جست‌وجوی استاد و پژوهشگر

• Nonlinear Systems
• Structural Dynamics
• Flow-Induced Vibrations
• +۶ مورد دیگر

Anil K. Bajaj is the Alpha P. Jamison Professor of Mechanical Engineering at Purdue University's West Lafayette School of Mechanical Engineering. He holds a B.Tech. from Indian Institute of Technology, Kharagpur (1973), an M.S. from Indian Institute of Technology, Kanpur (1976), and a Ph.D. from the University of Minnesota (1981). His research focuses on nonlinear systems, structural dynamics, aeroelastic stability, and bifurcation phenomena, with applications in MEMS, transportation, and human-machine interaction. Key research areas include modeling nonlinear systems, flow-induced vibrations, impacting systems, and micro/nano-technology. He has pioneered studies on internal resonances in mechanical systems and aeroelastic damping of flexible structures. His work integrates experimental validation, computational modeling, and theoretical analysis. Recent articles explore advanced topics like bistable systems, nonlinear MEMS resonators, and transmission noise mitigation. Awards include the 2009 Mentorship Award and ASME Fellowship. He advises graduate students in dynamics and vibration, and collaborates with industry on automotive and biomedical applications. His labs focus on nonlinear dynamics, MEMS design, and seat-occupant systems modeling.

• Quantum Physics
• Quantum Computing
• Quantum Control
• +۳ مورد دیگر

Michael Biercuk is a Professor and Director of the Quantum Control Laboratory at the University of Sydney. He holds a dual role as founder and CEO of Q-CTRL, a quantum technology company. His academic work focuses on quantum control, quantum firmware, and trapped ion systems, with applications in quantum computing, quantum metrology, and quantum simulation. Biercuk earned his undergraduate degree from the University of Pennsylvania and his Master's and PhD from Harvard University. He has held research fellowships at NIST Boulder and advised agencies like DARPA. Education: BA (University of Pennsylvania), MSc/PhD (Harvard University) Research interests include developing quantum control techniques to suppress errors in qubits, engineering quantum firmware for scalable systems, and exploring trapped ion-based quantum sensors. His lab combines theory and experiment, leveraging ultra-high-vacuum systems and precision lasers to study quantum coherence. Awards include the 2021 Australian Financial Review 'Most Innovative Companies' recognition, 2015 Eureka Prize for Outstanding Early Career Researcher, and multiple innovation accolades. His work bridges academia and industry, with collaborations spanning Tsinghua University, MIT, and NIST. Key Projects: Quantum Control & Firmware, Quantum Simulation of Many-Body Systems, Quantum Metrology with Ions

Steven B. Leebمشاهده پروفایل

استاد

• Power Electronics
• Energy Conversion Systems
• Motor Drives
• +۵ مورد دیگر

Steven B. Leeb is a Professor of Electrical Engineering and Computer Science (EECS) and Mechanical Engineering at MIT. He holds the Carl Richard Soderberg Chair in Power Engineering and is a MacVicar Fellow, recognizing his excellence in teaching and research. His work focuses on power electronics, energy conversion systems, motor drives, and nonintrusive power monitoring. Leeb has contributed to advancements in smart grid technologies, building energy management, and fault detection systems. He leads interdisciplinary research integrating control systems with renewable energy applications. Education: B.Sc., M.Sc., M.Eng., and Ph.D. in Electrical Engineering from MIT (1987–1993). His career at MIT spans over three decades, progressing from Assistant Professor (1993) to Full Professor (2005). He has advised numerous projects in collaboration with industries and military applications, including naval propulsion systems and unmanned aerial vehicle (UAV) energy buffering. Research Interests: Power Electronics and Motor Drives Nonintrusive Load Monitoring (NILM) Building Energy Management Smart Grid Technologies Sensors and Sensor Networks Electromagnetic Systems Awards: Over 15 major awards, including the National Science Foundation CAREER Award (1996), IEEE Fellow (2007), and multiple R&D 100 Awards. His work has led to patents in nonintrusive monitoring systems, smart lighting, and energy-efficient technologies. Teaching: Courses include Mechanical Engineering Tools (2.670) , Power Electronics Laboratory (6.131) , and Microcomputer Project Laboratory (6.115) . He emphasizes hands-on learning through labs like his DC motor experiments, which are featured in freshman orientation programs. Labs/Teams: Active in MIT’s Energy Initiative, collaborating with industry partners on projects such as naval propulsion systems and UAV energy systems. His group develops prototypes for commercial applications in smart buildings and renewable energy integration.

Niels Aageمشاهده پروفایل

دانشیار

• Topology Optimization
• Acoustics and Vibroacoustics
• Biomechanics
• +۵ مورد دیگر

Niels Aage is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on topology optimization, biomechanics, and multiphysics modeling, with applications in acoustic devices, biomedical implants, and microelectromechanical systems (MEMS). He holds roles such as Vice President of the International Society for Structural and Multidisciplinary Optimization (2023–2027). Education and Professional Background: Conducted a 5-month research visit at the University of Colorado, Boulder (USA) in 2010. Specializes in giga-scale numerical modeling, finite element methods, and topology optimization algorithms. Research Interests: Develops novel methods for topology optimization of fluidic, thermal, and acoustic systems. Explores applications in patient-specific spinal implants, metamaterials with vibroacoustic bandgaps, and nonlinear dynamic substructuring. His work integrates machine learning and reduced-order modeling for efficient simulation. Publications: Over 100 peer-reviewed articles, including recent contributions on connectivity promotion in topology optimization (2025), vibroacoustic metamaterial design (2025), and anatomically conforming spinal fusion cages (2024). Research emphasizes high-resolution modeling and bridging computational design with additive manufacturing. Scientific Awards: ISSMO Haftka Young Investigator Award (2021), Equinor Prize 2020, and Hyperion Innovation Excellence Award (2017). Recognized for contributions to structural optimization and computational mechanics. Advising and Grants: Supervises multiple PhD projects, including work on vibroacoustic shape optimization, quantum-opto-mechanical systems, and smart hearing aid modeling. Engages in collaborative projects funded by industry and academia. Labs/Teams: Collaborates with DTU’s Solid Mechanics group and industry partners on projects involving topology optimization, multiphysics simulation, and biomedical engineering. Active in international conferences and serves on editorial boards.

Yannick Salaminمشاهده پروفایل

استادیار

• Quantum Optics
• Nonlinear Optics
• Photonics
• +۳ مورد دیگر

Dr. Yannick Salamin is an Assistant Professor at CREOL, The College of Optics and Photonics at the University of Central Florida (UCF). His research focuses on quantum properties of light and nonlinear optical systems, particularly exploring quantum states of light, macroscopic quantum phenomena, and applications in quantum technology. His work utilizes optical parametric oscillators (OPOs) to generate and characterize quantum states, aiming to advance computing and metrology. Dr. Salamin holds a B.S. in Electrical Engineering from the University of Applied Sciences of Western Switzerland (2010), an M.S. from Zhejiang University (2014), and a Dr.Sc. from ETH Zurich (2019). His postdoctoral research at MIT under Prof. Marin Soljačić furthered his expertise in quantum nonlinear photonics. His research group develops systems to harness quantum vacuum noise for probabilistic computing and machine learning. Key areas include controlling nonlinear driven-dissipative systems, biasing quantum vacuums, and creating macroscopic probability distributions. Recent work includes generating large Fock states and squeezed states via nonlinear bound states in the continuum. Research Themes: Quantum vacuum engineering, nonlinear photonics, stochastic computing, and quantum metrology. Applications: Quantum computing, advanced sensors, and probabilistic machine learning. Dr. Salamin has received prestigious awards including the 2025 Ralph E. Powe Award, ABB Research Prize (2021), and the ETH Medal (2020). His lab includes three Ph.D. advisees and multiple undergraduate researchers. He collaborates widely, with publications in Nature Photonics , Science , and Proceedings of the National Academy of Sciences . Current projects emphasize scalable quantum systems and novel photonic devices.

Armin Zareمشاهده پروفایل

استادیار

• Control Theory
• Fluid Mechanics
• Stochastic Dynamical Modeling
• +۳ مورد دیگر

Armin Zare is an Assistant Professor at the University of Texas at Dallas in the Department of Mechanical Engineering , affiliated with the Center for Wind Energy . He obtained his PhD in Electrical Engineering from the University of Minnesota (2016) and previously held a postdoctoral position at the University of Southern California. Education : PhD (2016), MS (2016) in Electrical Engineering from University of Minnesota; BS (2010) in Electrical Engineering from Sharif University of Technology Research Interests : Modeling, dynamics, and control of large-scale and distributed systems; optimization; dynamics and control of complex fluid flows; renewable energy generation. His work focuses on stochastic modeling of turbulent flows and wind farm dynamics using control theory. Recent Publications highlight advancements in wind farm turbulence modeling, stochastic receptivity analysis, and covariance completion algorithms, reflecting his expertise at the intersection of control systems and fluid dynamics. Scientific Awards Young Investigator Program Award, Air Force Office of Scientific Research (2023) Doctoral Dissertation Fellowship, University of Minnesota (2015) Best Student Paper Award Finalist, American Control Conference (2014) Advisees include PhD students working on topics like wall turbulence modeling, wind farm forecasting, and stochastic dynamical systems, with several former students having completed theses on wind turbine wake modeling and fluid flow uncertainties.

Nasser Kehtarnavazمشاهده پروفایل

استاد

• Signal and Image Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Nasser Kehtarnavaz is an Erik Jonsson Distinguished Professor and Director of the Embedded Machine Learning (EML) Laboratory at the University of Texas at Dallas's Erik Jonsson School of Engineering and Computer Science. He holds a PhD from Rice University (1987) and has over 40 years of academic and industrial experience. His research focuses on signal/image processing, machine learning, biomedical applications, and real-time embedded systems. He has authored/co-authored 11 books and over 450 publications, and supervised 37 PhD and 35 MS students. Leadership roles: Editor-in-Chief of Journal of Real-Time Image Processing , SPIE Conference Chair, IEEE Fellow (2013), AAIA Fellow Industrial collaborations: Texas Instruments, AT&T Bell Labs, US Army TACOM Research Lab Key contributions: Smartphone-based signal processing labs, hearing aid amplification algorithms, and FPGA-based embedded systems Research interests include real-time implementation on embedded processors, biomedical signal analysis, and smartphone-based laboratories. He has pioneered educational tools like anywhere-anytime labs using smartphones for signal processing education. Recipient of numerous awards including IEEE Region 5 Professional Leadership Award (2015), Outstanding Engineering Educator Award (2013), and community recognition from SPIE (2020-2021). His funded projects (62 as PI/Co-PI) span healthcare tech, energy systems, and semiconductor manufacturing. Director of the EML Lab and previously the Signal and Image Processing Lab. Teaches graduate courses like Machine Learning and Pattern Recognition and undergraduate courses in signals and systems.

Shahana Ibrahimمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Signal Processing
• +۵ مورد دیگر

Shahana Ibrahim is a tenure-track Assistant Professor at the University of Central Florida under the AI Initiative, holding a joint appointment in the Department of Electrical and Computer Engineering and Computer Science. Her research develops provable methods for robust machine learning systems with applications in critical real-world scenarios. Education: Ph.D. in Electrical and Computer Engineering, Oregon State University (advised by Dr. Xiao Fu) Prior industry experience: System Validation Engineer at Texas Instruments (2012-2017) and NVIDIA GPU intern (2018) Her research spans machine learning, signal processing, and optimization with core expertise in weakly supervised learning, tensor decomposition, and stochastic algorithms. She focuses on enhancing AI reliability through theoretical guarantees for noisy data environments, particularly addressing label noise, incomplete annotations, and structured factorization challenges. Her work bridges signal processing theory with modern AI to solve practical problems in data quality and system robustness. Recent publications (2023-2025) reveal strong thematic consistency in handling imperfect supervision. Key trends include crowdsourced label modeling, instance-dependent noise characterization, and tensor/matrix completion techniques. Her approach uniquely integrates signal processing perspectives with deep learning, emphasizing identifiability conditions and geometric regularization to extract reliable patterns from corrupted data. Scientific Awards: Outstanding PhD Dissertation Award from EECS, Oregon State University (2024) Dr. Ibrahim actively mentors graduate researchers including Faizul and Grey, who co-authored her ICIP 2025 and IEEE CAMSAP 2023 publications. She secured the AI-BTO DARPA grant (December 2024) for physics-informed machine learning research on intrinsically disordered proteins. Current funding supports multiple RA/TA positions for PhD students in her lab. She serves on program committees for AISTATS, AAAI AI for Social Impact, and WiML at NeurIPS. Her research group develops end-to-end learning frameworks for noisy data environments, with active projects funded by DARPA focusing on biomedical applications and robust AI validation. The lab maintains strong industry connections through NVIDIA and Texas Instruments collaborations.

Donghoon Kimمشاهده پروفایل

استادیار

• Autonomous Systems Design
• Fault-Tolerant Control
• Health Monitoring of Autonomous Systems
• +۳ مورد دیگر

Dr. Donghoon Kim is an Assistant Professor at the University of Cincinnati's Department of Aerospace Engineering and Engineering Mechanics, part of the College of Engineering and Applied Science. He leads the Intelligent Autonomous Systems Research Laboratory (IASSRL), focusing on autonomous systems, fault-tolerant control, and celestial mechanics. Prior to academia, he worked at LG Electronics as a Senior Research Engineer, developing service robotic platforms. His professional affiliations include senior membership in AIAA and IEEE, and roles in technical committees for Astrodynamics and Robotics. Education: PhD in Aerospace Engineering (Texas A&M University, 2013) MS and BS in Aerospace & Mechanical Engineering (Korea Aerospace University, 2010 and 2008) Research Interests: Dr. Kim's work centers on intelligent autonomous systems , including robotic control, spacecraft dynamics, and machine learning integration. He emphasizes fault-tolerant control systems and health monitoring for autonomous platforms. His projects span celestial mechanics applications and deep learning-driven solutions for aerospace challenges. Grants & Awards: Recipient of the Neil Wandmacher Teaching Award (2022) $2.3M Air Force Research Lab grant for space robotics technologies (2024) $569K DoD grant for multi-agent trajectory planning (2024) Labs & Teams: Directs the IASSRL , collaborating on projects like the LEOPARDSAT-1 orbital platform and IntroSat educational spacecraft. Engages in industry partnerships with companies like Gimbal Innovations and CincyTech .

Huixuan Wuمشاهده پروفایل

دانشیار

• Fluid Mechanics
• Experimental Technology
• Multiphase Flow
• +۴ مورد دیگر

Huixuan Wu is an Associate Professor in the Department of Mechanical Engineering at the Florida A&M University-Florida State University College of Engineering. Their research focuses on fluid mechanics, experimental technology, multiphase flow, turbulence, and statistical mechanics. They hold a Ph.D. and M.S. in Mechanical Engineering from Johns Hopkins University (2011 and 2008, respectively). Notable achievements include the NSF CAREER Award and the Alexandra von Humboldt Scholarship. Research contributions span magnetic particle tracking technologies, turbulence analysis, and flow visualization techniques. Dr. Wu has also explored interdisciplinary applications such as wind sensing using UAVs and the statistical mechanics of income inequality. Publications highlight advancements in neural network-based algorithms for particle tracking, persistent homology methods in turbulent flows, and acoustic liner performance simulations. Their work bridges computational modeling, experimental fluid mechanics, and machine learning, with applications in aerospace and biomedical engineering. Labs and collaborations involve experimental setups for granular flow analysis and aerodynamic noise mitigation. Advising focuses on graduate students exploring fluid dynamics and related interdisciplinary topics.

Fang Luoمشاهده پروفایل

دانشیار

• Power Electronic Converters and Systems
• Power Module Packaging
• EMI Modeling and Mitigation

Fang Luo is the Empire Innovation Associate Professor and Director of the Spellman High Voltage Power Electronics Laboratory at Stony Brook University's Department of Electrical and Computer Engineering. He is affiliated with the College of Engineering and Applied Sciences, focusing on advancing power electronics technologies. His research interests encompass Power Electronic Converters and Systems, Power Module Packaging, and EMI Modeling and Mitigation. These areas address challenges in high-voltage systems, renewable energy integration, and electromagnetic compatibility. Dr. Luo's work emphasizes practical applications, such as optimizing power converters for offshore wind farms and developing advanced packaging solutions for wide bandgap (WBG) semiconductors. His laboratory, the Spellman High Voltage Power Electronics Lab, drives innovation in high-voltage systems and energy-efficient power electronics. His recent publications highlight advancements in HVDC wind energy systems, GaN-based converter designs, and EMI mitigation strategies. He has contributed to the design of modular power converters and cryogenic power electronics for electric aircraft propulsion. As a leader in his field, Dr. Luo's research bridges theoretical modeling and practical engineering solutions, with a focus on sustainable energy systems and cutting-edge semiconductor technologies.

• Control systems
• Mechatronics
• Precision engineering
• +۳ مورد دیگر

Chun-Yi Su is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on advanced control systems, mechatronics, robotics, and precision engineering. He specializes in nonlinear control, hysteresis compensation, and adaptive systems applied to soft actuators, UAVs, and smart materials. Key research areas include: Control of dielectric elastomer actuators Fault-tolerant cooperative control of unmanned aerial vehicles (UAVs) Adaptive neural network-based control for nonlinear systems Data-driven approaches for power electronics and energy systems Recent work emphasizes: Soft robotics actuation mechanisms Fractional-order control strategies Resilient control under cyber-physical attacks Biomimetic robotic systems His lab develops innovative solutions for smart materials, mechatronic systems, and autonomous robotics. Applications span renewable energy systems, biomedical devices, and aerospace engineering. Active in collaborative research with industry partners.

• Numerical Analysis
• Nonlinear Systems
• Circuit Theory
• +۳ مورد دیگر

Dr. Marissa Condon is an Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU), where she has been since 2000. She holds a BE (First Class Honours) from the National University of Ireland, Galway (1995) and a PhD from the National University of Ireland (1998). Prior to her academic role, she worked at the National Grid of the Electricity Supply Board of Ireland (1998–2000). Her research focuses on numerical modeling of highly oscillatory systems, nonlinear systems analysis, and high-frequency circuit simulation. She led the SFI Investigator Programme Grant SMART (Simulation and Modelling Techniques for Radio Frequency Technology). Her teaching roles include coordinating modules such as Circuits, Numerical Problem Solving for Engineers, and Signals. Her work spans electromagnetic scattering analysis, interconnect modeling, and model order reduction techniques. She has contributed to advancements in RF oscillator simulation and robust control of power electronics systems.

• Quantum Computing
• Quantum Error Correction
• Quantum Noise Characterization
• +۳ مورد دیگر

Robin Harper is an academic staff member at the University of Sydney , affiliated with the Sydney Nanoscience Hub . His research focuses on quantum computing , particularly in quantum error correction , noise characterization , and Bayesian tomography . Recent work includes: Developing scalable methods for quantum noise estimation (2025) Advancing non-Markovian process characterization (2025) Optimizing error correction circuits (2025) His publications highlight machine learning applications in quantum systems and pulse engineering for silicon qubits. Awards include the Gold Human-Competitive Award at GECCO 2017 . Harper contributes to experimental quantum research with grants like the 2023 Entangled HEX project, aiming to build superconducting logical qubits on a heavy hexagonal lattice.

Alexey Peregudinمشاهده پروفایل

مدرس

• Control Systems
• Optimal Control
• Adaptive Control
• +۵ مورد دیگر

Dr. Alexey Peregudin is a University Teacher in Control and Systems Engineering at the Department of Automatic Control & Systems Engineering (ACSE), University of Sheffield, UK (since 2023). He holds a PhD (Candidate of Technical Sciences) from ITMO University (2021), where he previously served as an Associate Professor (2022–2023) and Assistant Professor (2017–2022). His research focuses on optimal control under bounded disturbances, ellipsoid-based methods, adaptive control, and machine learning applications in control systems. He teaches courses such as AER124 (Analysis and Modelling of Aerospace Systems), ACS232 (Signals, Systems and Communications), AER203 (Control Systems), and ACS330 (Group Projects). Education: 2015: Bachelor’s in Control in Technical Systems (First Class Honours), ITMO University 2017: Master’s in Mechatronics and Robotics (First Class Honours), ITMO University 2021: PhD (Candidate of Technical Sciences), ITMO University (Thesis: Development of ellipsoid-based methods for disturbance/noise rejection) Research Interests: His work emphasizes robust control strategies, invariant/attractive ellipsoids methods, optimization, and integrating machine learning into control systems. He contributes to the Control Theory research group at ACSE. Teaching & Roles: Coordinates School Student Projects and teaches core engineering courses at the University of Sheffield. Previously held academic roles at ITMO University’s Faculty of Control Systems and Robotics.