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Ceyhun YildizView profile

Lecturer

• Renewable Energy Systems
• Power Electronics
• Artificial Intelligence
• +3 more

Ceyhun Yildiz is a Doctor Lecturer at the Circuits and Systems Department within the Faculty of Engineering and Natural Sciences at Bandırma Onyedi Eylül Üniversitesi. Previously, he held academic positions at Kahramanmaraş İstiklal University and Kahramanmaraş Sütçü Imam University, serving as Department Head at Kahramanmaraş İstiklal University's Elbistan Vocational School. His academic career spans over a decade with roles including research assistant (2005-2008) and lecturer positions in Electrical Engineering. His research focuses on renewable energy systems, power electronics, and artificial intelligence applications in energy sectors. Key interests include wind energy optimization, machine learning-driven forecasting (e.g., wind power, solar output, electricity prices), and hybrid energy system integration. He has led projects on optimal turbine placement, energy storage solutions, and grid stability analysis. Yildiz has authored/co-authored over 40 publications, with recent works emphasizing deep learning models for electricity load forecasting and wind farm layout optimization. He teaches graduate courses on machine learning applications in engineering and has supervised master's theses on solar power estimation and hybrid energy systems. His work integrates theoretical and applied research, addressing challenges in renewable energy scalability and grid compatibility.

Pietro De LellisView profile

Associate Professor

• Complex Networks
• Automatic Control
• Synchronization and Consensus
• +7 more

Pietro De Lellis is an Associate Professor of Automatic Control at the University of Naples Federico II, Italy. He holds a PhD in Automation Engineering (2009) from the same institution and has held visiting roles at NYU Polytechnic School of Engineering, including a Visiting Professorship (2010) and Postdoctoral Fellowships (2012–2014). His academic roles also include Adjunct Professor at the Italian Air Force Institute of Technology (2010–2014). His research focuses on complex networks, synchronization, control, and co-evolving systems in finance and biology, with collaborations at NYU and international institutions. Education: PhD in Automation Engineering (2009), University of Naples Federico II. Visiting scholar at NYU Polytechnic Institute (2009). Postdoctoral fellowships funded by Forgiare (2010), MASTRI (2012), and NYU projects on collective behavior and robotics. Research interests span analysis/synchronization of complex networks, collective behavior in animal groups, formation control, co-evolving financial networks, partial control strategies, and networks of discontinuous systems. Recent projects include the ACROSS initiative on stochastic systems and evolving networks. His work bridges theoretical control with experimental validation (e.g., Chua’s circuits experiments). Publications reflect interdisciplinary focus: synchronization in networks, pinning control algorithms, and applications to financial markets, robotics, and epidemiological modeling (e.g., 2020 Italian COVID-19 network analysis). Active in grants and collaborations, including EU-funded projects and industry partnerships. Teaching includes courses on system analysis and control of complex systems at the University of Naples. Labs: NYU Dynamical Systems Lab (collaborations), Electrical Engineering Lab (experimental setups).

• Robotics
• Control Systems
• Marine Engineering
• +3 more

Amer Orucevic is a Research Fellow at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His research focuses on advanced control methodologies for underwater snake robots, emphasizing practical stability, trajectory tracking, and environmental interaction. He specializes in nonlinear control systems, model predictive control, and extremum-seeking algorithms applied to autonomous marine robotics. Orucevic has contributed to multiple international conferences and journals, including the IEEE Transactions on Control Systems Technology and Control Engineering Practice. His work addresses challenges in positioning robots within complex marine environments like vortex wakes and optimizing sinusoidal gait patterns for efficient locomotion. Key Research Areas: Underwater Robotics, Nonlinear Control, Autonomous Systems Conference Contributions: Presented at 2022 IEEE Conference on Control Technology and Applications, 2023 IFAC World Congress, and 2024 IFAC Conference on Marine Systems

Mark A. MinorView profile

Associate Professor

• Robotics
• Mobile Robotics
• Autonomous Vehicles
• +5 more

Mark A. Minor is an Associate Professor in the Department of Mechanical Engineering at the University of Utah's College of Engineering, where he serves as Director of the Robotics Systems Lab and Coordinator of the Robotics Track within Mechanical Engineering. His research spans multiple domains of robotics including climbing robots, terrain adaptable mobile robots, virtual interfaces, autonomous vehicles, and flying robots. The Robotics Systems Lab under his direction synergizes design, modeling, and control to create novel robotic embodiments with enhanced adaptability, mobility, and immersion. Dr. Minor's research focuses on the synergistic integration of design, modeling, and control of robotic systems. His lab specializes in several types of robotic systems including climbing robots, terrain adaptable mobile robots, virtual interfaces, autonomous vehicles, and flying robots. With extensive expertise in the design and control of under-actuated nonholonomic systems, kinematic motion control, dynamic motion control, state estimation, sensor development, and data fusion, his work pushes the boundaries of what robotic systems can achieve in challenging environments. His research portfolio demonstrates a consistent focus on practical robotic applications across multiple domains. Recent work shows increasing emphasis on immersive virtual environments with wind, olfactory, and thermal displays, as well as sophisticated control systems for autonomous vehicles and terrain-adaptive locomotion. The integration of haptic feedback, multi-sensory stimulation, and soft robotics components represents an emerging trend in his research trajectory, bridging the gap between physical robotics and human perception. Dr. Minor has successfully advised numerous graduate students through completion of their degrees, with alumni now working at institutions including Harbin Institute of Technology, University of Utah, Orbital Sciences Corporation, and Western Digital Corporation. His research has been supported by prestigious sponsors including the National Science Foundation, NASA, Army Night Vision Lab, and industry partners such as ATK Launch System and Kairos Autonomi. The Robotics Systems Lab, directed by Dr. Minor, maintains several active research projects including Hybrid Mobility Research (investigating robots capable of rolling, walking, and climbing), Autonomous Vehicle Research (particularly related to the DARPA Urban Challenge), Traction Sensing and Control in Wheeled Mobile Robots, Immersive Virtual Environments (including the TreadPort Active Wind Tunnel), and Compliant Framed Modular Mobile Robots. The lab continues to push the boundaries of robotic mobility, control, and human-robot interaction.

İsmail BayezitView profile

Assistant Professor

• Unmanned Aerial Vehicles
• Flight Control Systems
• Autopilot Design
• +3 more

Dr. İsmail Bayezit serves as an Assistant Professor in the Department of Aeronautical Engineering at Istanbul Technical University (ITU), Turkey, with active research since 2007. His work bridges aerospace and marine engineering domains, focusing on unmanned systems and control technologies. With an h-index of 8 and 321 Scopus citations across 33 research outputs, he has secured 6 major research projects including VTOL system development and marine craft autonomy initiatives. His research fingerprint reveals dominant expertise in Quadcopter Engineering (100%), Motion Control (81%), and Unmanned Aerial Vehicle systems (80%). He specializes in advanced control methodologies including extremum-seeking control, LQR techniques, and distributed control strategies. Current work extends into AI-integrated navigation systems and energy-optimized flight performance, with significant crossover applications in marine craft control and underwater acoustics. Recent publications (2024-2025) demonstrate three converging trends: optimization of electric multirotor performance through energy-aware control, neural network-assisted navigation for GPS-denied environments, and cross-domain applications of control theory to both aerial and marine systems. His work increasingly integrates artificial intelligence with traditional control frameworks while maintaining strong experimental validation through physical prototypes. Bayezit has supervised 21 students and led 6 research projects from 2017-2025, including EU-funded initiatives on VTOL systems and national projects on UAV education sets. His project portfolio shows consistent progression from fundamental control theory (2017-2019) toward applied AI integration (2023-2025), with recent work focusing on autonomous marine craft instrumentation and next-generation UAV performance optimization.

• Sustainable Energy Systems
• Numerical Optimization
• Deep Learning
• +3 more

Dr. Manuel Dahmen serves as Head of Department at the Institute of Climate and Energy Systems (ICE-1) within the Research Center Jülich. His research focuses on designing sustainable and cost-efficient energy systems through numerical optimization and deep learning techniques. He leads efforts in advancing energy system technology, particularly in optimizing renewable energy integration, process network analysis, and the co-design of fuels and engines. His work emphasizes innovative applications of machine learning, such as physics-informed neural networks and reinforcement learning, to address challenges in energy system design and operation. Key areas include reducing greenhouse gas emissions in industrial processes, optimizing energy networks, and developing data-driven models for dynamic process control. Dr. Dahmen’s contributions span algorithm development (e.g., MUSE-BB decomposition algorithms), energy system scenario generation, and robust design methodologies under uncertainty. His research bridges computational methods with practical energy solutions, aiming to achieve decarbonization in industries like copper production and transportation. Publications highlight advancements in renewable energy integration, fuel design for spark-ignition engines, and the application of graph neural networks for molecular property prediction. His interdisciplinary approach fosters collaboration across chemical engineering, computer science, and energy economics to tackle global sustainability challenges.

Masoud SalehiView profile

Associate Professor

• Error Correcting Codes
• Information Theory
• Digital Communications
• +5 more

Dr. Masoud Salehi is an Associate Professor and Associate Chair for Graduate Studies in the Department of Electrical and Computer Engineering at Northeastern University, USA. He holds a BS (Summa Cum Laude) from Tehran University and MS/PhD from Stanford University. Previously, he worked at Isfahan University of Technology and Tehran University. His research focuses on error-correcting codes, information theory, digital communications, and physical-layer security. He has authored influential textbooks including Communication Systems Engineering (Prentice-Hall) and Contemporary Communication Systems Using MATLAB . Education: BS (Tehran U.), MS/PhD (Stanford U.). Visiting Professor at Eindhoven University of Technology (1988-1989). Research Interests : Network information theory, source-channel matching, data compression, turbo coding, coding for fading channels, digital watermarking. Recent work emphasizes physical-layer security in multi-user wireless networks and jamming mitigation strategies. Grants & Industry : Supported by NSF, GTE, NUWC, CenSSIS, Analog Devices. Consulted for Teleco Oilfield Services and AT&T. Awards : 2024 Outstanding Faculty Service Award. Editorial Board member of International Journal of Electronics and Communications . Key Contributions : Developed precoding techniques for MIMO systems, game-theoretic jamming mitigation, and LDPC decoding algorithms. Active in the Institute of Information Assurance (IIA) and Communications, Control & Signal Processing research group at Northeastern.

Tuna BalkanView profile

Professor

• Control Systems
• Robotics
• System Dynamics
• +5 more

Prof. Tuna Balkan is a Professor in the Mechanical Engineering Department at Middle East Technical University (METU), Ankara, Turkey. He holds a B.Sc. (1979), M.Sc. (1983), and Ph.D. (1988) from METU. His research focuses on control systems, robotics, fluid power control, and dynamic modeling. He leads the Control Systems Laboratory at METU and teaches courses such as Control Systems (ME 304), Fluid Power Control (ME 516), and Mechanical Engineering Systems Laboratory (ME 410). His work spans hydraulic actuator design, platform stabilization, and industrial robotic applications like spray painting and arc welding. Research interests include real-time control, Kalman filtering, and energy-efficient hydraulic systems. He has supervised numerous theses, including studies on hydraulic load simulators, energy-efficient actuators, and vibration-based energy harvesting. His publications cover topics like instability analysis in hydraulic systems, friction compensation in motion platforms, and microelectromechanical systems (MEMS) for energy harvesting. Prof. Balkan’s lab, Control Systems Lab (Room G-130), develops advanced control algorithms and experimental setups. His contributions to automotive safety, agricultural machinery design, and robotic spray painting have been widely recognized. He has collaborated on projects involving durability test rigs, unmanned aerial vehicles, and sensor integration for industrial applications.

Tomasz R. BieleckiView profile

Professor

• Mathematical Finance
• Stochastic Analysis
• Credit Risk
• +5 more

Tomasz R. Bielecki is a Professor in the Department of Applied Mathematics at Illinois Institute of Technology (IIT). He serves as Director of the Professional Master in Mathematical Finance program at IIT. His research interests span stochastic analysis, stochastic processes, mathematical finance, credit risk, counterparty risk, performance measures, stochastic control, semigroup theory, and functional analysis. He has held editorial roles at journals including SIAM Journal of Financial Mathematics and International Journal of Theoretical and Applied Finance. Bielecki has collaborated with numerous researchers such as Igor Cialenco, Stephane Crepey, and Monique Jeanblanc. His work includes influential books like Structured Dependence between Stochastic Processes and Counterparty Risk and Funding: A Tale of Two Puzzles . His recent publications focus on topics like Hawkes processes, dynamic risk measures, and stochastic control under model uncertainty. He has consulted for firms including Bank of America, Bloomberg, and Merrill Lynch. His research emphasizes applications in financial mathematics, credit risk modeling, and the development of robust frameworks for risk assessment and derivatives pricing.

• Biological Control Systems
• Nonlinear Systems and Control
• Robotics
• +4 more

Professor Zhiyong Chen is a faculty member at the University of Newcastle, affiliated with the School of Engineering and the Electrical and Computer Engineering Department. He holds the rank of Professor and specializes in control systems, robotics, and nonlinear dynamics. His research focuses on biological control systems, swarm intelligence, and adaptive control strategies for complex systems. Chen has authored influential textbooks such as Stabilization and Regulation of Nonlinear Systems: A Robust and Adaptive Approach (2015), which provides foundational knowledge in nonlinear control theory. Education: PhD from the Chinese University of Hong Kong. Research interests include multi-agent systems, fault-tolerant control, and reinforcement learning applications. His work emphasizes practical implementations in robotics, transportation systems, and aerospace engineering. He has contributed to over 212 journal articles and 119 conference papers, addressing challenges in distributed control, cybersecurity in cyber-physical systems, and autonomous synchronization. Chen's recent projects involve cooperative control of high-speed trains, resilient multi-agent systems under cyber attacks, and physics-informed reinforcement learning. His methodologies often integrate theoretical rigor with real-world applications, such as nanopositioning systems and fault diagnosis in mechanical systems. Grants and collaborations highlight his role in interdisciplinary research, combining control theory with machine learning and cryptography for secure networked systems. His lab focuses on advancing adaptive control techniques and their deployment in safety-critical environments.

Hillel ChielView profile

Professor

• Neural Networks
• Electrophysiology
• Biomechanics
• +7 more

Hillel Chiel is a Professor at Case Western Reserve University with joint appointments in the Department of Biology (College of Arts and Sciences), Department of Neurosciences (School of Medicine), Department of Biomedical Engineering (Case School of Engineering), and the Neural Engineering Center. His office is located in DeGrace Hall Room 304. Dr. Chiel leads a research laboratory focused on understanding how the brain and body generate adaptive behavior through neurophysiology, computational modeling, biomechanics, and robotics. Key research areas include: Neural control of feeding in Aplysia californica using MRI and 3D modeling Biologically-inspired robotic systems mimicking animal mechanics Wireless neural recording/stimulation techniques Infrared neural inhibition and thermal modulation of neural activity Neuromechanics of multifunctional behaviors His recent publications (2019-2021) demonstrate strong interdisciplinary focus on: computational neuroscience, infrared neural modulation techniques, biomechanics of invertebrate feeding systems, biomimetic robotics, and neuroprosthetic applications. Research consistently integrates experimental neurobiology with engineering principles.

Yunhui HeView profile

Assistant Professor

• Numerical Analysis
• Scientific Computing
• Finite Element Methods
• +5 more

Yunhui He is an Assistant Professor in the Department of Mathematics at the University of Houston. His research focuses on numerical analysis and scientific computing, with expertise in finite element methods, multigrid methods, and local Fourier analysis. He has held postdoctoral positions at institutions like the University of British Columbia and the University of Waterloo. His work includes contributions to preconditioning techniques, acceleration methods, and the numerical solution of partial differential equations. Education: PhD in Mathematics (2018), Memorial University of Newfoundland MSc in Computational Mathematics (2015), Chinese Academy of Sciences BSc in Mathematics and Applied Mathematics (2012), Capital Normal University Research Interests: Dr. He’s research emphasizes numerical methods for PDEs, multigrid algorithms, and iterative solvers. He explores topics like finite element methods, preconditioning strategies, and local Fourier analysis to enhance computational efficiency in fluid dynamics and optimal control problems. His work bridges theoretical analysis and practical implementation, with applications in engineering and physics. Articles Trends: Recent publications highlight advancements in multigrid relaxation schemes, Anderson acceleration for nonlinear PDEs, and preconditioners for coupled flow systems. His work often integrates local Fourier analysis to optimize solver performance, with applications to Stokes-Darcy equations and optimal control problems. Grants & Awards: He co-organized the 2025 NSF-funded CBMS Conference on Applied Mathematics and Machine Learning (DMS-2430460), demonstrating leadership in academic collaboration. Teaching: Taught courses including Linear Algebra, Partial Differential Equations, and Numerical Analysis at the University of Houston and other institutions. His pedagogical focus aligns with computational mathematics and scientific computing. Lab/Team: Hosts Santolo Leveque as a postdoctoral fellow (2024–present), advancing collaborative research in numerical methods and multigrid theory.

João Pedro HespanhaView profile

Professor

• Hybrid and Switched Systems
• Networked Control Systems
• Cooperative Control of Autonomous Agents
• +6 more

João Pedro Hespanha is a Distinguished Professor holding dual appointments in the Electrical and Computer Engineering and Mechanical Engineering departments at the University of California, Santa Barbara. He is affiliated with the Center for Control, Dynamical-Systems and Computation (CCDC) and the Institute for Collaborative Biotechnologies, where he leads research at the intersection of control theory, networked systems, and biological applications. Dr. Hespanha has established himself as a leading authority in hybrid systems and networked control with significant theoretical contributions and practical implementations. Dr. Hespanha received his Licenciatura and MS in Electrical and Computer Engineering from Instituto Superior Técnico in Lisbon, Portugal, before earning his PhD in Electrical Engineering and Applied Science from Yale University in 1998. After serving as an Assistant Professor at the University of Southern California from 1999-2001, he joined UC Santa Barbara in 2002 where he has remained ever since, rising to his current distinguished position. His educational background reflects a strong foundation in both theoretical mathematics and practical engineering applications. His research program spans multiple interconnected domains including hybrid and switched systems, networked control systems, cooperative control of autonomous agents, and systems biology. Dr. Hespanha's work on hybrid systems has fundamentally advanced the mathematical frameworks for modeling systems that combine continuous dynamics with discrete logic transitions. His research on networked control systems addresses critical challenges in communication-constrained environments, while his work in cooperative control tackles computational complexity and limited communication in multi-agent systems. His systems biology research applies control theory to model gene regulatory networks using stochastic hybrid systems. Dr. Hespanha's recent publications demonstrate consistent innovation across theoretical foundations and practical applications. His work shows a clear trajectory toward more complex networked systems, with increasing emphasis on security, resilience, and uncertainty quantification. The publications reveal strong interdisciplinary connections between control theory, computer science, and biology, with applications spanning autonomous vehicles, communication networks, and biological processes. Among his numerous accolades: Elevated to IEEE Fellow in 2008 for contributions to stability techniques for switched and hybrid systems Awarded the prestigious Ruberti Young Researcher Prize in 2009 Received the George S. Axelby Outstanding Paper Award in 2006 Honored with the Automatica Theory/Methodology best paper prize in 2005 Named IFAC Fellow in 2016 Received ACM SIGBED HSCC Best Paper Award in 2019 Dr. Hespanha has successfully mentored over 25 PhD students who have gone on to prominent positions in academia and industry. His research has been consistently supported by substantial funding from NSF, NIH, ONR, and other agencies, with current projects including pandemic management decision systems, precision drug delivery, and control of autonomous vehicle networks. He has taught numerous influential courses including Linear Systems Theory and Noncooperative Game Theory, authoring widely used lecture notes published by Princeton Press. Dr. Hespanha leads an active research group within the Center for Control, Dynamical-Systems and Computation, collaborating with researchers across engineering disciplines and biology. His lab maintains strong connections with industry partners working on autonomous systems, communication networks, and biological applications. He has organized major conferences including serving as General Chair for the 9th International Workshop on Hybrid Systems: Computation and Control in 2006, further establishing UCSB as a leading center for control systems research.

Marcel Vieira-LaraView profile

Assistant Professor

• Bioenergetics
• Biotechnology
• Metabolic Engineering
• +4 more

Dr. Marcel Vieira-Lara is an Assistant Professor at the Department of Biotechnology, Delft University of Technology (TU Delft), affiliated with the Faculty of Applied Sciences (TNW). His research group focuses on bioenergetics and quantitative biology applied to biotechnology, exploring metabolic strategies in organisms to develop sustainable applications. Key areas include energy transduction in industrially relevant organisms, metabolic engineering for yield improvement, and systems biology approaches integrating genetic, proteomic, and metabolic data. He teaches Microbial Physiology (LB2763) and Metabolic Engineering (LB2771) for the BSc Life Science and Technology program, co-developing courses with Rinke van Tatenhove-Pel. His group collaborates closely with the Industrial Microbiology section and emphasizes interdisciplinary research, combining experimental and computational methods. Current projects include mitochondrial ATP-Synthase engineering in yeast (supervised by Malte Marquardt) and studying fatty acid oxidation defects. His work addresses fundamental questions in bioenergetics while targeting applications in protein transition, alternative feedstocks, and industrial biotechnology.

Morten Bilde SimonsenView profile

Assistant Professor

• Biomechanics
• Osteoarthritis
• Gait Analysis
• +7 more

Morten Bilde Simonsen is an Assistant Professor at Aalborg University in the Department of Materials and Production, affiliated with the Section of Applied Systems Research and Biomechanics within the Faculty of Engineering and Science. His research focuses on biomechanics, musculoskeletal disorders, and the application of advanced technologies for clinical assessment and intervention. He holds a PhD awarded in April 2021. His work integrates biomechanical modeling, gait analysis, and proteomics to address conditions like knee osteoarthritis, rheumatoid arthritis, and pediatric obesity. A key project is the MathKOA initiative (2022–2027), a Novo Nordisk Foundation-funded effort developing predictive models for knee osteoarthritis. Research interests include gait mechanics, HIIT in youth obesity, and the biomechanical impact of interventions like foot orthoses. He has received awards such as the 2022 Best Presentation at the Regions Hospital Northern Jutland Symposium and the 2018 Danish Society of Biomechanics Student Award. His grants include leadership roles in multi-disciplinary projects combining clinical and engineering approaches. Collaborations span musculoskeletal modeling, sensor technology validation, and translational research in chronic pain and joint dysfunction. He is actively involved in lab-based studies on gait kinematics, biomarker identification, and exercise intervention efficacy.