairwoman of the Scientific Advisory Board of the RWI Leibniz Institute for Economic Research. Her institutional affiliations extend to research fellowships at IZA and RWI, along with editorial positions at the Journal of Labour Market Research, European Journal of Political Economy, Bulletin of Indonesian Economic Studies, and Journal of Development Studies. Professor Kis-Katos earned her Economics education in Szeged and Konstanz, attended the Swiss Doctoral Program at the Study Center Gerzensee, and received her doctoral degree from the University of Freiburg in 2010. Her scholarly work spans applied development economics and political economy with particular focus on how (de-)globalization and macroeconomic processes affect social and economic outcomes including labor markets, firm performance, land use change, deforestation, and conflict. Her research portfolio reveals consistent thematic threads across recent publications: the intersection of environmental concerns with economic development (particularly deforestation and palm oil in Indonesia), the gendered impacts of trade liberalization, the socioeconomic effects of pandemics like COVID-19, and the complex relationship between governance, corruption, and economic outcomes. Methodologically, her work combines rigorous econometric approaches with innovative data sources including satellite imagery and high-frequency power usage data. Teaching prize for the best doctoral course in RTG 1723, University of Göttingen (2019) Teaching prize of the Student Union of Economics of the University of Freiburg (2014) BMZ/GIZ Public Policy Award (2013) Friedrich-August-von-Hayek-award (2011) Excellence award of the KfW Development Bank (2011) Professor Kis-Katos leads multiple significant research initiatives including the BMZ-DEval funded evaluation of Madagascar's forest restoration program, the DFG-funded Thailand-Vietnam Socioeconomic Panel, and the DFG Research Training Group on Sustainable Food Systems. Her advisory role extends to supervising doctoral candidates through these projects and previously serving as spokesperson for the Research Training Group 1723 on Globalization and Development. Her substantial grant portfolio demonstrates strong research leadership across international collaborations involving institutions in Germany, Indonesia, Thailand, Vietnam, and the United States. Her work connects closely with the Collaborative Research Centre 990 on Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems in Sumatra, Indonesia, reflecting her deep engagement with environmental-economic research questions in Southeast Asia. She also contributes to interdisciplinary teams through projects like PlanetHealth examining global land-use impacts of the COVID-19 pandemic.

• Geotechnical Engineering
• Seismic Analysis
• Soil Mechanics
• +3 more

Youssef M A Hashash is the W. W. Grainger Chair and Professor in the Department of Civil and Environmental Engineering at the University of Illinois. His research focuses on geotechnical and earthquake engineering, with emphasis on seismic site response analysis, soil-structure interaction, and advanced computational methods like the Discrete Element Method (DEM). He has led projects on infrastructure resilience, including studies of buried water reservoirs, railway systems, and post-earthquake reconnaissance. Hashash has developed influential models for site amplification in Central and Eastern North America, contributing to seismic hazard assessments. His work integrates experimental centrifuge testing, numerical simulations, and field data. Notable contributions include guidelines for implementing NGA-East ground motion models and advancements in pore-water pressure generation models for liquefaction evaluation. Key Research Areas: Ground movement, seismic response, soil dynamics, and geotechnical data systems Major Projects: NGA-East Geotechnical Working Group, Beirut Explosion Analysis, and LA Metro Tunnel Projects Recipient of prestigious awards including the NAE Membership (2022), PECASE (2000), and Walter L. Huber Prize (2006), he collaborates internationally on earthquake engineering and geotechnical innovations. His lab develops tools like the DEEPSOIL software for nonlinear site response analysis and explores AI applications in geotechnical data interpretation.

Ibrahim SabekView profile

Assistant Professor

• Data Management
• Quantum Computing
• Machine Learning
• +3 more

Ibrahim Sabek is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), with a courtesy appointment in the Dornsife Spatial Sciences Institute. He leads the Next-generation Data-Intensive Systems Group (NexDIG) and previously held postdoctoral positions at MIT's Data Systems Group and an NSF/CRA Computing Innovation Fellowship. He earned his PhD in computer science from the University of Minnesota, Twin Cities in 2020, with recognition for his dissertation's excellence. His research focuses on integrating machine learning and quantum computing into data management systems, emphasizing scalable systems design, algorithms, and data structures. Notable awards include the Google Systems and ML Junior Faculty Award (2025), the NSF/CRA Computing Innovation Fellowship, and the Best Demo Award at ACM SIGSPATIAL 2024. His work spans quantum-augmented database engines, learned query optimizers, and causal inference for system debugging. He actively serves on program committees for top conferences like VLDB and SIGMOD, and organizes workshops such as Q-Data. Current courses include CSCI 543 on modern data management, emphasizing prerequisites like CSCI-485/585. Key contributions include frameworks like LIMAO, TurboReg, and Flash, addressing challenges in spatial probabilistic modeling and scalable regression. His research bridges machine learning, quantum computing, and traditional database systems, with applications in spatial data analysis and system optimization.

Qiwei YaoView profile

Professor

• Statistical Inference
• Time Series Analysis
• High-Dimensional Statistics
• +6 more

Qiwei Yao is a Professor of Statistics at the Department of Statistics, London School of Economics (LSE), where he maintains an active research program in statistical methodology and applications. His office is located in Columbia House, Room 7.16 at LSE's Houghton Street campus in London. Professor Yao's research focuses on statistical inference for complex time series, with particular expertise in high-dimensional time series, dynamic networks, spatio-temporal processes, functional time series, nonlinear time series, and high-frequency data. His work bridges theoretical statistics with practical applications, especially in financial econometrics. He has developed innovative methodologies for dimension reduction, factor modeling, and network analysis that have become influential in the field. His recent publications reveal a strong trend toward developing statistical methods for increasingly complex data structures, particularly focusing on high-dimensional and network-based time series. His work integrates machine learning techniques with traditional statistical approaches, as evidenced by papers on deep learning for Markov property testing and tensor decompositions for matrix time series. There's also a clear emphasis on privacy-preserving methods and differential privacy in network analysis. Professor Yao has secured substantial research funding through multiple EPSRC Programme Grants and Research Projects, including the EPSRC Programme Grant for 'Statistical Foundations for Detecting Anomalous Structure in Stream Settings (DASS)' and 'Network Stochastic Processes and Time Series (NeST)'. He also leads the EPSRC Research Project on 'Statistical Network Analysis: Model Selection, Differential Privacy, and Dynamic Structures' and has collaborated with industry partners like Andurand Capital Management on projects such as 'Forecasting Oil Prices Based on Quantitative Methods'. His research has significant applications across various domains, particularly in energy forecasting (electricity load prediction), financial modeling (volatility modeling, oil price forecasting), and ecological modeling (spatio-temporal population dynamics). Professor Yao maintains strong collaborative relationships with researchers across multiple institutions and disciplines.

Emma ColamarinoView profile

Researcher

• Electroencephalographic (EEG) Signal Processing
• Electromyographic (EMG) Signal Processing
• Brain-Computer Interfaces (BCI)
• +4 more

Emma Colamarino is a Researcher at the Department of Computer, Control and Management Engineering "Antonio Ruberti" of Sapienza University of Rome. She holds an M.Sc. in Biomedical Engineering (2014, cum laude) and a Ph.D. in Bioengineering (2019). Since 2015, she has been a research collaborator at the Neuroelectrical Imaging and Brain-Computer Interfaces Lab of IRCCS Fondazione Santa Lucia in Rome and served as a Visiting Ph.D. student at Imperial College London (2018). From 2019 to March 2023, she was a Post-Doctoral Fellow at Sapienza University. Her research focuses on Advanced electroencephalographic (EEG) and electromyographic (EMG) signal processing Brain-Computer Interface (BCI) protocols for cerebral function recovery Machine learning in neurorehabilitation Hybrid BCIs integrating cortico-muscular networks Recent publications address stroke rehabilitation, BCI design, spectral graph theory, and EMG-EEG integration. Her work spans biomedical data analysis, neuroengineering, and rehabilitation technology validation. Scientific awards include multiple grants from Sapienza University and the Italian Ministry of Health, a Student Award at the 7th International BCI Meeting (2018), and recognition as a Subject Expert (2019). She has supervised/co-supervised 18 MD theses across Biomedical, Management, and Robotics Engineering disciplines.

Richard KempterView profile

Professor

• Theoretical Neuroscience
• Computational Neuroscience
• Neural basis of learning and memory
• +7 more

Richard Kempter is a Full Professor at the Humboldt-Universität zu Berlin, where he leads the Theoretical Neuroscience research group within the Institute for Theoretical Biology, Department of Biology. His research focuses on the neural basis of learning and memory through computational and mathematical modeling of synapses, neurons, and neural networks. He is affiliated with several major research centers including the Bernstein Center for Computational Neuroscience, the Einstein Center for Neurosciences Berlin, and the CRC 1315 Memory Consolidation. Professor Kempter's research interests span theoretical and computational neuroscience with a particular focus on the neural mechanisms underlying learning and memory. His work employs biophysical modeling and mathematical analysis to study synaptic short- and long-term plasticity, the dynamics of single neurons, and the interaction of neurons in recurrently coupled networks. A key aspect of his research investigates how neural systems maintain a balance between learning susceptibility and stability against pathological activity patterns, with model systems including the hippocampus and early auditory system. His research group has made significant contributions to understanding hippocampal sharp wave-ripple events, phase precession in spatial navigation, auditory processing in barn owls, and memory consolidation mechanisms. The group's work combines theoretical approaches with computer simulations to unravel the computational principles of neural circuits, showing particular interest in how neural tissue remains susceptible to learning while maintaining robust stability against pathological activity patterns. Scholarship of the State of Bavaria (03/1994-12/1995) Emmy Noether Fellowship Part I (09/1999-08/2001), funded by the Deutsche Forschungsgemeinschaft Emmy Noether Fellowship Part II (01/2003-09/2008) Guest Professor , HU Berlin, Department of Biology (10/2008-03/2010) Professor Kempter has advised numerous PhD and Master's students throughout his career, with many continuing in neuroscience research. His group maintains strong connections with experimental laboratories to bridge computational models with empirical findings, particularly in hippocampal function and auditory processing. The Theoretical Neuroscience Lab participates in collaborative projects investigating memory consolidation and neural coding principles, contributing significantly to our understanding of how neural circuits implement computational principles underlying learning and memory.

• Photonics
• Microresonators
• Nonlinear Optics
• +3 more

Manuel Crespo-Ballesteros is a Research Fellow at the Aston Institute of Photonic Technologies (AiPT) within the College of Engineering and Physical Sciences at Aston University. He holds a BEng in Electronics and Automation Engineering from the Technical University of Cartagena (2007), an MSc in Theoretical Physics from the University of Murcia (2012), and a PhD in Radar Systems from the University of Birmingham (2016). His research focuses on Surface Nanoscale Axial Photonics (SNAP) technology, particularly microresonators, nonlinear optics, and optical frequency combs. He has contributed to advancements in microresonator fabrication, resonant tunneling phenomena, light-by-light transportation, and parametrically modulated frequency combs. His work bridges quantum mechanics and photonics, with applications in sensing, communications, and optical computing. Education: BEng in Electronics and Automation Engineering, Technical University of Cartagena, Spain (2007) MSc in Theoretical Physics, University of Murcia, Spain (2012) PhD in Radar Systems, University of Birmingham, UK (2016) Research Interests: Crespo-Ballesteros investigates microresonators created via SNAP technology, emphasizing their picometer precision and quantum-mechanical analogies. Key areas include resonant tunneling, nonlinear soliton-based light transport, and parametric frequency comb generation. His work explores applications ranging from high-speed communications to quantum physics simulations, such as black hole analogues using time-dependent potentials. Grants and Labs: Active in AiPT’s advanced photonics research, his lab develops cutting-edge SNAP microresonators with applications in precision spectroscopy and sensing. Collaborations include projects on fiber-optic bending-induced tunability and soliton-based transportation systems.

Valeria BruschiView profile

Researcher

• Audio Engineering
• Signal Processing
• Spatial Audio
• +5 more

Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.

Domniki AsimakiView profile

Professor

• Geotechnical Engineering
• Seismology
• Structural Dynamics
• +6 more

Domniki Asimaki is a Professor of Mechanical and Civil Engineering at the California Institute of Technology (Caltech), part of the Division of Engineering and Applied Science. Her research focuses on geotechnical engineering, computational mechanics, and structural dynamics, with an emphasis on understanding ground motion effects on natural and engineered systems such as dams, tunnels, and urban infrastructure. She holds a Dipl. from the National Technical University of Athens (1998), an M.S. (2000) and Ph.D. (2004) from MIT, joining Caltech in 2014. Key research interests include soil dynamics, wave propagation, regional ground deformation, and soil-foundation-structure interaction. She has pioneered data-driven approaches to integrate numerical simulations with field observations for resilient infrastructure design. Notable achievements include developing the open-source Seismo-VLAB software for seismic analysis and receiving prestigious awards like the Bodossaki Award of Scientific Excellence and the Geotechnical Earthquake Engineering Award. Her work addresses seismic hazards at urban and regional scales, with recent studies on the 2023 Türkiye earthquake, the 2019 Ridgecrest earthquake, and Kathmandu Basin dynamics. She leads initiatives to enhance ground motion prediction, landslide hazard assessment, and infrastructure resilience through advanced modeling and AI-driven methods. Education: Dipl., National Technical University of Athens, 1998 M.S., Massachusetts Institute of Technology, 2000 Ph.D., Massachusetts Institute of Technology, 2004 Awards: Bodossaki Award of Scientific Excellence Geotechnical Earthquake Engineering Award Labs/Teams: Leads research groups focusing on seismic hazard modeling, open-source software development, and geotechnical data assimilation techniques.

Diego Riveros-IreguiView profile

Professor

• Ecohydrology
• Biogeochemistry
• Water Resources
• +4 more

Diego Riveros-Iregui is a Professor in the Department of Geography at the University of North Carolina at Chapel Hill, recognized for pioneering research in ecohydrology and biogeochemistry. His work focuses on water-carbon-nitrogen interactions in tropical ecosystems, urban-rural gradients, and climate-impacted watersheds, employing high-frequency monitoring and advanced modeling techniques to address critical environmental challenges. His research interests center on tropical ecohydrology, particularly in Andean páramos and Galápagos Islands, examining carbon cycling in peatlands, nitrogen dynamics across land-use gradients, and stormwater impacts on urban streams. He integrates stable isotope analysis, machine learning, and field observations to study how geomorphology and climate variability regulate biogeochemical fluxes, with emphasis on vulnerable ecosystems facing anthropogenic pressures. Analysis of his 15 most recent publications (2021-2025) reveals dominant trends in high-resolution watershed monitoring, tropical carbon emissions, and urban hydrology. Key methodological innovations include machine learning for water use estimation, isotope-based tempestology, and bias correction in contaminant plume mapping, demonstrating interdisciplinary approaches spanning environmental engineering, climatology, and ecosystem science. Professor Riveros-Iregui has received the following scientific awards: Presidential Early Career Award for Scientists and Engineers (PECASE), the U.S. government's highest honor for early-career scientists, nominated by the National Science Foundation As a PECASE awardee, he leads NSF-funded research programs examining watershed processes across tropical and temperate regions. His collaborative work includes contributions to the EU-funded WELL CARE consortium on water security, though specific grant details and student mentorship records aren't documented in the source material. Current research priorities involve scaling point observations to watershed-level fluxes and assessing climate change impacts on island hydrology. While no dedicated laboratory is specified, his field studies leverage international partnerships in Ecuador's páramos and the Galápagos archipelago, focusing on microclimate-soil microbiome interactions and sustainable water resource management in high-elevation ecosystems.

• Medical Imaging
• Biomedical Engineering
• Magnetic Resonance Imaging (MRI)
• +3 more

Yonghyun Ha is an Associate Research Scientist in the Department of Radiology & Biomedical Imaging at Yale School of Medicine. His research focuses on advancing magnetic resonance imaging (MRI) technologies, particularly in low-field MRI systems, RF pulse design, and imaging hardware innovation. He collaborates with experts like Duy Phan, Haifan Lin, and Nikhil Malvankar, contributing to projects such as RF pulse distortion compensation and novel RF coil development. Research Interests: His work spans low-field MRI systems , RF engineering , imaging algorithm optimization , and hardware design . He explores applications like point-of-care imaging and cost-effective MRI solutions. Articles Trends: Recent publications address gradient-free imaging, field-cycling magnets, and deep learning for data compression. His work bridges engineering and clinical needs, emphasizing practical MRI advancements. Advising & Grants: No formal advisees are listed, but his collaborations suggest involvement in interdisciplinary research teams. No specific grants are mentioned, but his projects imply funding through institutional or NIH channels. Labs/Teams: Active in Yale’s Radiology & Biomedical Imaging department, contributing to MRI technology development and translational research initiatives.