جست‌وجوی استاد و پژوهشگر

Colin Jonesمشاهده پروفایل

دانشیار

• Optimal Control
• Model Predictive Control
• Optimization
• +۶ مورد دیگر

Colin Jones is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Automatic Control Laboratory, School of Engineering. He earned his BASc and MASc in Electrical Engineering and Mathematics from the University of British Columbia (1994-2002) and a PhD in Control Theory from the University of Cambridge (2002-2005). Prior to EPFL, he was an assistant professor there and a senior researcher at ETH Zürich. Current role: Director of the Robotics, Control, and Intelligent Systems Doctoral Program at EPFL Research focus: Optimization-based and model predictive control (MPC) for renewable energy systems, green energy management, and data-driven control methods His recent work (2023-2025) spans high-speed predictive control , smart grid optimization , and physically consistent neural networks , with applications to buildings, hovercrafts, and power systems. He has secured an ERC Starting Grant for his research on optimal control of building networks. Publications include over 200 papers in journals like Automatica , IEEE Transactions , and Energy and Buildings . Notable article trends include distributed optimization , data privacy in energy systems , and nonlinear MPC for autonomous vehicles . Scientific Awards : ERC Starting Grant for optimal control of building networks Advising : Supervises 10 current PhD students and has advised 19 past PhD students, including Alessandretti Andrea and Diwale Sanket Sanjay. Grants and projects emphasize smart energy systems , predictive demand response , and nonlinear control .

Cristian Gómez Canelaمشاهده پروفایل

استاد

• Environmental Chemistry
• Analytical Chemistry
• Mass Spectrometry
• +۵ مورد دیگر

Cristian Gómez Canela is a Full Professor in the Department of Analytical and Applied Chemistry at the School of Engineering, Ramon Llull University (IQS). He serves as Coordinator of the Master's Degree in Analytical Chemistry and is an active member of the Catalan Chemical Society (SCQ), representing SCQ in EuChems-EYCN. His academic journey includes a PhD in Chemistry from the University of Barcelona (2014), followed by postdoctoral research at IDAEA-CSIC and King's College University. Dr. Gómez Canela's research focuses on environmental analytical chemistry, particularly the optimization and validation of analytical methods based on liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and high-resolution mass spectrometry (HRMS) for determining organic pollutants in environmental samples. His work extends to metabolomics applied to aquatic organisms and the analysis of neurotoxic compounds in water systems. His research fingerprint reveals strong expertise in zebrafish models (100%), neurotransmitter analysis (66%), Daphnia magna studies (64%), and neurotoxicity assessment (21%). His recent publications (2024-2025) demonstrate a clear trend toward environmental neurotoxicology, with emphasis on the effects of pharmaceuticals and industrial pollutants on aquatic organisms. His work integrates advanced analytical techniques with biological endpoints to assess environmental risks, particularly focusing on neurological and cardiovascular impacts. The research spans method development for pollutant detection, environmental monitoring, and mechanistic studies of neurotoxic effects. Dr. Gómez Canela leads multiple significant research projects including CHEMIPARK (2024-2027) on passive sampling methodologies for environmental pollutants, GESPA (2022-2025) as part of the Environmental Process Engineering and Simulation Group, and several projects on neuroactive compounds in water systems. He has an impressive research output with 91 scientific publications from 2011-2025 and an h-index of 27 with over 2,000 citations. As a dedicated educator, he contributes to multiple academic programs including the Master in Analytical Chemistry, Master in Pharmaceutical Chemistry, and undergraduate degrees in Chemistry and Chemical Engineering. His research group GESPA represents a multidisciplinary team combining chemical engineering, biotechnology, and chemical analysis to advance environmental sustainability through theoretical and experimental approaches.

Bingzhang Chenمشاهده پروفایل

مدرس ارشد

• Biological oceanography
• Theoretical Ecology
• Ecosystem modeling
• +۹ مورد دیگر

Bingzhang Chen is a Senior Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. He previously held positions as a Chancellor’s Fellow at the same institution, a researcher at the Japan Agency of Marine-Earth Science and Technology (JAMSTEC), and was affiliated with Xiamen University and Mount Allison University. His academic journey began with a PhD from the Hong Kong University of Science and Technology. Education: PhD in Trophic interactions within the microbial food web, Hong Kong University of Science and Technology (Awarded 2009) His primary research interests lie at the intersection of biological oceanography and theoretical ecology, with a strong focus on ecosystem modeling. He investigates how biodiversity, particularly of phytoplankton, influences marine ecosystem functioning such as primary production and the biological carbon pump. A central theme in his work is understanding the differential temperature sensitivity between autotrophs and heterotrophs, a question that bridges statistical analysis, metabolic theory, and Earth system science. His recent publications highlight a consistent trend in developing and applying individual-based models (e.g., PIBM 1.0), analyzing large datasets on plankton thermal responses, and studying the impacts of climate change and anthropogenic activities (like nutrient input) on marine microbial communities across diverse regions from the South China Sea to the North Pacific and Scottish coastal waters. His work often combines modeling with observational data to address fundamental ecological questions. Scientific Awards: David Cushing Prize (2015) from the Journal of Plankton Research New Century Excellent Talent (2012) from the Ministry of Education of China Dr. Chen is actively involved in research supervision, currently guiding five PhD students. He has been the Principal Investigator on multiple research projects funded by organizations such as the Leverhulme Trust, FILAMO, and the National Science Foundation. His expertise in programming (R, Fortran, MATLAB) underpins his methodological approach. He also contributes to the scientific community as an Associate Editor for the prestigious journal Limnology and Oceanography . His work is associated with efforts to understand and model invasive species dynamics, such as the spread of Sargassum muticum in Scottish waters, and he is involved with external advisory groups like the MASTS Marine Artificial Intelligence Forum.

• Geomechanics
• Geophysics
• Numerical Modeling
• +۵ مورد دیگر

Dr. Moritz Ziegler is a geomechanics researcher affiliated with the Technical University of Munich (TUM) and the Assistant Professorship of Geothermal Technologies . He previously worked at GFZ Potsdam (2017–2023) and earned his PhD in Geophysics from the University of Potsdam (2014–2017). His research focuses on geomechanical numerical modeling , uncertainty quantification , and 3D stress field analysis , with applications to geothermal energy, seismic hazard, and rock mechanics. Education: Bachelor of Science in Geosciences (2008–2011), Freie Universität Berlin Master of Science in Geophysics (2011–2014), University of Potsdam PhD in Geophysics (2014–2017), University of Potsdam & GFZ Potsdam His work integrates advanced computational methods ( Altair Hypermesh , Dassault Systèmes Abaqus , Python , Matlab ) to address complex geomechanical problems. Recent publications analyze stress gradients in the North Alpine Foreland Basin, fault-stress interactions, and physics-based machine learning in geomechanics. He has contributed to software development (DOuGLAS v1.0) and calibration tools (FAST Calibration v2.4). Scientific awards or honors are not explicitly mentioned in the provided text. However, his research has been published in leading journals such as Geophysical Journal International , Solid Earth , and Pure and Applied Geophysics .

Riccardo Raheliمشاهده پروفایل

استاد

• Telecommunications
• Digital Signal Processing
• Wireless Communications
• +۵ مورد دیگر

Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.

• Industrial Organization
• Game Theory
• Econometrics
• +۵ مورد دیگر

C. Lanier Benkard is the Gregor G Peterson Professor of Economics at the Graduate School of Business, Stanford University. He is a prominent researcher in industrial organization, game theory, and econometrics, focusing on dynamic models of market competition and structural estimation. Research Interests: His work spans Dynamic games and equilibrium modeling Hedonic pricing and demand estimation Econometric tools for imperfect competition Computational methods for large-scale industries Publication Trends: His research emphasizes oblivious equilibrium approximations, strategic interactions in concentrated industries, and empirical analysis of markets with heterogeneous consumers. He frequently collaborates with scholars like Gabriel Weintraub and Patrick Bajari. Tools & Extensions: He has developed computational resources, including C++ and Matlab code, to analyze oblivious equilibrium. Current work includes extensions to Markov Perfect Industry Dynamics and aggregate shock modeling.

• Embedded Systems
• Artificial Neural Networks
• Signal Processing
• +۳ مورد دیگر

Magdalena Szymczyk is a Lecturer in the Department of Biocybernetics and Biomedical Engineering at AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. Her work bridges embedded systems, biomedical signal processing, and geophysical data analysis. Research focuses on energy-efficient sensor networks, neural networks for GPR data classification, and mathematical transforms in signal analysis Expertise in parallel computing, real-time systems, and biomedical engineering applications Her publications (2015–2025) demonstrate a trajectory from parallel neural networks and S-transform/GPR methodologies to recent work on MicroPython in embedded systems. Key themes include energy optimization in distributed architectures and AI-driven signal processing across biomedical and geophysical domains. She has authored works on deterministic chaos in simulations, GPU image processing, and cybersecurity in microcontroller systems. Her current research emphasizes embedded systems security, medical signal diagnostics, and computational methods for geological analysis. She utilizes tools like OpenCL for GPU acceleration and MATLAB for parallel computing implementations.

• Robotics
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Mohammad Alshibli serves as an Assistant Professor in the Department of Computer Systems at Farmingdale State College under a 10-month appointment, teaching courses including Introduction to Robotics, Computer Networks, Operating Systems, Database Systems, Programming Languages (C/C++/C#/Python/Matlab/Java/VB.NET), and Artificial Intelligence. His academic credentials: Ph.D. in Computer Science and Engineering (Artificial Intelligence and Robotics), University of Bridgeport, 2018 Master's in Computer Science, Albalqa Applied University, Elsalt, Jordan, 2011 B.S.c in Computer Science, Philadelphia University, Amman, Jordan, 2006 His research integrates Robotics, Artificial Intelligence, and Machine Learning to develop cognitive robotic systems for electromechanical disassembly sequencing and navigation optimization. Recent work presented at Farmingdale State College's Celebration of Scholarship and the LI Regional Virtual CSTEP Research Conference demonstrates applications in 3D-printed sketching robots, orthogonal array robust design, and heuristic optimization algorithms for end-of-life product disassembly.

• Robotic Systems
• Intelligent Computing
• Artificial Intelligence
• +۳ مورد دیگر

Nuno Miguel Fonseca Ferreira is a Full Professor at the Instituto Superior de Engenharia de Coimbra (ISEC), part of the Polytechnic of Coimbra, where he currently serves as President of the Scientific Council. His academic career spans over 25 years at ISEC, progressing from Assistant to Professor Coordenador Principal. He has held significant leadership positions including Vice-President of ISEC (2001-2005), Pro-President of the Polytechnic of Coimbra (2009-2010), President of ISEC (2010-2013), and Vice-President of the Polytechnic of Coimbra (2013-2017), where he was responsible for internationalization initiatives. His educational background includes a degree in Electrical Engineering from the University of Porto (1996), a Doctorate in Electrical Engineering from the University of Trás-os-Montes and Alto Douro (2006), and a Habilitation Title (Aggregation) from the same institution (2020). His research focuses on Robotic Systems, with specialization in cooperative robotic systems as evidenced by his Habilitation work. Professor Ferreira's research spans multiple domains of robotics and intelligent systems, with particular emphasis on multi-robot coordination, environmental applications, and medical robotics. His work bridges theoretical control systems with practical applications across diverse fields including forestry, healthcare, manufacturing, and education. He has developed innovative approaches to robotic manipulation, sensor integration, and human-robot interaction, often incorporating advanced techniques from artificial intelligence and machine learning. His recent publications demonstrate a strong trend toward practical applications of robotics in real-world environments, particularly in forestry maintenance, industrial automation, and medical applications. The research shows progression from theoretical control systems to applied robotics in challenging environments, with increasing integration of computer vision, deep learning, and collaborative systems. His work spans both fundamental robotics research and immediate industrial applications, reflecting a balance between academic inquiry and practical implementation. Professor Ferreira has supervised two doctoral theses and participated in numerous research projects with substantial funding. His leadership extends to coordinating 15 of the 33 national and international R&D projects he has participated in, demonstrating significant grant acquisition and management capabilities. His international collaborations through Erasmus+ and other European programs highlight his role in fostering global research partnerships. He is an integrated member of GECAD (Research Group in Engineering and Intelligent Computing for Innovation and Advanced Development), a Portuguese R&D unit classified as Excellent by the Portuguese Science and Technology Foundation. Additionally, he is a member of LASI (Associated Laboratory for Intelligent Systems), the Portuguese laboratory associated with Artificial Intelligence, connecting him to a broader national research ecosystem.

Jeeseop Kimمشاهده پروفایل

استادیار

• Robotics
• Autonomy
• Control Theory
• +۳ مورد دیگر

Jeeseop Kim is an Assistant Professor in the Department of Aerospace and Mechanical Engineering at The University of Texas at El Paso (UTEP), College of Engineering, specializing in robotics, autonomy, and control theory. His research focuses on safety-critical planning and control, with emphasis on bipedal/quadrupedal locomotion, hybrid dynamical system control, and whole-body planning and control. Education: B.S. in Mechanical and Aerospace Engineering, Seoul National University (2014) M.S. in Intelligence and Information (Robotics), Seoul National University (2017) Ph.D. in Mechanical Engineering, Virginia Tech (2022) Postdoctoral Scholar, Mechanical and Civil Engineering, Caltech (2022–2025) His research spans safety-critical control systems for legged robots, including obstacle-aware nonlinear model predictive control (MPC), control barrier functions, and distributed coordination algorithms. Recent work explores adaptive delay estimation, tactile sensing for robotic grasping, and hardware-software co-design for humanoid robots. Key article trends highlight advancements in autonomous inspection robotics, hybrid control architectures, and real-time planning for quadrupedal systems. His work integrates control theory with practical applications in industrial and healthcare domains. Awards: ASME DSCD Rudolf Kalman Best Paper Award (2022) IEEE ICRA Outstanding Paper Award (2023) Jeeseop teaches MECH 4332: Mechanical Computational Applications in Vision and Robotics (Fall 2025). He actively recruits Ph.D. students for Spring/Fall 2026 and seeks motivated undergraduates/MS students with skills in robotics kinematics, programming (C/C++, Python, MATLAB), and CAD design. The AIGIS Lab welcomes applicants with interests in robotics, controls, and autonomous systems.

Shiguo Jiangمشاهده پروفایل

دانشیار

• Geospatial Information Technologies
• Land Use/Land Cover Change
• Forest Ecosystem Dynamics
• +۴ مورد دیگر

Shiguo Jiang is a tenured Associate Professor in the Department of Geography, Planning, and Sustainability at the University at Albany's College of Arts and Sciences. Currently on sabbatical during Fall 2025, he maintains active research leadership through the Spatial Analysis Laboratory. His affiliations extend to the PhD Program in Information Science (College of Emergency Preparedness, Homeland Security and Cybersecurity) and the MS Program in Biodiversity, Conservation, and Policy (Department of Biological Sciences), reflecting his interdisciplinary approach. Dr. Jiang's educational background includes a PhD from Ohio State University (2012), an MS from Peking University (2004), and dual BS/BA degrees from Peking University (2001). His research integrates geospatial technologies with spatial statistics to investigate land use dynamics, forest ecosystems, and human-environment interactions. Key application areas include urban systems analysis, climate change modeling, and crime pattern detection, with notable fieldwork in the Maya Forest of Belize. His publication portfolio reveals an evolution from urban fractal analysis (early Beijing studies) toward integrated socio-ecological research, with recent emphasis on crime geospatial modeling and climate-ecosystem interactions. The 15 most recent articles demonstrate methodological innovation in remote sensing reconstruction and spatial statistics, applied across environmental, criminological, and public health domains. Dr. Jiang actively mentors graduate students across departments including Geography, Sociology, Information Science, and Criminal Justice. While currently unable to fund Graduate Research Assistants, he collaborates with students who secure external funding. His Spatial Analysis Laboratory requires technical proficiency in programming (Python/R/Matlab) and geospatial software, welcoming undergraduates through postdoctoral researchers with relevant skills.

Jianxi Gaoمشاهده پروفایل

دانشیار

• Network Science
• Artificial Intelligence
• Control Theory
• +۳ مورد دیگر

Jianxi Gao is an Associate Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI). His research focuses on network science, particularly network resilience, robustness, and control, integrating network theory, control theory, statistical physics, and operations research. He also explores the intersection of network science and AI, including applications of AI to network analysis and vice versa. His work aims to understand, predict, and control the resilience of complex systems against cascading failures. Key research areas include network resilience in transportation systems, quantum networks, and biological systems, with applications to pandemic response and infrastructure optimization. Gao's contributions span theoretical frameworks and computational tools, such as the NuRsE MATLAB package for network resilience analysis. His GitHub repositories (e.g., NuRsE and NON) showcase his open-source contributions to network science and computational methods. His recent publications address topics like AI-driven network analysis, quantum network percolation, and pandemic-induced healthcare system stress. He actively collaborates on interdisciplinary projects, emphasizing real-world applications of network science principles.

Javier Peñaمشاهده پروفایل

استاد

• Operations Research
• Convex Optimization
• First-Order Methods
• +۵ مورد دیگر

Javier Peña is the Bajaj Family Chair Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University, where he has been a faculty member since 1999. He currently holds the rank of Professor with tenure in the Department of Operations Research. His educational background includes: PhD in Applied Mathematics from Cornell University (1998) MS in Computer Science from Cornell University (1997) MS in Mathematics from Universidad de Los Andes, Bogotá, Colombia (1993) BS in Electrical Engineering from Universidad de Los Andes, Bogotá, Colombia (1991) BS in Mathematics from Universidad de Los Andes, Bogotá, Colombia (1991) Professor Peña's research focuses on the theoretical foundations and practical applications of optimization. His primary research interests include condition numbers for optimization, algorithms for convex optimization (particularly first-order methods), and equilibria computation. He has made significant contributions to understanding the convergence properties of the Frank-Wolfe algorithm and related first-order methods. His work uniquely bridges theoretical analysis with practical applications, particularly in finance and data science. His research demonstrates a consistent pattern of investigating the fundamental mathematical properties of optimization problems while developing practical algorithms with provable convergence guarantees. His extensive publication record shows a clear evolution from foundational work on condition numbers and Hoffman constants toward more applied research on first-order methods and their applications. A notable trend is his recent focus on affine-invariant analysis of optimization algorithms, which provides deeper insights into algorithm behavior independent of coordinate systems. His work frequently appears in top optimization journals like Mathematical Programming and SIAM Journal on Optimization. Professor Peña is also the co-author of the influential textbook 'Optimization Methods in Finance,' now in its second edition, which has become a standard reference in the field. In terms of teaching, Professor Peña regularly instructs courses in Probability and Statistics, Financial Optimization, and Convex Optimization. His teaching approach emphasizes practical applications, with students in Financial Optimization routinely using open-source financial datasets like Alpha Advantage Open Stock API in their projects. He has been actively involved in the academic community through numerous conference presentations, seminar invitations, and committee service at Carnegie Mellon University, including roles on the Faculty Senate, Promotion and Tenure Committee, and various curriculum committees.

• Electric Power Systems
• Renewable Energy Systems
• Control Systems
• +۳ مورد دیگر

Mahmoud Khalifa Abdelhamid Khalifa is a Researcher at the Institute for Research in Technology (IIT) of Comillas Pontifical University, affiliated with the Higher Technical School of Engineering (ICAI). He holds a B.Sc. (2019, first class honors) and M.Sc. (2023) in Electrical Engineering from Minia University, Egypt. His current role involves predoctoral research in electrical systems, focusing on battery energy storage systems and their impact on low-inertia power systems stability. Education: B.Sc. Electrical Engineering, Minia University (2019), ranked first in class M.Sc. Electrical Engineering, Minia University (2023) Research Interests: Mahmoud’s work centers on modeling, control, and stability analysis of energy storage systems, particularly in the context of renewable energy integration. His expertise includes doubly-fed induction generators (DFIG), grid stability, and advanced control algorithms for wind and solar systems. Publications & Contributions: He has authored/co-authored peer-reviewed journal articles, conference papers, and a book on DFIG control systems. His work emphasizes optimizing dynamic performance in renewable energy systems and enhancing grid reliability through advanced control techniques. Affiliations & Skills: Mahmoud is proficient in MATLAB/Simulink, PLC programming (Siemens SIMATIC STEP 7), and tools like Arduino C, Microsoft Office, and SPSS. His research is supported by institutional affiliations with IIT and Minia University. Labs/Teams: Engaged in IIT’s electrical systems research group, contributing to projects on smart grids and energy storage solutions.

Monica Martinez Wilhelmusمشاهده پروفایل

استادیار

• Sea Ice Dynamics
• Remote Sensing Observations
• Fluid Transport
• +۳ مورد دیگر

Dr. Monica Martinez Wilhelmus is the Thomas J. and Alice M. Tisch Assistant Professor of Engineering at Brown University's School of Engineering. She holds affiliations with NASA Jet Propulsion Laboratory (JPL) and is an adjunct professor at the University of California Riverside. Her research integrates experimental and numerical methods to study transport phenomena at the intersection of biology, oceanography, and fluid mechanics. Key interests include sea ice dynamics, remote sensing, and fluid transport by plankton aggregations. Education: B.Sc. in Mechanical Engineering from Universidad Nacional Autonoma de Mexico (2010), M.S. and Ph.D. in Mechanical Engineering from Caltech (2012, 2016). Her postdoctoral work at JPL/Caltech focused on collaborative ocean science projects. Research in the Wilhelmus Lab explores fluid mechanics in environmental and biological systems, with projects like Arctic sea ice tracking, robotic platforms, and plankton hydrodynamics. The lab's work bridges engineering and environmental science to address climate observation challenges and ocean turbulence. Her interdisciplinary approach combines satellite data analysis with field experiments, contributing to understanding Arctic Ocean eddies and submesoscale currents. Collaborative efforts include developing algorithms for ice floe tracking and advancing sediment diagenesis models.