جستجوی استاد راهنمای دانشگاهی

Shawn Gomezمشاهده پروفایل

استاد

• Systems Biology
• Network Pharmacology
• Translational AI
• +۷ مورد دیگر

Dr. Shawn Gomez is a Professor in the Lampe Joint Department of Biomedical Engineering at UNC-Chapel Hill and North Carolina State University and in the Department of Pharmacology at UNC-Chapel Hill. He serves as the Executive Director of FastTraCS, a component of the NC TraCS Institute funded through the NIH CTSA Program, and is a UNC Lineberger Comprehensive Cancer Center member. His educational background includes a PhD in Biomedical Engineering from Columbia University (1999), an MS in Aerospace Engineering Sciences from the University of Colorado, Boulder (1993), and a BS in Aerospace Engineering Sciences from the same institution (1990). He completed postdoctoral training in Bioinformatics and Computational Biology at the Judith P. Sulzberger Columbia Genome Center and Institut Pasteur in Paris. Dr. Gomez's research spans systems biology , network pharmacology , and translational AI , with a focus on understanding cell signaling architecture in human disease. His lab develops computational approaches for network pharmacology and targeted cancer therapies, along with machine learning methodologies to address clinical needs and enhance clinical decision making. The research integrates computational modeling with experimental approaches to improve diagnostic and therapeutic interventions. His recent publications reveal a strong focus on kinome research, particularly in pancreatic cancer and understudied kinases, with increasing integration of machine learning techniques for predicting clinical outcomes and kinase-substrate relationships. The work spans from fundamental systems biology to translational applications in cancer therapeutics and surgical outcomes prediction. Scientific Awards: Leadership Advanced Program, UNC-Chapel Hill 2017 Chancellor's Entrepreneurship Boot Camp 2015 ACCLAIM Scholar (Academic Career Leadership Academy in Medicine) 2013-2014 UNC Research Council Award 2011 Carl Storm URM Fellowship 2008 UNC Junior Faculty Development Award 2006 Florence Gould Scholar 2005 Pasteur Foundation Fellow 2002-2005 Dr. Gomez directs the Gomez Lab, which focuses on systems biology, network pharmacology, and translational AI. The lab maintains several key resources including Darkkinome.org, FAAS, and IAS servers for kinome research. His work bridges computational biology with clinical applications, particularly in cancer therapeutics and surgical outcomes prediction through machine learning approaches.

Guy Hoffmanمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Embodied Cognition
• Social Robotics
• +۳ مورد دیگر

Guy Hoffman is Associate Professor and Associate Director of Undergraduate Affairs at Cornell University's Sibley School of Mechanical and Aerospace Engineering. He holds faculty appointments in Aerospace Engineering, Computer Science, Information Science, and Mechanical Engineering. Hoffman earned his Ph.D. in Human-Robot Interaction from MIT and M.Sc. in Computer Science from Tel Aviv University. His research explores computational, design, and social aspects of Human-Robot Interaction (HRI), with focus areas including: Embodied cognition for social robots Anticipation and timing in HRI Nonverbal behavior in human-robot collaboration Robotics for performing arts Non-anthropomorphic robot design Publications demonstrate interdisciplinary work spanning social robotics, adaptive interfaces, inclusive design, and AI education. Recent articles explore shadow-based interaction privacy, emotional conveyance through shape-changing interfaces, and cultural aspects of robot morphology. Major recognitions include: Andrew P. Sage Best Transactions Paper Award (IEEE, 2020) Dennis G. Shepherd Teaching Award (Cornell, 2019) Best Paper Award, IEEE/ACM HRI Conference (2015) His research group develops robotic platforms like Blossom and investigates human-robot collaboration in workspaces, inclusive play for children with mixed abilities, and open-source educational tools for AI literacy.

Kathleen C. Howellمشاهده پروفایل

استاد

• Orbit Mechanics
• Spacecraft Dynamics and Control
• Trajectory Optimization
• +۵ مورد دیگر

Kathleen C. Howell is the Hsu Lo Distinguished Professor of Aeronautics and Astronautics at Purdue University's School of Aeronautics and Astronautics. Her expertise spans orbit mechanics, spacecraft trajectory optimization, and mission design in multi-body systems. She holds degrees from Iowa State University (B.S., 1973), Stanford University (M.S., 1977; Ph.D., 1983). B.S. in Aerospace Engineering, Iowa State University, 1973 M.S. in Aeronautical & Astronautical Engineering, Stanford University, 1977 Ph.D. in Aeronautical & Astronautical Sciences, Stanford University, 1983 Her research focuses on libration point orbits, solar sail trajectories, and trajectory optimization in Earth-Moon and interplanetary systems. She has pioneered methods for analyzing Lissajous trajectories, invariant manifolds, and low-thrust mission design. Recent work includes solar sail applications for lunar coverage and ARTEMIS mission trajectory analysis. Publications highlight innovations in multi-body dynamics, with contributions to journals like Acta Astronautica , Journal of Guidance, Control, and Dynamics , and AIAA/AAS Conference Proceedings . Her work emphasizes practical mission design tools and visualization techniques. Awards: Fellow, AIAA (2013) W.A. Gustafson Teaching Award (2012) Dirk Brouwer Award (2004) Presidential Young Investigator Award (1984) Multiple Elmer F. Bruhn Teaching Awards Her advising and grants include leadership in space mission design, formation flight, and solar sail technology. She has collaborated on projects like the TRIANA mission and contributed to the Cassini end-of-mission analysis. Active in professional societies, she has edited conference proceedings and delivered invited lectures globally.

Tim Coloniusمشاهده پروفایل

استاد

• Fluid Dynamics
• Cavitation and Bubble Dynamics
• Aerodynamic Sound
• +۵ مورد دیگر

Tim Colonius is the Frank and Ora Lee Marble Professor of Mechanical Engineering and Medical Engineering and holds the Cecil and Sally Drinkward Leadership Chair at the California Institute of Technology. He has been affiliated with Caltech since 1994 and currently serves as Executive Officer for Mechanical and Civil Engineering . Colonius earned his B.S. from the University of Michigan (Ann Arbor), and both his M.S. and Ph.D. from Stanford University. Research Interests: His work focuses on fluid dynamics (global instabilities, cavitation, aerodynamic sound), flow control (closed-loop control, reduced-order modeling), and biomedical applications (shock waves, lithotripsy, ultrasound). He also develops advanced numerical methods for interface capturing, immersed-boundary techniques, and high-order accuracy. Scientific Contributions: Recent publications highlight his research in multiphase flows, vortex ring collisions, turbulent jet analysis, GPU-accelerated simulations, and biomedical applications. His group uses computational and data-driven approaches to study turbulence, instabilities, and flow optimization. Scientific Awards: AIAA Aeroacoustics Award Fellow of the Acoustical Society of America Fellow of the American Physical Society (APS) NSF and DoD research grants

• Robotics
• Artificial Intelligence
• Space Robotics
• +۵ مورد دیگر

M.Sc. Maximilian Mühlbauer is a researcher at the Chair of Sensor-Based Robot Systems and Intelligent Assistance Systems at Technische Universität München (TUM), part of the Faculty of Computer Science. His work focuses on robotics, artificial intelligence, and space robotics, particularly in areas like in-orbit manufacturing, virtual fixtures, and human-robot interaction. He contributes to projects such as the ACOR initiative and the AI-In-Orbit-Factory, exploring fault-tolerant processes and adaptive robotic systems for space applications. Research Interests: Maximilian’s research emphasizes AI-driven robotics , space robotics , and control systems . He develops methodologies for virtual fixtures , reconfigurable robotic systems , and teleoperation with shared control . His work integrates probabilistic models and machine learning for resilient systems in challenging environments like space. Publications: His recent work spans topics from in-orbit manufacturing and force-sensitive space manipulators to multi-modal haptic teleoperation , reflecting a focus on practical robotic applications in aerospace and industry. Grants/Advising: Maximilian oversees available theses on topics like mixture of experts fixture learning and virtual fixture adaptation , inviting collaboration on AI-driven robotics projects. He collaborates with Prof. Alin Albu-Schäffer and contributes to TUM’s research initiatives in autonomous systems. Labs: He is part of the Sensor-Based Robot Systems lab, advancing robotics for human-centric and space-oriented applications.

Chao Liuمشاهده پروفایل

پژوهشگر

• Surgical Robotics
• Teleoperation
• Haptics
• +۲ مورد دیگر

Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.

• Explainable AI
• Computational Argumentation
• Quantitative Bipolar Argumentation Frameworks
• +۲ مورد دیگر

Xiang Yin is a Research Associate at the Department of Computing in Imperial College London , affiliated with the Computational Logic and Argumentation group (CLArg) . His work bridges Explainable AI (XAI) and Computational Argumentation (CA) , focusing on the explainability of Quantitative Bipolar Argumentation Frameworks (QBAFs) through attribution and counterfactual explanations. Research Interests: Explainable AI (XAI) Computational Argumentation Quantitative Bipolar Argumentation Frameworks Model Interpretability Human-AI Interaction Logical Reasoning for AI Publication Trends reveal a focus on argumentation-based explainability, with 2025-2024 works addressing large language models for claim verification, truth-discovery frameworks, and counterfactual explanations. Earlier works (2023-2022) explore random forest explanations, faithfulness criteria, and QBAF analysis. His 2018 publications on aircraft prediction systems demonstrate applied machine learning expertise. Education PhD in Artificial Intelligence under Prof. Francesca Toni and Dr. Nico Potyka Pre-PhD: Machine Learning R&D Engineer at Baidu Labs & Teams Xiang is part of the CLArg group at Imperial College London, focusing on integrating computational argumentation with AI explainability and contestability.

Kshitij Sabnisمشاهده پروفایل

مدرس

• Experimental Aerodynamics
• High-Speed Aerodynamics
• Vehicle Aerodynamics
• +۷ مورد دیگر

Kshitij Sabnis is a Lecturer in Aerospace Engineering at the School of Engineering and Materials Science, Queen Mary University of London. He serves as Admissions Lead and Outreach & Recruitment Lead for Aerospace Engineering, and Deputy Director of Industrial Engagement (Graduate Attributes). He is affiliated with the Centre for Intelligent Transport and conducts experimental research in high-speed aerodynamics. Education: PhD in Experimental Aerodynamics, University of Cambridge Master’s in Physics Dr Sabnis's research focuses on experimental aerodynamics across various speed regimes, particularly shock/boundary-layer interactions, vortex dynamics, and supersonic flows. His work involves wind tunnel experiments on simplified models to understand complex fluid mechanics in applications ranging from racecar wings to supersonic aircraft intakes. He employs advanced diagnostics and develops novel experimental setups to enhance physical insight into flow phenomena. His recent publications (2019–2025) reflect a strong emphasis on high-speed flow behavior, including shock-induced separation, vortex interactions, and nacelle aerodynamics. Key themes include flow control, wind tunnel design, and validation of turbulence models. His work bridges fundamental fluid dynamics with practical aerospace engineering challenges. Scientific Awards: FHEA (Fellow of the Higher Education Academy) Dr Sabnis actively supervises PhD students and leads externally funded research projects. He has secured grants from EPSRC and the Royal Society, supporting work on schlieren imaging enhancement and small-scale wind turbines for rural energy. He teaches advanced aerodynamics modules and contributes to curriculum and industrial engagement. He leads a research group focused on experimental high-speed aerodynamics and is involved in developing new diagnostic techniques and test rigs. His team investigates vortex interactions and aerodynamic performance under extreme flow conditions.

M. Laura Beninatiمشاهده پروفایل

دانشیار

• Environmental Fluid Mechanics
• Sediment Transport
• Multi-phase Fluid Dynamics
• +۳ مورد دیگر

M. Laura Beninati is an Associate Professor of Mechanical Engineering at Bucknell University. She holds dual B.S. degrees in Architectural and Civil Engineering from Drexel University (1994), M.S. in Civil and Mechanical Engineering from Drexel (1997), and a Ph.D. in Mechanical Engineering from the University of Iowa (2004). Her research focuses on environmental fluid mechanics, sediment transport, turbulence dynamics, and experimental fluid mechanics instrumentation. She teaches courses in fluid mechanics, thermodynamics, and engineering experimentation. Awards: Lindback Grant (2007), Swanson Research Fellow (2005-2007), Amelia Earhart Scholarship (2002-2003) Her experimental studies emphasize vortex dynamics and turbulence interactions in fluid flows, with applications to environmental and aerospace engineering. Research methodologies include advanced fluid dynamics instrumentation and computational modeling.

Francesco Ambrogiمشاهده پروفایل

استادیار

• Fluid Dynamics
• Computational Fluid Dynamics
• Turbulent Boundary Layers
• +۳ مورد دیگر

Francesco Ambrogi is an Assistant Professor in the Department of Mechanical and Materials Engineering at Queen's University, where he leads the Fluids, Energy, and Bio-inspired Unsteady Simulations (FEBUS) lab. His research focuses on computational and theoretical studies of turbulent boundary layers under pressure gradients, with applications in unsteady aerodynamics (turbine blades, rotor blades) and biomimicry (swimming/flying animals) for flow control. Dr. Ambrogi received his PhD in Mechanical Engineering from Queen's University in 2024, following a MASc in Energy and Nuclear Engineering from the University of Bologna, Italy (2019), and a BAsc in Mechanical Engineering from the University of Modena and Reggio Emilia, Italy (2015). He previously served as an Adjunct Assistant Professor at Queen's University in 2024 and completed a Postdoctoral Research Fellowship at the University of Waterloo in Mechanical and Mechatronics Engineering. His research program centers on advancing the understanding of turbulent boundary layer physics under unsteady pressure gradients. Dr. Ambrogi's team leverages modern computational tools, particularly large-eddy simulations, to investigate separated turbulent boundary layers and large-scale coherent structures. These structures are pivotal for the transport of mass, momentum, energy, and contaminants in turbulent flows. His work has significant implications for engineering applications such as turbulent mixing, heat diffusion, and contaminant transport in the atmosphere, with direct relevance to turbine blades, rotor blades, and biomimetic systems for flow control. Dr. Ambrogi's recent publications demonstrate a consistent research trajectory focused on unsteady boundary layer separation phenomena, showing increasing sophistication in handling complex unsteady flow physics. His work combines rigorous computational methods with practical applications in aerodynamics and flow control, particularly examining how time-varying freestream conditions affect boundary layer separation and how turbulent kinetic energy is advected in these complex flows. Dr. Ambrogi has secured funding through the Natural Sciences and Engineering Research Council of Canada (NSERC-CRNSG) under the Discovery Grant Program, with computational support provided by the Digital Research Alliance of Canada. His educational initiatives include ARC4CFD, an open-source course designed to bridge the gap between small-scale CFD simulations and large-scale computations on high-performance computing systems. As director of the FEBUS lab at Queen's University, Dr. Ambrogi leads research that combines fundamental fluid dynamics with practical engineering applications. The lab's work spans from theoretical investigations of flow separation mechanisms to the development of computational tools for practical engineering problems in aerospace and bio-inspired systems.

• Computer Vision
• Deep Learning
• Semantic Segmentation
• +۳ مورد دیگر

Dr. Guangliang Cheng is an Associate Professor in the Department of Computer Science at the University of Liverpool. His research focuses on deep learning, computer vision, and perception algorithms with applications in remote sensing, medical imaging, and autonomous systems. Prior to his current role, he served as a vice research director in the Autonomous Driving Group at SenseTime and completed postdoctoral research at the Aerospace Information Research Institute, Chinese Academy of Sciences. Ph.D. in Pattern Recognition from the National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA) Postdoctoral Researcher at Aerospace Information Research Institute, Chinese Academy of Sciences (2017–2019) Dr. Cheng’s research integrates computer vision and deep learning to address challenges in semantic segmentation, domain adaptation, and robust detection. Recent work explores wavelet-based multimodal fusion for remote sensing and attention-guided architectures for medical imaging. His 2025 publications span journals like GIScience & Remote Sensing and Knowledge-Based Systems , emphasizing scalable solutions for geospatial and biomedical applications. In 2025, Dr. Cheng’s article trends highlight remote sensing semantic segmentation, cross-domain medical imaging, and drone-based fire detection. His collaborations span institutions such as SenseTime, Chinese Academy of Sciences, and University of Liverpool teams, focusing on frequency-domain fusion, attention mechanisms, and GPU optimization. As a supervisor, Dr. Cheng seeks highly motivated PhD students to join projects supported by scholarships including the Centres for Doctoral Training (CDT) and Duncan Norman Scholarship. He serves as Module Co-ordinator for COMP338: Computer Vision (2024–2025) and actively reviews for top-tier journals and conferences.

Christopher Mortonمشاهده پروفایل

دانشیار

• Fluid-Structure Interaction
• UAV Technology Development
• Energy Engineering
• +۷ مورد دیگر

Dr. Christopher Morton is an Associate Professor in the Department of Mechanical Engineering at McMaster University, specializing in fluid-structure interaction, UAV technology, and energy systems. His research focuses on aerodynamics, flow control, and sustainable energy solutions, with applications in aerospace and environmental engineering. Education background includes a BASc in Mechatronics Engineering (University of Waterloo, 2008), MASc (2010), and Ph.D. (2014) in Mechanical Engineering from the same institution. His work bridges experimental and computational methods, particularly in flow estimation and control using advanced diagnostics like PIV and spectral analysis. His research interests span vortex-induced vibrations (VIV), unsteady aerodynamics, and energy harvesting through fluid-structure interactions. Recent publications highlight innovations in flow field reconstruction, sensor-based monitoring, and turbulence control. His work has been recognized through awards such as the Departmental Research Excellence Award (2021-2022) and multiple teaching accolades, reflecting his dedication to both research and education. Dr. Morton currently teaches MECH ENG 4FM3 (Advanced Instrumentation for Thermo-Fluids) and MECH ENG 723 (Flow Induced Vibrations), emphasizing hands-on experimental techniques and theoretical analysis. He actively supervises graduate students and collaborates with industry partners like Atlantis Research Labs and Plains Midstream Canada. Key Research Clusters: Advanced Materials & Manufacturing, Digital & Smart Systems, Energy, and Environment. Teaching Excellence: Awarded “Professor of the Year” multiple times and recognized for outstanding teaching performance.

Véronique Michaudمشاهده پروفایل

دانشیار

• Polymer Composite Processing
• Adaptive Composites
• Material Science
• +۳ مورد دیگر

Véronique Michaud is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Laboratory for Processing of Advanced Composites (LPAC) within the School of Engineering (STI). Her research focuses on polymer composite processing, adaptive composites (e.g., shape memory alloys, self-healing mechanisms), and material science. She also contributes to teaching in Materials Science and Engineering, including courses like 'Materials: From Chemistry to Properties' and 'Composite Materials Processing.' Her academic roles include Associate Professorships in SMX, EDMX, and EDAM teaching units, and she serves as a PhD program committee member for the Doctoral Program in Advanced Manufacturing. She has advised numerous PhD students, including Michele Bonacina, Pierre-Alexandre Boschert, and Jean-Baptiste Desbrest, among others. Research highlights include sustainable composite material development, defect mitigation in composites, and advanced manufacturing techniques. Her work often addresses challenges in aerospace and renewable energy applications, emphasizing sustainability and material innovation.

Jianjun Shiمشاهده پروفایل

استاد

• Manufacturing Systems
• Quality Control
• Cyber-Physical Systems
• +۳ مورد دیگر

Jianjun (Jan) Shi is the Carolyn J. Stewart Chair and Professor at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) and holds a joint appointment with the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. He previously served as the G. Lawton and Louise G. Johnson Chair Professor of Engineering at the University of Michigan. His research focuses on system informatics and control for manufacturing and service systems, with notable contributions to quality improvement, cyber-physical systems, and data-driven methodologies. B.S. & M.S. in Electrical Engineering, Beijing Institute of Technology (1984–1987) Ph.D. in Mechanical Engineering, University of Michigan (1992) Dr. Shi’s research interests include process modeling, control systems, and quality engineering. He pioneered methodologies for in-process quality improvement and developed advanced frameworks for high-dimensional data analysis in manufacturing. His work integrates statistical methods, machine learning, and system informatics to enhance operational efficiency and product quality. He has published over 150 peer-reviewed papers and secured $19 million+ in research grants from NSF, DOE, and industry partners. His lab, the System Informatics and Control Group, collaborates with automotive, aerospace, and pharmaceutical sectors. Shi leads initiatives such as the Quality Science Center at the Chinese Academy of Sciences and serves on editorial boards of journals like IIE Transactions and ASME Transactions . Recipient of the IIE Albert G. Holzman Distinguished Educator Award (2011) Fellow of INFORMS, ASME, and IIE Academician of the International Academy for Quality Shi advises 26 Ph.D. graduates, many of whom hold faculty positions or leadership roles in industry. His research group’s innovations have been implemented in global manufacturing systems, yielding significant economic impacts. Current work includes 4D printing, cyber-physical system resilience, and federated learning for industrial data.

• Fluid Dynamics
• Turbulence
• Heat Transfer
• +۶ مورد دیگر

Andrea Ianiro is a Full Professor in the Aerospace Engineering Department at Universidad Carlos III de Madrid (UC3M), where he leads research in fluid dynamics, turbulence, and heat transfer. His work bridges experimental techniques and machine learning applications for flow analysis and control. He serves as Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) and directs the EFM Lab (Experimental Fluid Mechanics Laboratory) at UC3M. Professor Ianiro's research focuses on turbulence characterization, boundary layer flows, and the application of machine learning to fluid mechanics problems. His work spans experimental techniques including Particle Image Velocimetry (PIV), infrared thermography, and advanced data processing methods. Recent research emphasizes data-driven approaches for flow field reconstruction, turbulence control, and heat transfer optimization in wall-bounded flows. His projects often combine theoretical, experimental, and computational approaches to address complex fluid mechanics challenges. The analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional fluid mechanics. His work increasingly focuses on using deep learning techniques (particularly CNNs and GANs) for flow field prediction from limited measurements, developing meshless computational methods for flow analysis, and applying optimization techniques (including genetic algorithms) to heat transfer enhancement. His research maintains a strong experimental foundation while embracing data-driven approaches to tackle turbulence modeling challenges. Associate Editor of the International Journal of Heat and Mass Transfer (2025-2028) Professor Ianiro leads multiple significant research projects including SPANDRELS (SParse AND paRsimonious Event-based fLow Sensing, 2025-2030), HumanIC (Human-Centric Indoor Climate for Healthcare Facilities, 2024-2027), and EXCALIBUR (Extraction of machine learning strategies for turbulent flow control, 2023-2026). His work has attracted funding from the European Commission, Spanish National Research Agency, and industry partners including Airbus. He has supervised numerous theses on topics including AI-based sensing of turbulent flows, convective heat transfer control, and turbulent boundary layers. At UC3M, Professor Ianiro directs the Experimental Fluid Mechanics Laboratory (EFM Lab), which focuses on advanced measurement techniques for fluid flow and heat transfer characterization. The lab specializes in PIV/PTV techniques, infrared thermography, and the development of novel experimental approaches for turbulence research. Current research directions include machine learning applications for flow field reconstruction, plasma-based flow control, and heat transfer optimization in complex flow configurations.