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Di YuanView profile

Professor

• Network Optimization
• Mathematical Optimization
• Communication Systems
• +2 more

Di Yuan is a Professor at the Department of Information Technology, Uppsala University, specializing in applied optimization within communication networks. Current research emphasizes network optimization for 4G/5G systems, wireless network capacity, optical network layout, and transportation scheduling for electric vehicle charging. The work integrates mathematical optimization , machine learning , and telecommunications to solve real-world network efficiency challenges. Faculty member in the Optimization Group Focus areas: Network optimization , Age of information , Wireless systems Collaborations with engineers and data scientists in edge computing and vehicular networks Recent publications analyze multi-cell caching , decentralized federated learning , and cross-attention network models . Research extends to passive cooling systems for base stations and proteome deconvolution in biomedical applications. Key partnerships with IEEE and interdisciplinary teams drive innovations in energy-aware scheduling and biomedical informatics .

Agnes RosnerView profile

Professor

• Visual Attention
• Working Memory
• Long-Term Memory
• +3 more

Professor Agnes Rosner is a leading academic at the Institute of Psychology , Leibniz University Hannover. Her research focuses on the interplay between visual attention and working memory , elaboration strategies , eye movements during verbal memory retrieval , exemplar-based judgment , preference decision-making , and ambiguity in decision processes . 2022: Flexibility Grant (30,000 CHF) from Swiss National Science Foundation 2019: Ambizione Grant (911,146 CHF) for "The mind's eye in episodic memory" 2016: University Prize (1,000 EUR) from Technical University Chemnitz Her recent publications analyze memory retrieval through eye movements, with projects funded by SNSF and DAAD. She leads the "Mind's Eye" research group studying memory-based eye movements in Switzerland (2021-2025) and has held roles as peer mentor and selection committee member for junior researchers.

• Wireless Communications
• Quality of Service
• Quality of Experience
• +5 more

Iffat Ahmed is a wireless networking researcher specializing in multimedia quality optimization, with a PhD from IMT School for Advanced Studies Lucca (2013). Her academic journey includes adjunct faculty roles at Allama Iqbal Open University and teaching positions at Pakistan's Federal Directorate of Education. Current affiliations reflect post-PhD research activity with international collaborations at CTTC Lab Barcelona. Her educational background features: PhD in Computer Science and Engineering, IMT School for Advanced Studies Lucca, Italy (2010-2013) Master's research on Cross-layer optimization for multimedia content over next generation networks Research focuses on Next Generation Wireless Networks with emphasis on cross-layer optimization for video services. She pioneers techniques in resource management , scheduling algorithms , and QoE-QoS mapping to enhance scalable video transmission in cellular environments. Her work bridges physical layer constraints with application requirements through PHY/application cross-layer design. Publication trends (2007-2013) show evolution from general multimedia traffic engineering to specialized LTE/femtocell solutions, with 2013 representing peak output in IEEE flagship conferences. Key themes include multicast transmission policies and adaptive scheduling for heterogeneous networks. Notable recognitions include: Second Prize, 'Inventare il Futuro' innovation forum (University of Bologna, 2013) Winner, ICT Report Writing Competition (Pakistan Ministry of IT, 2007) Research funding comprises Italian Government PhD scholarship and Erasmus grant for Barcelona collaboration. Past teaching roles demonstrate student mentorship capacity in operating systems and networking fundamentals. Current activity suggests continued research in multimedia QoS for emerging wireless standards without dedicated lab leadership.

Omar AbbaasView profile

Assistant Professor

• Smart Manufacturing
• Smart Supply Chain
• Cyber-Physical Systems
• +11 more

Omar Abbaas is an Assistant Professor in the Department of Mechanical Engineering at The University of Texas at San Antonio (UTSA) within the Klesse College of Engineering and Integrated Design. His academic background includes a dual-title Ph.D. in Industrial Engineering and Operations Research, an M.S. in Industrial Engineering, and a B.S. in Industrial Engineering from Jordan University of Science and Technology. Ph.D., The Pennsylvania State University (Industrial Engineering & Operations Research) M.S., The Pennsylvania State University (Industrial Engineering) M.S., SUNY Binghamton (Industrial & Systems Engineering) B.S., Jordan University of Science and Technology (Industrial Engineering) Dr. Abbaas specializes in smart manufacturing, cyber-physical systems, and supply chain optimization. His research integrates agent-based modeling, network optimization, and combinatorial auction techniques to address complex logistical and operational challenges in modern industrial systems. The recent publications highlight his work in electric vehicle charging infrastructure, supplier selection, and multi-agent scheduling systems. These articles reflect a consistent focus on optimization algorithms, auction mechanisms, and smart logistics solutions across transportation, supply chain, and manufacturing domains. His industry experience includes roles as a Black Belt process improvement leader in logistics, business analyst at an engineering consulting firm, and sheet metal design engineer in manufacturing. These practical engagements inform his academic research in network optimization, alternative fuel distribution, and quality assurance frameworks.

• Structural Engineering
• Bridge Engineering
• Steel Structures
• +5 more

Dr. Kollár Dénes serves as an Assistant Professor at the Department of Bridges and Structures within the Faculty of Civil Engineering at Budapest University of Technology and Economics (BME). His academic position focuses on structural engineering with specialization in bridge systems, steel structures, and advanced structural analysis methodologies. The department forms part of BME's historic engineering faculty, which has been central to Hungary's infrastructure development since 1782. His research portfolio demonstrates deep expertise in multiple critical domains of structural engineering: Bridge Engineering: Extensive work on the Széchenyi Chain Bridge rehabilitation, including corrosion assessment, risk analysis, and structural health monitoring of historical bridges Steel Structures: Investigation of residual stresses, distortions, and stability in welded connections, box sections, and corrugated web girders Advanced Monitoring: Development of deep learning-based systems for bridge weigh-in-motion and structural health assessment Corrosion & Failure Analysis: Probabilistic modeling of corrosion effects on steel components and structural reliability Welding Technology: Numerical simulation of welding processes and their impact on structural integrity Analysis of his 15 most recent publications (2022-2025) reveals a concentrated research trajectory centered on the Széchenyi Chain Bridge in Budapest, with 7 studies directly addressing its structural rehabilitation. Key methodological approaches integrate experimental measurements with numerical simulations, particularly in residual stress analysis of welded steel components. Emerging trends include the application of deep learning for structural monitoring systems (3 publications) and fire resistance studies of specialized steel girders. His work consistently bridges theoretical modeling with practical infrastructure challenges, emphasizing safety assessment of aging bridge systems. No scientific awards are documented in the available information sources. Academic advising activities and research grant details remain unspecified in current documentation. His departmental role involves direct contribution to structural engineering education at BME, though specific teaching responsibilities aren't detailed in the provided materials.

• Cyber Physical Systems
• Internet of Things
• Smart Mobility
• +5 more

Dr. Prasant Kumar Misra is a Senior Scientist at Tata Consultancy Services Research and Visiting Faculty at the Department of Cyber Physical Systems, Indian Institute of Science Bangalore. With over 60 publications in cyber physical systems, IoT, and smart mobility, his work focuses on optimization and decision intelligence for electric vehicle management and infrastructure systems. Research Interests : Intelligent cyber physical systems, smart mobility, operations research, sensor informatics. Scientific Awards : MIT TR35 India, ERCIM Fellowships, Best Paper Awards at ACM SenSys, EWSN, and COMAD. His articles from 2015–2025 cover topics like IoT optimization , EV routing algorithms , smart grid integration , and acoustic localization , with keywords spanning Computer Science , Electrical Engineering , and Applied Mathematics . He chairs IEEE and ACM chapters and serves on editorial boards for Elsevier Ad Hoc Networks and IEEE Intelligent Transportation Systems Magazine. Professional Roles : Chair-Elect, IEEE Bangalore Section Area Editor, Elsevier Ad Hoc Networks Journal Associate Editor, IEEE Intelligent Transportation Systems Magazine

Deniz VuruşkanView profile

Assistant Professor

• Textile Sciences and Engineering
• Yarn Technology
• Textile Technology Education
• +3 more

Deniz Vuruşkan is an Assistant Professor at the Department of Textile and Fashion Design under the Faculty of Fine Arts at Gaziantep University . With a doctorate in Textile Engineering from Çukurova University (2010), his career spans academic research, administrative leadership, and artistic contributions. PhD in Textile Engineering (Çukurova University, 2010) Master’s in Textile Engineering (Gaziantep University, 2003) Licence in Textile Engineering (Afyon Kocatepe University, 2000) His research focuses on textile technology , emphasizing yarn engineering , sustainable production , and innovative machinery design . Recent work explores recycled polyester blends, double core yarn mechanics, and carpet performance under dynamic loads. Articles highlight applications in material science , mechanical testing , and industrial automation . Vuruşkan has secured multiple national grants, including TÜBİTAK and SAN-TEZ projects, and holds a patent for ring-spinning machine modifications. He has served as Erasmus Coordinator (2016-2017) and Dean Assistant (2019), while organizing conferences on textile innovation. His artistic activities include curating and participating in mixed exhibitions like Modern Masallar Gecesi (2024) and Retrospective Traces (2017), blending technical expertise with creative design.

Vincent LiuView profile

Associate Professor

• Distributed Systems
• Networking
• Programmable Networks
• +7 more

Vincent Liu is an Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. He directs the Distributed Systems Lab (DSL) and leads the PennNetworks research group. His research bridges distributed systems and networking, focusing on programmable networks, fault-tolerance, cloud infrastructure, and Internet architecture. Education includes a Ph.D. from the University of Washington and undergraduate research at the University of Texas at Austin in compilers and parallel systems. Research spans distributed systems optimization, cloud computing, sustainable computing, and ML infrastructure. Recent publications emphasize low-latency systems (Paella), cloud multicast (Cloudcast), distributed snapshots (Beaver), and sustainable computing frameworks (Carbon Connect). Network simulation innovations include DONS and NetVision. Awards & Honors: NSF CAREER Award (2019) VMWare Early Career Award (2019) Best Paper Award, USENIX NSDI (2015) Google Fellowship in Networking (2014) Qualcomm Innovation Fellowship (2014) Facebook Faculty Research Award Google Research Award Advises 11+ PhD students, with graduates at Meta, AWS, Microsoft Research, and academia (e.g., Qizhen Zhang, Asst. Prof. at Toronto). Secured grants from NSF, VMWare, Facebook, and Google. Leads the Distributed Systems Lab and PennNetworks group exploring cloud architectures, programmable networks, and sustainable computing. Actively recruiting PhD students.

Kateryna MorozovskaView profile

Researcher

• Computational Methods for Energy Systems
• Physics-Informed Machine Learning
• Renewable Energy Integration
• +3 more

Kateryna Morozovska is a Researcher at the KTH Royal Institute of Technology , affiliated with the Division of Decision and Control Systems and the School of Electrical Engineering and Computer Science . Her work bridges computational methods and energy systems development, focusing on physics-informed machine learning for renewable energy integration and power transformer optimization. Education B.S. and M.S. in Electrical Mechanics from Zaporizhzhya National Technical University (2013) European Energy Masters program with mobility at DTU (Denmark), TU Delft (Netherlands), and NTNU (Norway) PhD in Electrical Engineering from KTH (2020) on 'Dynamic rating for applications in renewable energy' Licentiate from KTH (2019) Research Focus Kateryna's research emphasizes Physics-Informed Neural Networks (PINNs) for power system optimization, including transformer thermal modeling, cellulose degradation analysis, and renewable energy integration. Her projects explore dynamic rating techniques to enhance grid efficiency and sustainability, funded by Vinnova and applied in PV-power plants and wind farms. Scientific Contributions She has developed frameworks for transformer cost analysis, wind farm sizing, and sensor placement optimization using PINNs and MILP. Her work addresses environmental trade-offs in wind energy, such as raw material mining impacts, and investigates thermodynamic challenges in nanocellulose and power systems. Affiliations Kateryna collaborates with industry partners through the PINN Summer School and contributes to SweGRIDS and Mendeley communities. Her teaching includes hands-on PINN training and multi-GPU machine learning.

Soudeh GhorbaniView profile

Assistant Professor

• Systems and Networking
• Cloud Computing
• Data Center Optimization
• +4 more

Soudeh Ghorbani is an Assistant Professor of Computer Science at Johns Hopkins University (on leave since 2023) and a full-time Scientist at Meta. She directs the Hopkins Networking Lab and founded the Introduction to Computing Research (ICR) program. Her research focuses on foundational networked systems, including cloud infrastructure, data center optimization, and network congestion control, with grants from NSF, Google, Meta, Intel, and VMware. Education: Ph.D. in Computer Science, University of Illinois Urbana-Champaign (2016) M.Sc. in Computer Science, University of Toronto (2011) B.Sc. in Computer Engineering, Sharif University of Technology (2009) Research Interests: Systems and networking, cloud computing infrastructures, distributed AI training, network bottlenecks, formal methods, and control theory. Her work targets making the Internet faster and more reliable through provable system designs. Publication Trends: Recent articles (2020-2025) emphasize data center networks, congestion control, packet deflection, and network verification. Key themes include microburst mitigation, traffic pattern analysis, and scalable network algorithms. Awards: Facebook Faculty Research Award (for microburst detection) Intel Fast Forward Award Advising & Grants: Advises 8 PhD/MS students. Research supported by NSF, Google, Meta, Intel, and VMware. Directs the Foundational Networked Systems Lab, focusing on cloud/datacenter innovations. Labs & Teams: Leads the Hopkins Networking Lab. Founded ICR to introduce undergraduates to computing research. Lab members include PhD students Kevin Lu, Sana Mahmood, Sepehr Abdous, and Erfan Sharafzadeh.

Željko IvandićView profile

Professor

• Mechanical Engineering
• Structural Engineering
• Computer-Aided Design (CAD)
• +9 more

Željko Ivandić is a Full Professor at the Faculty of Mechanical Engineering in Slavonski Brod, University of Slavonski Brod, with a career spanning over three decades. His work integrates Mechanical Engineering , Structural Analysis , and Biomechanics , focusing on CAD, tribology, and sustainable design. Doctor of Technical Sciences, University of Zagreb (2002) Master of Science, University of Zagreb (1996) Graduate in Mechanical Engineering, Faculty of Mechanical Engineering in Slavonski Brod (1990) His research emphasizes product development , 3D printing , and environmental protection . Recent work includes biomechanical testing devices and LCA-based environmental assessments. Articles highlight interdisciplinary approaches to structural integrity , robotics , and industrial design . Projects like the Croatian-Slovenian fracture mechanics collaboration and EU-funded ME4CataLOgue underscore his expertise in applied engineering. He mentors through CroRIS and contributes to professional societies, including The Design Society.

Rishabh IyerView profile

Assistant Professor

• Computer Systems
• Performance Analysis and Optimization
• Operating Systems
• +5 more

Rishabh Iyer is an Assistant Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley. His research bridges computer systems, networking, and formal methods with a focus on performance predictability and reliability. Prior to Berkeley, he completed his PhD at EPFL and undergraduate studies at IIT Bombay. His educational background includes: PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL) Bachelor's degree from Indian Institute of Technology Bombay (IIT Bombay) Iyer's research centers on performance interfaces for computer systems – creating succinct abstractions that allow engineers to reason about system performance without understanding implementation details. His work spans three major directions: (1) Extracting performance interfaces from implementations, (2) Designing systems with predictable performance, and (3) Formally verifying performance claims. This research combines operating systems, networking, computer architecture, and formal verification techniques to address performance unpredictability in modern systems. His group develops tools like PIX for network functions, KFlex for kernel extensions, and Software LPN for hardware accelerators. His publications reveal strong focus on performance modeling for network functions, kernel extensions, and hardware accelerators, with recent work expanding into real-time systems and SD-WAN validation. The research consistently targets practical impact, with deployments at companies like Meta and Alibaba. Scientific recognition includes: ACM SIGOPS Dennis M. Ritchie Award Eurosys Roger Needham PhD Award Dimitris N. Chorafas Award Best Paper at VDAT 2019 Iyer actively advises students at UC Berkeley and teaches courses including CS 294-262 (Performance Analysis) and CS 168 (Internet Architecture). Previously at EPFL, he taught Principles of Computer Systems, Software Engineering, and Vector Calculus. His group seeks talented students interested in building reliable, high-performance systems. Current research directions include performance interfaces for distributed applications, next-generation kernel extensions, and formally verified network systems. He leads research within UC Berkeley's systems community and maintains strong connections with EPFL's Dependable Systems Lab where he completed his PhD.

• Stochastic Processes
• Stochastic Models of Evolving Populations
• Probability Theory
• +6 more

Donald Dawson is a Distinguished Research Professor at the Department of Mathematics and Statistics , Carleton University. His work spans over five decades, focusing on stochastic processes, population genetics, and interacting particle systems. Research Interests : Stochastic Processes, Stochastic Models of Evolving Populations, Measure-Valued Diffusions, Large Deviations, and Multiscale Analysis. His research often bridges theoretical probability with applications in biology and physics. Scientific Awards : CRM-Fields Institute Prize (2004) Article Trends : His recent publications emphasize mean-field models, interacting branching processes, and ultrametric systems, reflecting a sustained focus on stochastic dynamics and their mathematical foundations. Supervision : Available for honours project supervision. His career includes mentoring roles in stochastic population systems and queueing theory.

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +3 more

Aditya Raikwar is an Instructor in the Department of Computer Information Systems at Colorado State University's College of Business. His research focuses on human-computer interaction, particularly in augmented and virtual reality environments. He has pioneered studies on AR cue reliability, ML-driven visual search performance, and immersive 3D notification systems for practical applications like culinary training. Augmented Reality Interface Design Human-AI Collaboration Immersive Technology Evaluation Educational Simulation Usability Engineering His publications demonstrate consistent exploration of cognitive load reduction, sensory feedback optimization, and task efficiency in mixed reality contexts. While no formal awards or advisees are documented in this profile, his work contributes to advancing AR/VR applications in both professional and educational settings.

• Computer Science
• Blockchain Technology
• Internet of Things
• +4 more

Dr. Adia Khalid is a researcher at Bielefeld University's Faculty of Engineering, affiliated with the Knowledge Representation and Machine Learning Group. Her office is located at CITEC 1-229, and she can be contacted via telephone at +49 521 106-12214. Her research focuses on interdisciplinary applications of computer science, including blockchain technology, Internet of Things (IoT), smart grids, energy management systems, data security, and optimization algorithms. She investigates solutions for real-world challenges such as secure data trading in vehicular networks, electricity theft detection, robust IoT infrastructure, and renewable energy integration. Her publication trends show consistent work in energy systems optimization (microgrid management, load forecasting) and decentralized technologies (blockchain applications in transportation, data security, and IoT networks). Recent work demonstrates growing emphasis on AI-driven solutions for energy infrastructure and automotive systems.