جست‌وجوی استاد و پژوهشگر

Mathieu Salzmannمشاهده پروفایل

عضو هیئت علمی

• Computer Vision
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Mathieu Salzmann is a Senior Scientist and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Computer Vision Laboratory (CVLAB) in the School of Computer and Communication Sciences (IC). He also holds a courtesy appointment with the EPFL College of Humanities and serves as Deputy Chief Data Scientist at the Swiss Data Science Center (SDSC). He has held concurrent roles in teaching units including SIN, SODH, and SSC, reflecting his interdisciplinary engagement. His research focuses on the intersection of machine learning and computer vision, particularly in deep learning for 2D and 3D visual scene understanding, efficient and robust models, domain adaptation, and interpretable AI. These interests are evident across his extensive publication record in top-tier venues. His recent publications (2023–2024) show a consistent trend in advancing deep learning methods for visual recognition, with strong representation at CVPR, ICCV, ECCV, ICML, ICLR, and NeurIPS. Topics include domain generalization, 3D understanding, model robustness, and multimodal learning, often with applications in real-world systems. His editorial roles as Associate Editor for IEEE TPAMI and Action Editor for TMLR further highlight his leadership in the field. Area Chair: ICML 2023, CVPR 2023, ICCV 2023, NeurIPS 2023, AAAI 2024, ECCV 2024 Associate Editor: IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Action Editor: Transactions on Machine Learning Research (TMLR) Mathieu Salzmann has supervised numerous PhD students at EPFL, both current and past, including Bouquet Yann Yanis, Javed Saqib, Li Shuangqi, and others. He has also been involved in research grants and collaborative projects, such as his work with S. Süsstrunk and R. Baroni on comics reconfiguration. His part-time role as Senior GNC Engineer at ClearSpace (2020–2024) illustrates his applied research engagement in aerospace systems. He is actively involved in EPFL’s data science and AI research ecosystem through SDSC and multiple labs.

James Forbesمشاهده پروفایل

دانشیار

• Dynamics and Control
• Robotics
• Nonlinear Control
• +۵ مورد دیگر

James Forbes is an Associate Professor in the Department of Mechanical Engineering at McGill University. He holds the title of William Dawson Scholar and is affiliated with the Dynamics Estimation & Control of Aerospace & Robotics Systems research group. His primary research focus is on Dynamics and Control, with emphasis on navigation, guidance, and control (GNC) techniques for robotic systems. He teaches courses such as MECH 309 (Numerical Methods), MECH 412 (System Dynamics), and advanced topics in control systems. Forbes earned his Ph.D. in Aerospace Science and Engineering from the University of Toronto, following an M.A.Sc. from the same institution and a B.A.Sc. in Mechanical Engineering from the University of Waterloo. His research interests include nonlinear state estimation (batch methods, filtering), control synthesis via optimization (LQR, LMI approaches), and data-driven modeling using Koopman operator techniques. Applications span unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and SLAM systems. He has developed the navlie Python package for state estimation on Lie groups. Notable awards include the William Dawson Scholar distinction. His recent work focuses on multi-UAV localization, robust control algorithms, and sensor fusion techniques. He collaborates on projects involving UWB-based positioning and inertial navigation systems.

• Computational Logic
• Answer Set Programming
• Bioinformatics
• +۶ مورد دیگر

Alessandro Dal Palu' is an Associate Professor at the Department of Mathematical, Physical, and Computer Sciences at University of Parma. He holds a PhD in Computer Science from University of Udine and has been with University of Parma since 2005, transitioning from Researcher to Associate Professor in 2014. His teaching portfolio includes courses on Computer Architecture, Constraint Programming, and Algorithms & Data Structures. His research spans computational logic, bioinformatics, and GPU computing. Notable achievements include the 2007 GULP award for his Ph.D. thesis and the ICLP 2010 best paper award. He has led Italian INdAM-GNCS research projects on GPU applications (2011) and Logic Programming in cancer genomics (2016). Recent publications focus on explainable AI frameworks, bioinformatics applications, and sustainable logistics solutions. His work integrates Answer Set Programming with biomedical challenges like protein structure analysis and cancer genome evolution. He chairs the International Conference on Logic Programming (ICLP 2018) and has organized multiple international workshops on constraint programming. 2007 GULP Award ICLP 2010 Best Paper PI for INdAM-GNCS projects (2011, 2016) Program Committee member for international conferences

David McDanielمشاهده پروفایل

استاد پژوهشی

• Computational Fluid Dynamics (CFD)
• Aircraft Stability and Control
• High-Fidelity Simulations
• +۵ مورد دیگر

David McDaniel is a Research Professor (Not-In-Residence) at the University of Alabama at Birmingham (UAB), affiliated with the Department of Aerospace Engineering within the College of Engineering. He holds a B.S. in Aeronautical Engineering from the United States Air Force Academy, an M.S. in Mechanical Engineering from The George Washington University, and a Ph.D. in Aerospace Engineering from the University of Colorado at Colorado Springs. Dr. McDaniel’s career spans military service and academic research. He began as a US Air Force flight tester analyzing stability and control of aircraft like the B-1A and B-2A bombers. Later, he taught aerodynamics and thermodynamics at the US Air Force Academy while pioneering computational aerodynamics research in the Aeronautics Lab. Currently, he leads development of the Kestrel fixed-wing simulation tool under the DoD’s High Performance Computing Modernization Program (HPCMP CREATE™-AV). He is a senior member of the American Institute of Aeronautics and Astronautics (AIAA) and maintains an active DoD security clearance. His research focuses on high-fidelity CFD simulations for multidisciplinary aerospace problems, including hypersonic flows, aircraft stability/control modeling, and unstructured grid methods. His work supports defense acquisition efficiency through advanced simulation tools like Kestrel, which integrates aerodynamics, propulsion, and structural dynamics for fixed-wing aircraft analysis. Publications highlight advancements in surrogate modeling, machine learning for aerodynamic predictions, and high-performance computing optimizations. His contributions address challenges in CFD accuracy, scalability, and real-world applications for fighter aircraft and hypersonic systems.

Gianluca Zazaمشاهده پروفایل

استادیار

• mHealth
• Remote Patient Monitoring
• Cardiovascular Risk Assessment
• +۴ مورد دیگر

Gianluca Zaza is an Assistant Professor (non-tenure track) in the Computer Science Department at the University of Bari Aldo Moro, where he conducts research in healthcare technology and artificial intelligence applications. His work focuses on developing contact-less monitoring systems for vital signs and cardiovascular risk assessment using advanced computational techniques. Dr. Zaza's research interests span mHealth, remote patient monitoring, cardiovascular risk assessment, fuzzy inference systems, photoplethysmography, computer vision, and healthcare technology. His work demonstrates a strong focus on applying computational intelligence to solve real-world healthcare problems, particularly in the context of non-invasive monitoring solutions. His recent publications reveal a clear trend toward developing contact-less monitoring systems for vital signs, with particular emphasis on blood oxygen saturation and cardiovascular risk assessment. These works leverage neuro-fuzzy systems, remote photoplethysmography, and video imaging techniques to create practical healthcare solutions that have gained significant relevance during the pandemic era. Member of GNCS-INDAM (Gruppo Nazionale per il Calcolo Scientifico) of Istituto Nazionale di Alta Matematica Research supported by INdAM GNCS within the project 'Computational Intelligence methods for Digital Health' Associated with CITEL - Centro Interdipartimentale di Telemedicina Dr. Zaza's research has practical applications in telemedicine and remote patient monitoring, with potential to reduce the need for physical contact during health assessments, which became particularly valuable during the COVID-19 pandemic. His work bridges the gap between computer science, biomedical engineering, and clinical practice through innovative technological solutions.

Shawn Keshmiriمشاهده پروفایل

استاد

• Guidance Navigation and Control (GNC)
• Multi-Agent Unmanned Aerial Systems
• Aircraft Modeling and System Identification
• +۲ مورد دیگر

Dr. Shawn Keshmiri, the Spahr Professor at the University of Kansas, is a faculty member in the College of Engineering , Department of Aerospace Engineering . His research focuses on advanced guidance, navigation, and control systems for unmanned aerial vehicles, combining classical control theory with modern machine learning approaches. Education : B.S. from Shiraz University, M.S. from California State University, Los Angeles (CSULA), Ph.D. from the University of Kansas Dr. Keshmiri's work emphasizes nonlinear and robust control systems , multi-agent UAV coordination , and applications of artificial intelligence in adaptive aircraft control. His recent publications demonstrate expertise in: 3D path following via Lyapunov control Reinforcement learning-based flight controllers Control barrier functions for safety guarantees Wind shear and turbulence mitigation Multi-reference guidance algorithms

Mathias Hudoba de Badynمشاهده پروفایل

دانشیار

• Control Theory
• Networked Dynamical Systems
• Smart Buildings
• +۷ مورد دیگر

Mathias Hudoba de Badyn is an Associate Professor in the Department of Technology Systems (ITS) at the University of Oslo. He previously served as a postdoc at the Automatic Control Lab at ETH Zürich (2019-2023) working with John Lygeros and Roy Smith. His academic journey includes a PhD in Aeronautics and Astronautics from the University of Washington under Mehran Mesbahi, where he focused on distributed control theory. His research interests center on control and estimation of networked dynamical systems with emphasis on sustainability applications. Using algebraic graph theory, he investigates how network structure affects distributed control, estimation, and optimization algorithms. His primary application domains include smart buildings and energy hubs interconnected with the electric grid for demand-side management and peak shaving, as well as aerospace applications involving multi-vehicle systems from UAV swarms to distributed satellite systems. His recent publication trends show strong focus on distributed control algorithms applied to energy systems and aerospace applications, with increasing integration of machine learning techniques while maintaining theoretical rigor. His work spans from fundamental network theory to practical implementations in building control and spacecraft systems. Work package leader in CENSSS (Centre for Space Sensors and Systems) Involved with FME Solar Centre for Environmentally Friendly Research Active supervisor for numerous PhD and Master's students His research group has secured projects related to smart buildings, energy systems, and aerospace control, with recent work focusing on virtual power plants, spacecraft GNC, and AI validation in maritime automation. He maintains strong collaborations with institutions including ETH Zürich, University of Washington, and various industry partners.

Roberto Furfaroمشاهده پروفایل

استاد

• Guidance, Navigation and Control
• Machine Learning in Aerospace
• Space Situational Awareness
• +۷ مورد دیگر

Roberto Furfaro is a Professor in the Department of Systems and Industrial Engineering and the Department of Aerospace and Mechanical Engineering at the University of Arizona, College of Engineering. He serves as Deputy Director of the Space, Security, Safety & Sustainability Center (S4C) and is a key figure in space situational awareness and planetary exploration systems. His educational background includes a Laurea Degree (MS equivalent) in Aeronautical Engineering from the University of Rome 'La Sapienza' (1998) and a PhD in Aerospace Engineering from the University of Arizona (2004). His research spans guidance and control of planetary landers, machine learning applications in space systems, hypersonic vehicle G&C, and systems engineering for small body proximity operations. He leverages advanced AI, particularly reinforcement learning and deep learning, to solve complex aerospace challenges. The recent publications reflect a strong trend toward intelligent, autonomous systems in spaceflight, especially using deep reinforcement learning for planetary landing, guidance under uncertainty, and space-based object tracking. His work bridges control theory, astrodynamics, and artificial intelligence. 2021 Da Vinci Fellow, College of Engineering AIAA Associate Fellow (2022) AAS Fellow (2021) Asteroid 133474 Roberto Furfaro named in honor of OSIRIS-REx contributions Prof. Furfaro has served as PI or Co-PI on over $80M in research grants from NASA, AFRL, and DoD. He has advised numerous students and leads research teams in autonomous space systems and machine learning applications. He is the Target Follow-up Working Group lead for the NASA NEO Surveyor Mission and was Systems Engineering Lead for SPOC during OSIRIS-REx Phase B-D. He is actively involved in professional service as Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and technical member of the AIAA Astrodynamics Committee and AAS Space Surveillance Committee.

• Metabolic Diseases
• Diabetes
• Obesity
• +۵ مورد دیگر

Prof. Jürgen Machann serves as Group Leader of the Division "Metabolic Imaging" at the Institute for Diabetes Research and Metabolic Diseases (IDM), a joint institution of Helmholtz Zentrum München and University of Tübingen. Since joining Helmholtz Center Munich in 2012, he has established himself as a designated expert for MR examinations in national and international metabolic research studies including the German National Cohort (NAKO) and TULIP lifestyle intervention program. His academic trajectory features: Physics studies at University of Tübingen (1988-1995) Scientific work at Section on Experimental Radiology, University Hospital Tübingen (1995-2011) Doctoral thesis in human sciences, Medical Faculty, University of Tübingen (2011) Postdoctoral lecture qualification (Habilitation), Medical Faculty, University of Tübingen (2014) Machann's research pioneers non-invasive phenotyping of metabolic diseases through advanced MRI/MRS techniques. He developed quantitative assessment protocols for whole-body adipose tissue compartments (visceral, subcutaneous) and ectopic fat accumulation in liver/pancreas using specialized segmentation routines. His work integrates big data analysis with deep-learning based segmentation for epidemiological studies like KORA and GNC, revealing critical insights into insulin resistance pathogenesis and type 2 diabetes progression. Current research trends from his 2024-2025 publications demonstrate focused exploration of body composition subphenotypes, dietary impacts on liver fat and brain insulin action, and refinement of adipose tissue quantification methods. His group actively contributes to major research networks including German National Cohort, BeLOVE ("Berlin Longterm Observation of Vascular Events"), and German Center for Diabetes Research (DZD), advancing metabolic risk prediction through cutting-edge imaging analytics.

Simone D'Amicoمشاهده پروفایل

دانشیار

• Distributed Space Systems
• Formation Flying
• Spacecraft Guidance and Control
• +۳ مورد دیگر

Simone D'Amico is an Associate Professor in the Department of Aeronautics and Astronautics at Stanford University and holds a courtesy appointment in Geophysics. He is the Founding Director of the Space Rendezvous Laboratory (SLAB) and Director of the AA Undergraduate Program. His research focuses on distributed space systems, formation flying, and spacecraft autonomy, with contributions to missions like GRACE, TanDEM-X, and PROBA-3. He leads upcoming NASA/NSF-funded projects including STARLING, VISORS, and SWARM-EX. D'Amico has received numerous awards, including the NASA Group Achievement Award (2004) and the Leonardo 500 Award (2019). Education: B.S. and M.S. from Politecnico di Milano (2003), Ph.D. from Delft University of Technology (2010). Prior to Stanford, he spent 11 years at the German Aerospace Center (DLR) as a research scientist and team leader. Research Interests: Advanced astrodynamics, spacecraft Guidance, Navigation, and Control (GNC), autonomy, and distributed space systems. His work aims to enable miniature satellite swarms for remote sensing and space exploration. Awards: Includes AAS and AIAA Best Paper Awards (2019-2022), Terman Faculty Fellowship (2013-2016), and multiple DLR recognitions. Advising & Grants: Supervises doctoral and master’s students, advises NASA and startups, and leads SLAB’s hardware-in-the-loop testbeds for DSS development. Labs & Projects: SLAB collaborates internationally on missions like STARFOX and SWARM-EX, advancing technologies for asteroid characterization and exoplanet imaging.

Giovanni Fasanoمشاهده پروفایل

استاد

• Operations Research
• Numerical Analysis
• Computational Mathematics
• +۶ مورد دیگر

Giovanni Fasano is a Full Professor at the Department of Management, Venice School of Management, Ca' Foscari University of Venice. His academic journey includes a PhD in Operations Research from Sapienza University of Rome and extensive contributions to optimization theory, computational mathematics, and applications in finance and engineering. He holds dual qualifications in the Italian National Scientific Qualification (Sector 01/A5 and 01/A6). Education: PhD in Operations Research (2001), Sapienza University of Rome MSc in Electronic Engineering (1997), Sapienza University of Rome High School Diploma (1986), Liceo Scientifico B. Pascal, Rome Research Focus: His work spans optimization algorithms (e.g., conjugate gradient, Newton-Krylov), stochastic models for agent interactions, and applications in finance (cryptocurrency forecasting), ship design, and machine learning. He has pioneered methods for handling large-scale and nonconvex problems, including preconditioning techniques and hybrid metaheuristics (PSO). Grants & Projects: Key roles in projects like the €1M Interreg MIMOSA (maritime transport) and RITMARE (ship hydrodynamics). Funded by EU, MIUR, and industry partners (e.g., INSEAN, RINA). Awards: Charles Broyden Prize (2009), Best Publication Awards (2009, 2014), ANVUR FFABR Grant (2017). Over 100 peer-reviewed articles and 34 co-authors (9 international). Labs/Teams: Member of BLISS (Ca' Foscari), GNCS (INdAM), and Science of Complex Systems groups. Active in conferences (e.g., SIAM, EUROPT) and editorial roles (Mathematical Methods in Economics and Finance).

Remi Draiمشاهده پروفایل

استاد

• Guidance, Navigation, and Control (GNC)
• Aerospace Engineering
• Spacecraft Dynamics
• +۴ مورد دیگر

Remi Drai is Professor of Mathematics at Grove City College, Pennsylvania. His primary appointment resides within the Department of Mathematics, where he teaches and conducts research in applied mathematics with a strong emphasis on guidance, navigation, and control (GNC) systems for aerospace applications. Prof. Drai's research portfolio, as evidenced by more than two-dozen peer-reviewed publications between 1997 and 2014, centers on the mathematical foundations of spacecraft navigation and control. His interests span vision-based landing algorithms for lunar and planetary missions, robust multi-objective control synthesis via convex optimization, and autonomous guidance schemes for near-Earth asteroid rendezvous. A recurring theme is the fusion of inertial sensors with vision/GNSS data to achieve pinpoint landing accuracy under stringent mission constraints. Across his publications, Drai addresses both theoretical contributions—such as dissipative control theory and linear matrix inequality (LMI) methods—and practical validation through laboratory demonstrations and flight testing. This dual focus highlights a commitment to bridging rigorous mathematical analysis with real-world aerospace engineering challenges. Laboratory & Collaborations: While explicit laboratory names are not provided, the breadth of flight-test campaigns (e.g., precision landing GNC facility tests, ExoMars EDL demonstrator) indicates extensive collaboration with European space agencies and industry partners. Contact: Email: DraiR@gcc.edu Phone: 724-458-2105

Carol MARTINEZ LUNAمشاهده پروفایل

پژوهشگر

• Space Robotics
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Dr. Carol Martinez Luna is a Research Scientist and Deputy Head of the Space Robotics group (SpaceR) at the SnT Interdisciplinary Centre, University of Luxembourg. She holds a PhD in Robotics and Automation from Universidad Politécnica de Madrid (2013) and previously served as an Assistant Professor at Pontificia Universidad Javeriana, Colombia. Her research spans Space Robotics , Computer Vision , and Machine Learning , with current focus areas including: Multi-purpose manipulation for planetary/orbital robots Perception systems for autonomous space operations Domain adaptation to bridge simulation-to-reality gaps On-ground testing of orbital technologies Recent publications (2022-2025) predominantly address space debris removal , autonomous grasping , and robotic perception , with heavy emphasis on machine learning techniques and high-fidelity simulation validation. Notable trends include generative models for manipulation and adaptive control under uncertainty. She actively advises 7 PhD students and 9 Master's candidates on topics ranging from space manipulation to vision-based safety systems. Her lab develops experimental platforms for orbital scenario emulation and collaborates on ESA-funded debris removal initiatives.

Ahmad Bani Younesمشاهده پروفایل

دانشیار

• Spacecraft Guidance, Navigation and Control (GNC)
• Orbital Mechanics
• Space Robotics
• +۳ مورد دیگر

Dr. Ahmad Bani Younes serves as an Associate Professor in the Department of Aerospace Engineering within San Diego State University's College of Engineering, where he directs the Spacecraft Platform for Astronautics & Celestial Emulation (SPACE) Lab and advises the Rocket Club. His academic leadership extends to developing space-related programs and CubeSat projects at SDSU. His educational background includes a PhD in Aerospace Engineering from Texas A&M University (2013), an MSc in Aerospace Engineering from the University of Dayton (2009), and a BSc in Mechanical Engineering from Jordan University of Science & Technology (2003). Dr. Bani Younes' research focuses on Spacecraft Guidance, Navigation and Control (GNC) , Orbital Mechanics , and Space Robotics . His work encompasses high-fidelity gravity modeling for Earth anomalies, efficient satellite trajectory propagation, optimal control for spacecraft attitude tracking, and algorithmic differentiation for generating high-order derivatives. He also pioneers robotic sensing and control research in proximity operations, human-robot interaction, stereo vision, swarm robotics, and autonomous aerial vehicles through the SPACE Lab. Analysis of his 15 most recent publications (2010-2021) reveals a strong evolution from foundational orbital mechanics (Lambert's problem solutions, state transition tensors) toward cutting-edge applications in space robotics and autonomous systems. Recent works increasingly integrate machine learning (e.g., deep learning for aerial refueling) with traditional control theory, while maintaining rigorous computational approaches like Chebyshev-Picard iteration and dual-quaternion algebra. His distinguished awards include: Modeling and Simulation of Laser Communication Terminal of Satellites, Space Micro Inc., 2021 NASA JPL R&TD Innovative Spontaneous Concept Proposal, 2019 John V. Breakwell award (co-authored with JDP student), 2019 Khalifa University Competitive Internal Research Award (CIRA), 2019 Texas A&M Engineering Experiment Station (TEES) Award, 2018 Khalifa University Employee Award for Outstanding Service, 2016 ADEC Award for Research Excellence AARE, ADEC DRONES: Build and Fly chief expert award, WorldSkills, 2017 DRONES: Build and Fly chief expert award, EmiratesSkills, 2015 Recognition Certificate for best advising Matlab Club, Khalifa University, 2014 Best Paper Award, 37th AAS GNC conference, 2014 SIAM Award, Automatic Differentiation, 2012 Graduate Teaching Academy (GTA) Award, Texas A&M University, 2012 Graduate Teaching Academy (GTA) Senior Fellowship, Texas A&M University, 2012 Graduate Teaching Academy (GTA) Fellowship, Texas A&M University, 2011 Award of Academic Excellence, Jordan University of Science and Technology, 2003 As an academic advisor, he mentors the Rocket Club and develops the CubeSat project. His research is funded by competitive grants including NASA JPL R&TD proposals and Space Micro Inc. contracts, supporting hardware development for laser communication terminals and spacecraft GNC systems. These grants enable experimental validation in the SPACE Lab's 6DOF environment. The SPACE Lab serves as a critical operational testbed for space systems, conducting hardware-in-the-loop experiments in robotic sensing, proximity operations, and autonomous aerial vehicle control. Current initiatives include swarm robotics for satellite constellations and stereo vision systems for in-orbit servicing, positioning SDSU at the forefront of space technology research.

• Aerospace Control
• Guidance, Navigation and Control (GNC)
• Unmanned Aircraft Systems (UAV)
• +۳ مورد دیگر

Nadjim Horri is a Lecturer in aerospace control and Course Director of the MSc Aerospace Engineering at the University of Leicester. He is affiliated with the School of Engineering, and a member of the Aerospace Research Group and the Green Energy and Transportation Research Group. His research focuses on safe, resilient GNC systems for manned/unmanned aircraft, satellite AOCS, and space mission design. He collaborates with Space Park Leicester on satellite control systems. Education: PhD from the University of Surrey (attitude control of underactuated spacecraft), followed by roles as a Research Fellow at Surrey Space Centre and Assistant Professor at Coventry University. His work includes EU projects like ASTRONET and AAReST, and Innovate UK projects on CAV parking. Research interests include UAV path planning, fault detection, secure estimation against cyberattacks, wind disturbance rejection, and AI-enhanced control. He teaches modules on real-time control, avionics, and spacecraft dynamics. His expertise spans flight simulation, HIL implementations, and multimode GNC systems. Labs/Teams: Active contributor to Surrey Space Centre projects, aerospace research group collaborations, and interdisciplinary green energy initiatives.