جست‌وجوی استاد و پژوهشگر

• Mechanical Engineering
• Manufacturing Engineering
• Materials Processing
• +۷ مورد دیگر

Tobias Andersson is a Senior Lecturer in Mechanical Engineering at the University of Skövde , affiliated with the School of Engineering Science and Department of Engineering . His work focuses on advanced manufacturing simulations and optimizations. Research Projects: ShiftLabs (Digital Transformation), QWELD (Laser/Ultrasonic Welding), Virtual Engineering initiatives Technical Expertise: Finite Element Analysis, Multi-physics Modeling, Laser Welding, Adhesive Layer Mechanics His recent publications highlight trends in AI-driven manufacturing, including ANN predictive models for machining deviations and deep learning applications in welding quality assessment . He also investigates thermal stress in cutting processes and fracture mechanics in aerospace alloys. Collaborations span institutions in Sweden and Argentina, with frequent co-authorship on topics like hairpin welding optimization and multi-objective drilling simulations. Current initiatives include ReactEU Energy Storage & Power Electronics and ShiftLabs digital transformation services.

• Human-Robot Interaction
• Digital Human Modeling (DHM)
• Cognitive Ergonomics
• +۴ مورد دیگر

Ari Kolbeinsson is a Senior Lecturer in Product Design Engineering at the School of Engineering Science , University of Skövde . His research focuses on human-robot collaboration , digital human modeling (DHM) , cognitive ergonomics , and user experience (UX) design in industrial contexts. Department: Department of Engineering Science Email: ari.kolbeinsson@his.se Research Interests span the integration of human factors into manufacturing systems , with emphasis on embodied cognition , context-aware interruptions , and digital assembly instructions . He explores how cognitive and physical ergonomics can be harmonized through DHM tools and intuitive interface design . Publications highlight trends in industrial digitization , collaborative robotics , and user-centered manufacturing . Key subfields include human-machine interaction (HMI) , gamification for training , and functional tones in action perception . Projects like DIGITALa arbetsInStruktioner för kognitivt arbete (2022–2024) and Virtual Engineering TACO (2019–2021) address digital transformation and demographic challenges in manufacturing. Earlier work (2009–2013) focused on collision-free path planning in IMMA . Education and teaching roles include coordinating bachelor's and master's courses in Integrated Product Development , with a focus on user experience processes and digital training .

Candace Jensمشاهده پروفایل

استادیار

• Data Analytics in Finance
• Firm Investment Strategies
• Economic Environments
• +۳ مورد دیگر

Candace Jens is an Assistant Professor of Finance at the Whitman School of Management , Syracuse University. Her work bridges finance and data analytics, emphasizing the transformative power of data in business decision-making. She previously taught at Tulane University and has been published in prestigious journals like the Journal of Financial Economics and the Journal of Financial and Quantitative Analysis . Education: Undergraduate from Niagara University, Master’s in Business Analytics, Ph.D. from the University of Rochester. Jens focuses on: Applications of data analytics in financial contexts (e.g., investment optimization, mortgage prediction). Interdisciplinary overlaps with politics, law, and economics. Impact of firm investments on communities and employees. She actively promotes data literacy as a portable skill for diverse career paths and contributes to Whitman’s expansion in data analytics education.

Mashrura Musharrafمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Marine Technology
• +۶ مورد دیگر

Mashrura Musharraf is an Assistant Professor in the Department of Energy and Mechanical Engineering at Aalto University, specializing in Marine Technology. Her research focuses on integrating data mining, machine learning, and AI into human-centered systems to enhance maritime safety, particularly for autonomous and icebreaker-assisted vessels. Her work addresses the complexities of decision-making in harsh environments, emphasizing the interpretability of AI algorithms for autonomous ships and the role of human factors in winter navigation. Recent projects include predicting icebreaker assistance needs, analyzing crew behavior, and optimizing maritime operations under environmental regulations. Her publications span topics like ensemble ML models, explainable AI for autonomous vessels, and data-driven strategies for ice-covered waters. Collaborations with researchers such as Cong Liu and Pentti Kujala highlight her interdisciplinary approach to Arctic and maritime challenges. Musharraf contributes to research groups focused on Marine and Arctic Technology, aiming to bridge gaps between automation and human reliability in offshore emergencies through simulator data and Bayesian networks.

Karolos Grigoriadisمشاهده پروفایل

استاد

• Robust Control
• Optimal Control
• Systems Optimization
• +۹ مورد دیگر

Karolos Grigoriadis is the Moores Professor of Mechanical Engineering at the University of Houston, where he also serves as Department Chair of Mechanical and Aerospace Engineering and Director of the Aerospace Engineering Program. His research spans robust control, parametric uncertainty analysis, subsea engineering, and biomedical control systems, with applications in aerospace, petroleum engineering, and medical device development. Systems Optimization and Uncertainty Analysis Robust and Fault Tolerant Control Subsea Systems Diagnostics and Optimization Biomedical Modeling and Control His recent publications focus on linear parameter varying (LPV) systems, multiphase flow modeling, and secure control strategies for industrial and aerospace applications. He has developed specialized tools for automated blood pressure regulation and subsea pipeline integrity analysis. Grigoriadis' work integrates theoretical control systems research with practical applications in energy systems, robotics, and biomedical engineering. He leads the University of Houston's Subsea Engineering Academic Advisor office and collaborates on advanced modeling projects across multiple domains.

• Computer Science
• Distributed Systems
• Peer-to-Peer Networks
• +۲ مورد دیگر

Vittorio SCARANO is a Full Professor at the University of Salerno, affiliated with the Department of Computer Science. His office is located at Fisciano Campus, Building F, Fourth Floor, Room 001. Reception hours are held on Thursdays (9:00–11:00) and Fridays (11:00–12:00) via Microsoft Teams ( vitsca@unisa.it ). Additional appointments can be scheduled by email. His research focuses on Computer Science , with emphasis on: Distributed Systems and P2P Networks Collaborative Learning Environments Algorithm Design and Optimization Mobile and Adaptive Learning Technologies His publications demonstrate consistent work in networking, distributed computing, and educational tools, with recent expansions into mobile learning infrastructure. No scientific awards, grants, or student advising relationships are documented in the sources. He participates in international academic exchanges through Erasmus+ agreements for study and traineeship, though specific lab/team details are unavailable.

Stefan Horst Sommerمشاهده پروفایل

استاد

• Machine Learning
• Riemannian Geometry
• Stochastic Processes
• +۳ مورد دیگر

Stefan Horst Sommer is a Professor at the Department of Computer Science (DIKU), University of Copenhagen . He leads the Pioneer AI (P1AI) section, serves as Head of Studies for Machine Learning and Data Science, and co-founded the Center for Computational Evolutionary Morphometry (CCEM) with Rasmus Nielsen. His work bridges stochastic processes , geometric statistics , and machine learning with applications in computational anatomy and diffusion modeling . Key Roles : Head of Pioneer AI, Head of MLDS Studies, CCEM PI Labs : Applied Geometry Lab, CCEM Research focuses on Riemannian geometry , anisotropic diffusion , and stochastic shape analysis . Current projects include geometric machine learning for aerodynamic modeling and probabilistic image registration with applications in medical imaging and evolutionary biology . His 96+ publications emphasize manifold-valued processes and geometric deep learning . Collaborations span computational anatomy , stochastic mechanics , and AI-driven scientific computing . He co-organizes international workshops on geometric statistics and maintains active GitHub repositories for open-source research tools.

• Modular and Offsite Construction
• Building Information Modelling (BIM)
• Lean Manufacturing
• +۵ مورد دیگر

Dr. Mohamed Al-Hussein is a Professor and NSERC Industrial Research Chair in the Industrialization of Building Construction at the University of Alberta’s Department of Civil and Environmental Engineering. His work focuses on advancing modular and offsite construction technologies through automation, lean principles, and Building Information Modelling (BIM). PhD, Construction Engineering & Management, Concordia University (1999) MASc, Construction Engineering and Management, Concordia University (1995) MSc, Civil Engineering, University of Architecture & Civil Engineering, Bulgaria (1988) BSc, Civil Engineering, University of Architecture & Civil Engineering, Bulgaria (1983) Dr. Al-Hussein’s research spans five key domains: Modular Construction: Pioneering high-efficiency offsite building systems, including rapid assembly of student dorms and mid-rise residential buildings. BIM & Digitalization: Developing 3D/4D modeling frameworks, automated design systems, and digital twin applications for construction optimization. Environmental Sustainability: Quantifying CO2 emissions, exploring nano energy storage, and advancing solar PV integration in residential construction. Urban Planning: Specializing in age-restricted community design, municipal infrastructure maintenance, and housing affordability analysis related to paving standards. Construction Safety: Applying ergonomic risk assessment tools and virtual reality to enhance worker safety and reduce construction-related hazards. His 400+ peer-reviewed publications reflect cutting-edge applications of AI, deep learning, and simulation across construction processes. Recent work explores metaverse integration, blockchain collaboration tools, and advanced crane operation optimization using reinforcement learning. As Editor-in-Chief of the International Journal of Industrialized Construction , Dr. Al-Hussein remains a global authority in this field. He has developed industry-transforming technologies like the Quikmod-2 modular lift frame and PCL lift frame project , with real-world implementations ranging from Shell Scotford complex equipment replacement to CBC News and Forbes featured projects.

• Additive Manufacturing
• Multi-Axis Manufacturing
• Prosthetics Design
• +۳ مورد دیگر

Nathaniel Kaill is a Researcher affiliated with the School of Design and Creative Arts. His work focuses on additive manufacturing, particularly multi-axis systems and tool path design for complex structures. He holds a PhD in Multi-Axis Additive Manufacturing, an MSc in Advanced Manufacturing Technology and Systems, and a BEng in Aerospace Systems Engineering. His research aims to enhance material integrity and mechanical performance through rotational axis integration in 3D printing processes. Key research interests include improving layered material bonding, stress analysis via FEA-driven design, and applications in low-limb prosthetics. He has contributed to iterative design projects to optimize prosthetic components using additive manufacturing techniques. His expertise bridges mechanical engineering, biomedical engineering, and materials science. No academic awards or grants are explicitly mentioned. Advising roles or student mentorship details are not provided in the text. Current involvement in research projects related to the circular economy of small medical devices is noted.

H B Acharyaمشاهده پروفایل

استادیار

• Network Security
• Cybersecurity
• Distributed Systems
• +۶ مورد دیگر

H B Acharya is an Assistant Professor in the Department of Computer Science at Oklahoma State University, specializing in network security, programmable networks, and cybersecurity. He holds a PhD from The University of Texas at Austin and a B.Tech from IIT Kharagpur. His research focuses on data-plane security (e.g., DeeP4R for DPI in P4), decoy routing systems (SiegeBreaker), and internet interference analysis. He has received grants including an NSF RAPID award and best paper recognition at SecureComm 2018. His teaching includes courses on network security, distributed systems, and computer systems design. Research interests span network protocols, distributed systems, and emerging technologies like ML/quantum computing's impact on networks. Notable projects include analyzing the Russia-Ukraine war's cyberspace effects and developing tools for measuring network capacity and censorship resilience.

David Broidoمشاهده پروفایل

استاد

• Theoretical Condensed Matter Physics
• Materials Property Prediction
• Phonon Transport
• +۳ مورد دیگر

David Broido is a Professor of Physics at Boston College, specializing in theoretical condensed matter physics. His research focuses on predicting materials properties using first-principles computational methods, with an emphasis on phonon and electron transport. Key areas include identifying materials with ultrahigh thermal conductivity, coupled electron-phonon transport, and spin-lattice coupling in magnetic systems. His work spans semiconductor and insulator thermal properties, topological materials, and thermoelectric optimization. Education: B.S. (University of California, Santa Barbara), M.S. and Ph.D. (University of California, San Diego). Research Group: Broido Research Group . Research Interests: Phonon and electron transport in novel materials Prediction of ultrahigh thermal conductivity materials Electron-phonon coupling effects in semiconductors Magnetic materials and spin-lattice interactions Thermoelectric materials optimization Publications: Over 100 peer-reviewed articles, including landmark studies on boron arsenide's thermal conductivity, Kitaev spin liquids, and coupled transport phenomena. Recent work explores phonon scattering mechanisms, topological semimetals, and temperature-dependent material properties. Labs/Teams: Active leader of a research group focusing on computational materials science. Collaborates with experimentalists to validate theoretical predictions on novel materials.

Davide Guzzettiمشاهده پروفایل

دانشیار

• Astrodynamics
• Space Mission Design
• Machine Learning
• +۵ مورد دیگر

Davide Guzzetti is an Associate Professor in the Department of Aerospace Engineering at Auburn University , where he combines expertise in astrodynamics with cutting-edge technologies like machine learning and immersive computing. Ph.D. in Aeronautics and Astronautics, Purdue University M.S. in Space Engineering, Politecnico di Milano & Torino B.S. in Aerospace Engineering, Politecnico di Milano His research focuses on space mission design and astrodynamics , particularly in cislunar environments and highly elliptical orbits. He leads innovative projects applying machine learning to satellite systems, virtual reality to trajectory design, and origami-inspired engineering to spacecraft deployables. Recent publications reflect trends in orbital mechanics , autonomous space systems , and human-machine collaboration for space mission planning. His work spans technical analysis of self-folding polymers, game-theoretic approaches to satellite constellation competition, and immersive visualization tools for multi-body dynamics. NASA Early Career Faculty Award (2025) Ginn Faculty Achievement Fellow (2025) Guzzetti's research has secured multiple grants including a NASA EPSCoR award for studying microgravity effects on self-folding polymer sheets and a NASA Innovative Advanced Concepts (NIAC) award for space-based self-assembling antenna arrays. He also contributes to educational innovations through Massive Open Online Courses (MOOCs) and elementary education outreach programs in spacecraft dynamics. His laboratory develops interactive solutions for astrodynamics applications, integrating immersive computing with intelligent systems to enhance space mission design processes. Current projects include studying resilience of deployable space structures and optimizing autonomous path-planning for asteroid proximity operations.

Yazan Alqudahمشاهده پروفایل

استاد

• Optical Wireless Communication
• Mobile Networks
• Embedded Systems
• +۳ مورد دیگر

Dr. Yazan Alqudah is a Professor in the Department of Electrical and Computer Engineering at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He holds a Ph.D. in Electrical Engineering from Pennsylvania State University (2003) and has held roles at Intel Corporation and multiple universities, including Princess Sumaya University for Technology and Western Carolina University. His research focuses on optical wireless communication, mobile networks, and embedded systems, with contributions to machine learning applications in transportation and healthcare. Education: Ph.D., Electrical Engineering, Pennsylvania State University, 2003 M.S., Electrical Engineering, Pennsylvania State University, 1997 B.S., Electrical Engineering and Computer Science, University of Jordan, 1993 Research Interests: His work spans broadband optical wireless communication, next-generation mobile networks, embedded systems design, and machine learning applications in healthcare and transportation. Notable areas include autonomous vehicle sensing, wearable health monitoring, and fault-tolerant automotive systems. Publications Trends: Recent articles emphasize machine learning for driving behavior analysis, sensor fusion in autonomous systems, and optimization of wireless communication protocols. Earlier work includes contributions to WiMAX technology, optical wireless MIMO systems, and energy storage solutions for solar PV arrays. Awards: Intel Recognition Awards (2005, 2007) Best Researcher Award at PSUT (2014) Labs & Projects: Developed hands-on labs for broadband wireless technology and embedded systems education. Current projects include a mobile application for breathing abnormality detection and tools for facial thermography-based lie detection.

Muhammad Ali Gulzarمشاهده پروفایل

استادیار

• Software Engineering
• Automated Debugging
• Testing
• +۶ مورد دیگر

Muhammad Ali Gulzar is an Assistant Professor in the Department of Computer Science at Virginia Tech and an Amazon Scholar at Amazon Web Services. He holds a Ph.D. (2020) and B.S. (2014) in Computer Science from UCLA and Lahore University of Management Sciences, respectively. His research focuses on improving developer productivity through automated debugging and testing for emerging software domains, including data-intensive systems, machine learning applications, and computational notebooks. Education Ph.D., Computer Science, University of California, Los Angeles (2020) B.S., Computer Science, Lahore University of Management Sciences, Pakistan (2014) Research Interests Dr. Gulzar redesigns software productivity tools for emerging applications across three areas: (1) automated tracking-code localization in web applications, (2) re-engineering testing/debugging for data-intensive systems (e.g., Apache Spark), and (3) advancing testing/debugging in federated learning. His work includes projects like TraceFL for federated learning interpretability, NoT.JS for JavaScript tracking blocking, and MeanCache for LLM caching. Recent Contributions Recent papers address accessibility issues in ad-driven web pages (ICSE 2025), interpretability in federated learning (ICSE 2025), and notebook executability (MSR 2025). His team received the ACM CCS 2024 Distinguished Artifact Award for tracking JavaScript function analysis and a 2024-25 Amazon-VT Award for semantic caching research. Grants & Projects CCI-funded project on web ad transparency/accessibility engineering Amazon Scholar collaboration on productivity tools Student Contributions Recent advisees include Abdul Haddi Amjad (ad accessibility), Waris Gill (Federated Learning), and Tien Nguyen (notebook analysis). Students have contributed to industry-relevant tools like GitMeter for evidence-based hiring and DeSQL for SQL debugging.

Andrea L'Afflittoمشاهده پروفایل

دانشیار

• Autonomous Robots
• Control Theory
• Unmanned Systems
• +۳ مورد دیگر

Dr. Andrea L'Afflitto is an Associate Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech. His primary research focuses on autonomous robots, unmanned systems, control theory, and lightweight robotics. He holds a Ph.D. in Aerospace Engineering from Georgia Tech and has held roles including Assistant Professor at the University of Oklahoma (2015–2019) and Summer Faculty Fellow at the Army Research Lab (since 2017). His work spans funded projects with ARL, DARPA, NSF, and ONR, emphasizing applications like autonomous aerial support for ground troops. Education B.S. & M.S. in Aerospace Engineering, University of Napoli 'Federico II' (2004, 2006) M.S. in Mathematics, Virginia Tech (2011) Ph.D. in Aerospace Engineering, Georgia Tech (2015) His research interests include robust adaptive control, model reference adaptive control (MRAC), barrier Lyapunov functions, and nonlinear systems. He has authored 1 monograph, 2 book chapters, and over 40 peer-reviewed publications. Notable awards include the 2018 DARPA Young Faculty Award and the Domenica Rea D'Onofrio Scholarship (2011–2015). Grants & Collaborations His projects are funded by Army Research Lab (ARL), DARPA, NSF, and ONR. He has developed an open-source framework for nonlinear control of UAVs and contributed to terrain-informed motion planning for tactical vehicles. His work integrates cutting-edge control theory with practical applications in autonomous systems. Labs & Teams Dr. L'Afflitto leads research in autonomous systems at Virginia Tech, focusing on UAV control and adaptive algorithms. He collaborates with Army Research Lab on tactical autonomous systems and has ties to institutions like FermiLab and Thales Alenia Space through prior industry experience.