جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Deep Learning
• Neural Networks
• +۳ مورد دیگر

Enrique Romero Merino is an Associate Professor at the Department of Computer Science within the Barcelona School of Informatics (FIB) at the Polytechnic University of Catalonia (UPC). He is a key member of the IDEAI-UPC (Intelligent Data Science and Artificial Intelligence Research Group) and the SOCO (Soft Computing) research group. His expertise spans machine learning, deep learning, and neural networks, with interdisciplinary applications in medical imaging, computational architecture, and data science. His research focuses on developing advanced machine learning methodologies, including restricted Boltzmann machines, radiomics for medical diagnostics, and generative design in architecture. He actively collaborates on projects like diabetic retinopathy prediction using OCTA imaging, automated social housing layout generation, and glioblastoma treatment response analysis. Romero Merino has contributed to 147 academic activities, including journal publications, competitive R&D projects, and conference presentations. His recent work emphasizes the intersection of AI with healthcare and sustainable architectural design, leveraging techniques like radiomics and deep learning for real-world problem-solving.

• Computational Geometry
• Program Testing
• Software Reliability Estimation

Simeon Ntafos is a Professor in the Department of Computer Science at the University of Texas at Dallas, serving as Associate Dean for Undergraduate Education and Director of the Office of Student Services. His research focuses on computational geometry, program testing, and software reliability estimation. Ph.D., Northwestern University (1979) M.S. in Electrical Engineering, Northwestern University (1977) B.S. in Electrical Engineering, Wilkes College (1974) His computational geometry work includes terrain guarding, watchman routes, and polygon partitioning, while his software engineering research compares testing strategies like random and partition testing. Publications span from 1988 to 2005, showing sustained contributions to geometric algorithms and software reliability. As an academic leader, he has organized conferences including the 21st Symposium on Computational Geometry and contributed to journals such as IEEE Transactions on Software Engineering and Algorithmica. His methodological innovations include greedy algorithms for VLSI routing and visibility-based optimization techniques.

Phillip S. Colesمشاهده پروفایل

دانشیار

• Supply Chain Management
• Economics
• Business
• +۳ مورد دیگر

Phillip S. Coles is a Teaching Associate Professor at Lehigh University in the Decision and Technology Analytics (DATA) department. With over 30 years of industry experience, he specializes in Supply Chain Management , Economics , and Business . Education : Bachelor's degree in Agricultural Science from Pennsylvania State University M.B.A. in Supply Chain Management from Lehigh University M.S. in Applied Economics and Management from Cornell University Lean and Continuous Improvement training from The Kaizen Institute, Manufacturer's Resource Center, and Toyota Supplier Support Center Research Focus : Supply chain economics Manufacturing systems optimization Trade policy and globalization Behavioral aspects of resource allocation Media Contributions : Regular columnist for Discourse Magazine Freelance contributor to The Wall Street Journal , The Hill , Pittsburgh Post-Gazette , and Washington Examiner Expert commentary on inflation dynamics, labor policy, and supply chain disruptions Industry Experience : Vice President of Strategic Management at a multi-million dollar produce company Consulting firm focused on plant layout optimization and assembly line balancing

Ok-Youn Yuمشاهده پروفایل

استاد

• UAV Technology in Construction
• Sustainable Energy Systems
• Infrastructure Sustainability
• +۱۳ مورد دیگر

Dr. Ok-Youn Yu is a Professor and current Department Chair of the Department of Sustainable Technology and the Built Environment at Appalachian State University, where he has been a faculty member since 2010. He holds a Ph.D. in Civil Engineering from Texas A&M University and brings both academic excellence and five years of industry experience as a bridge and tunnel engineer to his role. Ph.D., Civil Engineering, Texas A&M University, 2009 M.S., Construction Management, Texas A&M University, 2005 B.S., Civil Engineering, Konkuk University, Seoul, Korea, 1999 Dr. Yu’s research focuses on advancing sustainable technologies in civil infrastructure, particularly through the integration of UAVs (drones) in construction surveying, erosion monitoring, and building energy analysis. His work also spans sustainable energy systems such as biomass heating and landfill gas monitoring, alongside infrastructure sustainability, remote health monitoring, and natural hazard early warning systems. He applies advanced decision-making tools like Bayesian networks, influence diagrams, and life cycle assessment to project risk management and optimal modeling. His recent publications reflect a strong trend toward interdisciplinary innovation, combining remote sensing, data analytics, and sustainable design. These works span applications in construction accuracy, energy-efficient buildings, and resilient infrastructure. The integration of Building Information Modeling (BIM) and 4D CAD into energy performance management is another key theme. Dr. Yu has successfully secured nearly $2 million in research funding from prestigious agencies including the National Science Foundation (NSF), Environmental Protection Agency (EPA), U.S. Department of Agriculture (USDA), North Carolina Department of Transportation (NCDOT), and the North Carolina Department of Agriculture and Consumer Services. He has mentored over 30 graduate students and numerous undergraduates, fostering the next generation of sustainable technology leaders. He leads multiple research initiatives including UAV-based monitoring, sustainable energy systems, and web-based early warning platforms for infrastructure. His lab supports hands-on student research in drone technology, energy modeling, and risk analysis.

Seokhyun Chungمشاهده پروفایل

استادیار

• Internet of Things (IoT)
• Data-Driven Analytics
• Federated Learning
• +۴ مورد دیگر

Seokhyun Chung is an Assistant Professor at the University of Virginia, located in Lab 257 of Olsson Hall. His research focuses on IoT-enabled systems, leveraging data-driven methods such as federated learning, multi-task learning, and Bayesian probabilistic modeling to address challenges in statistical heterogeneity, scalability, and personalization in connected systems. Applications span smart healthcare and manufacturing systems, emphasizing reliability and efficiency. Research Interests: Chung's work integrates IoT, machine learning, and systems engineering to develop collaborative analytics frameworks. He explores federated learning architectures for distributed data fusion, probabilistic modeling for uncertainty-aware predictions, and optimization techniques for resource allocation in edge computing environments. His healthcare focus includes gait analysis and load estimation for wearable devices, while manufacturing applications involve job scheduling and additive manufacturing quality control. Key Contributions: Recent work highlights include federated multi-output Gaussian processes for heterogeneous systems, real-time adaptation of time-series predictions, and fairness-aware machine learning for load carriage tasks. His interdisciplinary projects address both technical and operational challenges, such as emergency department layout optimization and toxic gas monitoring networks. Labs & Infrastructure: Chung's research is conducted in Olsson Hall's advanced labs, leveraging IoT sensor networks, edge computing setups, and collaborative simulation environments to prototype innovative smart systems solutions.

• Academic Writing
• Written Communication
• Oral Communication
• +۶ مورد دیگر

Leen Pollefliet is an academic communication specialist at Ghent University's Faculty of Engineering and Architecture , specifically within the Department of Information Technology . With a 1985 Master of Languages (magna cum laude) from Ghent University, she has been teaching engineering students since 1988, developing a comprehensive communication learning pathway for bachelor's to master's level curricula. Specializes in academic writing and oral communication Authored 8+ educational handbooks since 2009 Focus on practical skills: thesis writing, presentations, job applications Created QR-code-based interactive learning tools for digital teaching Her research focuses on professional communication challenges in engineering education, particularly: Structural integrity in technical documents Modern APA referencing practices Effective academic poster design Business presentation techniques Writing process optimization Language education for STEM students Key publication trends show sustained focus on engineering communication since 2009, with 2024 conference paper "Connecterend presenteren" emphasizing audience engagement strategies. Her 2022 book "Scoring with Your Thesis" integrates digital learning materials through QR codes. Notable contributions include: 2024 Conference Paper on Presentation Techniques 2022 Thesis Writing Handbook 2016 8th Edition Communication Guide

• Human-Computer Interaction (HCI)
• Computer Vision
• Deep Learning
• +۶ مورد دیگر

Yue Jiang is an incoming Assistant Professor at the University of Utah (Fall 2025) and is currently finishing her Ph.D. at Aalto University and the Finnish Center for Artificial Intelligence (FCAI). Her research focuses on human-centered technologies in HCI, computer vision, and deep learning, particularly in computational user interface understanding, eye tracking, and adaptive GUI layouts. She has held visiting roles at Carnegie Mellon University (CMU) and collaborated with institutions in Canada and the UK. She serves on program committees for CHI, VL/HCC, and IUI, and has organized computational UI workshops at CHI conferences. Education: Ph.D. in Intelligent Systems (Aalto University & FCAI, 2025) Visiting Ph.D. Student (CMU, 2024) M.Sc. in Computer Science (University of Maryland, 2020) B.Sc. in Computer Science (University of Toronto, 2018) Research Interests: Yue explores computational representations of UIs, human behavior modeling via eye tracking and motion capture, and adaptive interfaces. Her work bridges HCI, computer vision, and machine learning to enhance human capabilities through AI-driven systems. Awards: Meta Research PhD Fellowship (2023–2025) Heidelberg Laureate Forum Young Researcher (2024) Google Europe Students with Disabilities Scholarship (2022) Advising & Grants: Yue mentors students in areas like multimodal generative AI and seeks researchers for her group. She has received grants from FCAI, Adobe Research, and the National Science Foundation. Labs & Collaborations: Active in the Computational Behavior Lab (Aalto) and BIG Lab (CMU), she collaborates on projects like OR-Constraints for adaptive GUIs and graph-based UI modeling.

Marius Hadryمشاهده پروفایل

پژوهشگر

• Self-aware Computing Systems
• Self-adaptive Systems
• Internet of Things (IoT)
• +۶ مورد دیگر

Marius Hadry is a doctoral researcher at the Chair of Software Engineering (Computer Science II) at the University of Würzburg, under the supervision of Prof. Samuel Kounev. He is affiliated with the Department of Computer Science within the Faculty of Mathematics and Computer Science. His research focuses on Self-aware Computing Systems , Sel-adaptive Systems , IoT and Cyber-physical Systems , Industry 4.0 , Platooning , and Intelligent Transportation Systems . Marius holds a Master's (2021) and Bachelor's (2019) in Computer Science from the University of Würzburg. Education: Master of Computer Science (2019-2021), Bachelor of Computer Science (2016-2019), both at the University of Würzburg. His work emphasizes practical applications of adaptive systems in transportation and logistics. Recent research explores traffic forecasting models, failure prediction in HDDs, and performance analysis of microservices. Marius actively contributes to international conferences like MASCOTS, SEAMS, UCC, and ICPE. Teaching activities include supervising Bachelor/Master theses, coordinating software architecture lectures, and organizing seminars on software engineering. He has also taught operating systems and contributes to academic initiatives like the Secure Software Systems Group.

Jean Heemskerkمشاهده پروفایل

استاد

• Building Construction
• Architectural Design
• Technical Construction
• +۵ مورد دیگر

Prof. Jean Heemskerk (Frankfurt University of Applied Sciences, Faculty of Architecture, Civil Engineering and Geomatics) serves as Dean of Department 1 since 2022. His work focuses on building construction, architectural design, and technical construction while bridging theory with practice in urban development projects. He has established a reputation for integrating sustainable concepts and material innovation into architectural education. Bachelor of Architecture, TU Karlsruhe (1989) Diploma, TU Darmstadt (1996) Co-founder of motorplan Frankfurt (1996) His research interests center around technical construction , urban design , and renewable energy integration through projects like wind energy architectural potential studies and early childhood MINT education initiatives using play objects. He emphasizes material experimentation (particularly concrete) and spatial problem-solving in complex urban contexts. Students under his supervision have received numerous awards including: Master students: 1st prize in Green Campus Award (2016), Dachwelten competition (2015) Bachelor students: multiple awards from Fachvereinigung Deutscher Betonfertigteilbau e.V. and Heidelbergcement AG His recent work includes the Z1 Bahnstadt masterplan development (2022) and Planetarium design for Senckenberg Museum expansion.

• Algorithms
• Theoretical Computer Science
• Graph Layout Problems
• +۸ مورد دیگر

Jordi Petit Silvestre is a professor in the Department of Computer Sciences at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is a member of the ALBCOM research group, focusing on algorithms, bioinformatics, complexity, and formal methods. His work bridges theoretical computer science with practical applications in algorithm engineering, VLSI design, and computer science education. His research interests include algorithms , graph layout problems , parallel computing , data structures , and computer science education . He has made significant contributions to the design and analysis of efficient algorithms, particularly in graph layout optimization and cache-conscious data structures. His work extends to electronic design automation, with publications on macro placement, routing, and physical design for integrated circuits. The recent publications highlight a dual focus: (1) algorithmic and physical design for VLSI, involving macro placement, routing, and system-level optimization; and (2) innovations in computer science education, particularly through the Jutge.org platform, continuous assessment, MOOCs, and feedback mechanisms in online judges. This reflects a career deeply engaged in both theoretical research and educational technology. Jordi Petit has participated in numerous competitive and non-competitive R&D+i projects, often in collaboration with other leading researchers at UPC. He has contributed to educational innovation projects aimed at transforming programming education and curriculum design in computer science degrees. He is actively involved in the development and deployment of Jutge.org , an educational programming judge that supports automated assessment and learning in programming courses. His work in this area includes improving feedback, integrating formal verification, and analyzing course evolution through metrics like pass rates and workload.

Kepa Iturraldeمشاهده پروفایل

استادیار

• Construction Automation
• Digital Transformation in Architecture
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Kepa Iturralde is a Senior Researcher and Junior Professor (Assistant Professor) at the Institute for Construction Management (IBL) of the University of Stuttgart. He works within the Cluster of Excellence IntCDC, focusing on the digital transformation of construction processes through robotics, automation, and advanced modeling techniques. Research Interests His work addresses the integration of Unmanned Aerial Vehicles (UAVs) for marker placement AprilTags detection for measurement accuracy Cable-driven robots for curtain wall installation Prefabricated layout definition Point cloud processing for renovation in construction workflows. He emphasizes automation, modular systems, and error-correction interfaces for building envelopes. Publications & Projects Recent articles highlight applications of robotics in residential renovation, machine learning for measurement precision, and kit-of-parts methodologies for façade upgrading. His research bridges technical innovation with practical implementation in construction lifecycle management. Education & Positions Kepa holds a PhD (2021) from the Technical University of Munich and a Master's degree in Architectural Construction from the University of the Basque Country. He has been affiliated with institutions such as the Technical University of Munich (2015–2021), Sungkyunkwan University (2015), and the University of Tokyo (2011–2014).

Paul Flemingمشاهده پروفایل

پژوهشگر

• Wind Farm Control
• Wake Steering
• Field Validation
• +۲ مورد دیگر

Paul Fleming is a Researcher at the National Renewable Energy Laboratory (NREL) , serving as Principal Investigator for wind energy control systems within the National Wind Technology Center. His work focuses on Wind Farm Control , Wake Steering , and Field Validation technologies. He acts as Operating Agent for IEA Wind Task 44 and Chief Editor for Wind Energy Science journal. Education : PhD in Electrical Engineering from Vanderbilt University Key Research Areas : Control systems for wind farms, wake steering optimization, field validation of renewable energy technologies Recent publications highlight applications of reinforcement learning in energy systems, robust wind farm layout design, and economic impacts of flow control strategies. He received the NREL Distinguished Member of Research Staff award in 2021.

Matthew Guthausمشاهده پروفایل

استاد

• Electronic Design Automation (EDA)
• VLSI Design
• Machine Learning for EDA
• +۵ مورد دیگر

Matthew Guthaus is a Professor at UC Santa Cruz, where he serves as lead Principal Investigator of the VLSI Design and Automation Lab and is a member of the Hardware Systems Collective. He founded the VLSI Design Automation (VLSI-DA) laboratory in 2006, focusing on physical design, circuits, and algorithms research for electronic design automation (EDA). His research spans low-power circuits, thermal-aware design, reliability, and machine learning applications in EDA. Guthaus's research interests center on advancing EDA through modern AI techniques, with active projects including GATMesh (GNN-based clock mesh analysis), GAT-Steiner (GNN-driven Steiner tree prediction), OpenGCRAM (open-source gain cell compiler), and effective capacitance modeling with GNNs. His work emphasizes open-source tool development and hardware innovation. Recent publications (2021-2025) demonstrate strong focus on machine learning integration within EDA workflows, open-source silicon initiatives, and memory design optimization. Key trends include graph neural networks for physical design challenges, democratization of EDA tools, and co-optimization techniques for AI hardware. Scientific awards include: NSF CAREER Award (2011) for resonant clocking research Guthaus leads the VLSI Design and Automation Lab, which develops open-source EDA tools like OpenRAM and collaborates within the Hardware Systems Collective. He contributes to NSF initiatives on integrated circuit education and workforce development, authoring workshop reports in 2021-2022. He will present recent work on OpenROAD optimizations at ORConf 2025.

Aurelian Vadeanمشاهده پروفایل

دانشیار

• Design and manufacturing
• Stress analysis
• Modeling, simulation and finite element methods
• +۸ مورد دیگر

Aurelian Vadean is an Associate Professor in the Department of Mechanical Engineering at Polytechnique Montréal, where he conducts research in advanced mechanical systems analysis and optimization. He holds a Doctorate from INSA Toulouse, France, along with DEA and Engineering credentials. His work is primarily conducted through the GAOSYM - Mechanical Systems Analysis and Optimization Group, and he serves as Research Director of the Road Safety Team: Vehicle Collisions, Defects and Special Investigations. Dr. Vadean's research spans multiple domains including topological optimization, biomechanics of implants, AI-driven structural design, joint optimization, and numerical simulation methods. His work addresses challenges in aerospace, automotive, and hydraulic turbine applications, with particular focus on composite materials and structural integrity. He has developed expertise in both theoretical and applied aspects of mechanical engineering, with strong connections to industry partners including Bombardier, Airbus, and Transport Canada. His publication record demonstrates a clear progression from fundamental mechanical analysis toward increasingly sophisticated computational methods integrating artificial intelligence with traditional engineering approaches. Recent work shows particular emphasis on topology optimization enhanced by machine learning techniques, composite materials for specialized applications, and biomechanical modeling for medical implants. Design Society, Member Research Center for High-Performance Polymer and Composite Systems (CREPEC), Member Dr. Vadean maintains an active supervision portfolio with numerous doctoral and master's students working on cutting-edge mechanical engineering problems. His research is supported by major funding from Transport Canada, NSERC, CRIAQ, Bombardier, and Airbus Atlantic Canada, focusing on vehicle collision investigations and topological optimization of aerostructure components. He leads research teams working on practical applications in transportation safety, sustainable infrastructure, and advanced manufacturing.

Manfred Dietrichمشاهده پروفایل

پژوهشگر

• Design automation
• IC design
• System design
• +۳ مورد دیگر

Manfred Dietrich is a Researcher at TU Dresden's Institute of Precision Engineering and Electronic Design, actively leading EU projects including HyPerStripes (2022-2025) and KI4BoardNet (2022-2025). His work focuses on design automation, IC design, and system design for advanced semiconductor integration. His educational background includes: 1970-1974: Dipl.-Ing in Information Technology, TU Dresden 1981: Promotion (PhD) on 'Fault localization in analog circuits' Dr. Dietrich's research centers on 3D/2.5D integration challenges, particularly interposer-based memory interfaces, thermal management of stacked systems, and Wide IO implementations. His methodologies address critical bottlenecks in signal integrity, power delivery, and design verification for next-generation semiconductor packaging. Publications from 2014-2016 demonstrate consistent focus on thermal optimization of 3D systems and XML-based design rule checking, establishing foundational work for current EU projects targeting high-performance computing architectures. Scientific awards: None documented. With extensive grant leadership including ECSEL's Microprince project (2017-2020) and current EU supervision roles, his portfolio reflects significant funding acquisition expertise. No student advisees are listed in available records. He actively contributes to industry standards through memberships in VDE's ITG/GMM groups, the GI/VDE 'Computer-aided circuit and system design' cooperation, and as an ECSEL Strategic Research Group expert.