Find Academic Supervisors

• Digital Twins
• Heavy Civil Engineering
• Construction Logistics
• +4 more

Anne Fischer, M.Sc., is a researcher at the Chair of Material Handling, Material Flow, and Logistics at the Technical University of Munich (TUM). Her work focuses on digital twins, construction automation, and resource scheduling in heavy civil engineering. She is based in Garching near Munich and collaborates with institutions like UC Berkeley and Stanford University. Research Interests: Digital Twin frameworks, simulation-based optimization, BIM integration, activity recognition in construction, and sustainable logistics systems. Collaboration: Serves as a contact person for international exchanges with U.S. institutions. Publication Trends: Her recent articles (2024–2021) address construction automation, digital twin applications, and variability management in civil engineering projects. Key Projects: Engaged in initiatives like Bauen 4.0 , MiProcess2Twin , and SiteRoute , which focus on digitalization and automation in construction. Location: Boltzmannstraße 15, Garching bei München (Room: 5505.EG.501).

Maria Ribera SanchoView profile

Professor

• Software Engineering
• Conceptual Modeling
• Ontologies
• +4 more

Dr. Maria Ribera Sancho is a Professor at the Polytechnic University of Catalonia (BarcelonaTech), holding roles as Dean of the Faculty of Informatics of Barcelona (2004–2010), Vice-Dean (1998–2004), and currently Manager of the Education and Training Department at the Barcelona Supercomputing Center (BSC-CNS). She chairs the EQANIE Accreditation Committee and serves on the ACM-W Europe Executive Committee. Her research focuses on Software Engineering, Conceptual Modeling, Ontologies, Learning Analytics, and IoT applications. Notable contributions include work on automated design using conceptual models, model-driven software development, and semantic-based IoT infrastructure monitoring. She leads projects like LinDaFIX (social welfare data tools) and REMEDiAL (ontology-driven software automation). Key awards include the UPC Quality in Teaching Prize (2005, 2021), Jaume Vicens Vives Distinction (2005), Sapiens Award (2011), and Festibity Award (2011). She advises doctoral and master’s students on topics like IoT semantic monitoring and educational ontology development. Academic director of the inLab FIB Talent Program, she also directs the PRACE Advanced Training Center at BSC. Main projects include TINTIN (SQL integrity tool), e-Catalunya (collaborative government platform), and PILARES (learning analytics for secondary education). Her work bridges academia and industry through competitive projects with companies and institutions.

• Software Engineering
• Machine Learning
• DevOps
• +3 more

Emelie Engström is a software engineering researcher at Lund University, specializing in empirical studies at the intersection of academia and industry. Her work focuses on regression testing, machine learning applications in software quality, DevOps practices, and aligning requirements engineering with autonomous systems validation. University: Lund University Research Areas: Software Engineering, Machine Learning, DevOps, Autonomous Systems Her recent research examines ML-driven bug report classification, sustainable DevOps for cyber-physical systems, and optimizing anomaly detection through industrial case studies. She has developed taxonomies like SERP-test to improve communication between academic researchers and software practitioners. Key article trends show strong emphasis on: 2025: ML techniques for bug classification 2024: Ericsson case studies on automated bug assignment 2023: Anomaly detection in DevOps 2021: Autonomous driving system testing As a prolific collaborator, she works with researchers across Sweden including Per Runeson, Markus Borg, and Kai Petersen on projects ranging from cognitive load analysis in large-scale development to regression test scoping in software product lines.

• Software System Quality
• Software Architecture Design and Evaluation
• Software Visualization and Reverse Engineering
• +8 more

Wilhelm Hasselbring is Professor of Software Engineering at the School of Electronics and Computer Science, University of Southampton. His research focuses on software system quality, architecture design, and distributed systems with emphasis on fault-tolerance and monitoring. Software System Quality Architecture Design and Evaluation Microservices and DevOps Digital Twins and Prototyping Open Science Practices Current research explores digital twin prototypes for smart farming applications, metamorphic testing methodologies, and scalable microservice architectures. His work bridges theoretical frameworks with industrial applications in middleware and cloud systems. Recent awards include the Ernst Denert Award for Software Engineering (2019-2020). Publications span topics from JavaBERT language models to MQTT bridge evaluations, emphasizing software visualization and reverse engineering techniques. Contact: W.Hasselbring@soton.ac.uk

Riku Ala-LaurinahoView profile

Researcher

• Digital Twin
• Cyber-Physical Systems
• Industrial Automation
• +3 more

Riku Ala-Laurinaho is a Researcher at Aalto University's Department of Energy and Mechanical Engineering, with a focus on Digital Twin technologies and Industrial Automation. He holds a Master's (2019) and Bachelor's (2018) in Engineering and Technology from Aalto University. His research interests span Digital Twins in industrial contexts, Cyber-Physical Systems, IoT applications, and data-centric systems. He explores semantic-enhanced industrial metaverse frameworks and collaborative design paradigms. Recent work emphasizes context-aware systems, torsional vibration analysis tools, and Human-Centric Manufacturing processes. His publications (16+), including high-impact articles in Journal of Manufacturing Systems and SoftwareX , reflect a focus on industrial innovation. METEX award (2020) Contributions to 5+ open-source datasets (e.g., OpenTorsion, A!ex autonomous car dataset) His advising includes 1 supervised thesis, with grant details pending.

• Control Engineering
• Telecommunications
• Cloud Computing
• +3 more

Johan Eker is a Professor at the Department of Automatic Control at Lund University and an Adjunct Professor at ELLIIT: the Linköping-Lund initiative on IT and mobile communication . He is also a member of the LTH Profile Area: AI and Digitalization and LU Profile Area: Natural and Artificial Cognition . His research focuses on control engineering, telecommunications, cloud computing, real-time systems, IoT, and anomaly detection. He actively contributes to UN Sustainable Development Goals through his work. He has received notable awards including the Best paper runner-up award at IEEE CloudNet 2023 , Best Paper Award at RTCSA 2004 , and Best Student Paper Award at RTCSA 1999 . Key projects include: AORTA: Advanced Offloading for Real-Time Applications (2023–2025) ICS: Industrial Cloud Sandbox (2019) AutoDC: Autonomous datacenter for long-term deployment (2018–2021) He has organized workshops such as the Real-Time Cloud Workshop and serves on the advisory board for Internet of Things and People (IoTaP) .

Srinivas ShakkottaiView profile

Professor

• Networking
• Wireless Networks
• Reinforcement Learning
• +6 more

Srinivas Shakkottai is a Professor in the Department of Electrical and Computer Engineering (ECE) and affiliated faculty in the Department of Computer Science and Engineering (CSE) at Texas A&M University. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2007), followed by a postdoctoral stint at Stanford University. Since 2008, he has been at Texas A&M, advancing through roles from Assistant to Associate Professor before attaining full Professor status. Education: Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign (2007) Postdoctoral Associate, Stanford University Research Interests: Focus on algorithms for communication, energy, and transportation networks. Key areas include wireless networks, reinforcement learning, caching/content distribution, multi-agent learning, game theory, networked markets, and systems design. He co-directs the LENS Laboratory and the Texas A&M Initiative on Connected Intelligence (TICI). Key Awards: NSF CAREER Award (2012) Google Faculty Research Award (2010) Defense Threat Reduction Agency Young Investigator Award (2009) Grants & Labs: Leads research projects funded by NSF, including collaborative efforts on EdgeRIC (NextG cellular networks) and Caching systems. Active in labs focused on AI-driven network optimization and intelligent control systems. Lab & Teams: Co-director of LENS Lab and TICI, emphasizing real-time intelligent control, edge computing, and networked intelligence.

Djamal ZeghlacheView profile

Professor

• Network Virtualization
• Cloud Computing
• Software-Defined Networking
• +5 more

Djamal Zeghlache is a Professor at Telecom SudParis (now part of Institut Polytechnique de Paris), where he leads research in network virtualization, cloud computing, and software-defined networking. His work spans multiple domains including wireless communications, network security, and AI applications in networking systems. Affiliated with the SAMOVAR laboratory (Services and Architectures for Multimedia and Ubiquitous Access to Resources), he has established himself as a prominent researcher in network and service management. Professor Zeghlache's research interests focus on the intersection of networking and artificial intelligence, with particular emphasis on network virtualization, cloud computing, and software-defined networking. His work addresses critical challenges in network function virtualization, resource allocation, and optimization in distributed systems. In recent years, he has expanded his research to include AI-driven approaches for network management, healthcare monitoring using wireless technologies, and optical network control. His publications demonstrate a consistent trajectory from traditional networking challenges to more complex, AI-integrated solutions for modern network infrastructures. Analysis of his recent publications (2023-2025) reveals a strong trend toward integrating machine learning, particularly deep reinforcement learning and graph neural networks, into network management systems. His work spans multiple application areas including healthcare monitoring (using RF-based techniques for vital sign detection), transportation systems (bike-sharing optimization), and optical networking (disaggregated control frameworks). The interdisciplinary nature of his research connects computer networking with biomedical engineering, urban mobility, and formal methods for system verification. Professor Zeghlache has supervised numerous PhD students and collaborated extensively with researchers across Europe and internationally. His work has resulted in significant contributions to network virtualization, cloud resource management, and network security. He has been involved in multiple research projects focusing on next-generation networking technologies, including 5G, network slicing, and cloud-native network functions.

Anya Helene BaggeView profile

Associate Professor

• Programming Language Design and Implementation
• Software Language Engineering
• Semantics of Programming Languages
• +8 more

Anya Helene Bagge is an Associate Professor in the Department of Informatics at the University of Bergen, where she is a researcher at the Bergen Language Design Laboratory. Her work focuses on programming languages and software language engineering, with strong ties to education and tool development. Research Interests: Programming language design and implementation Software language engineering Semantics of programming languages Domain-specific languages and language extensions Program transformation using Rascal, MPL, and Stratego/XT Aspect-oriented programming, especially Domain-Specific Aspect Languages Her recent publications reflect a consistent focus on software language engineering, refactoring, microservice security, and programming education. Themes across her work include language design, program analysis, and the development of educational tools and methodologies. Scientific Awards: The Realist Committee's Teaching Award 2016/17 Lecturer of the Year in Computer Science (Spring 2015) Anya Bagge actively supervises students, including PhD and Master’s candidates such as Tero Hasu, Kristoffer Haugsbakk, and Nina Andersen. She has been involved in numerous academic activities, including organizing the OOPSLE workshop and serving on program committees for conferences like SLE, HILT, and WCRE. She has also taught core courses including INF101, INF225, and INF328, demonstrating a strong commitment to both research and teaching. Labs and Teams: She is affiliated with the Bergen Language Design Laboratory , collaborating with researchers such as Magne Haveraaen, Eva Burrows, and Tero Hasu.

Ruozhou YuView profile

Assistant Professor

• Computer Networks
• Distributed Systems
• Cybersecurity
• +10 more

Ruozhou Yu is an Assistant Professor in the Department of Computer Science and a Courtesy Assistant Professor in the Department of Electrical and Computer Engineering at NC State University. His research focuses on computer networks, distributed systems, and cybersecurity , with applications to quantum networking, blockchain, IoT, cloud/edge computing, and machine learning . He earned his PhD in Computer Science from Arizona State University (2019) and his BS from Beijing University of Posts and Telecommunications (2013). Education: PhD, Computer Science, Arizona State University, 2019 BS, Computer Science, Beijing University of Posts and Telecommunications, 2013 Yu's research spans quantum internet (high-fidelity entanglement distribution, satellite-assisted quantum networks), blockchain technologies (payment channel networks, smart contracts, layer-2 security), and edge computing (resource provisioning, SLA verification, market design). He also explores machine learning in distributed systems (LLM fine-tuning on graphs) and network security (data delay attacks, Byzantine-robust federated learning). His recent publications (2024–2025) emphasize quantum networking (LACE, QuESat), edge computing SLAs (VeriEdge, WolfPack), and blockchain security (Thor, Fence). Articles like AdaOrb (PerCom 2025) and Physics-Informed Scheduling (RTAS 2025) highlight cross-domain innovations. Awards & Recognition: NSF CAREER Award (2021) IEEE TNSE Excellent Editor Award (2024) IEEE INFOCOM Distinguished TPC Member (2024, 2022, 2020) Yu supervises PhD and Master's students in quantum networking (Huayue Gu), blockchain (Xiaojian Wang), and edge computing (Zhouyu Li). He serves as Associate Editor for IEEE Transactions on Network Science and Engineering and Area Editor for Elsevier Computer Networks .

Dag SjøbergView profile

Professor

• Software Engineering
• System Development
• IT Systems
• +12 more

Dag Sjøberg is a Professor at the Department of Informatics (Ifi), University of Oslo . He also holds a part-time position at SINTEF Digital . His research focuses on empirical software engineering with emphasis on development processes , agile methodologies , technical debt , and programming skill assessment . Research Interests: Empirical methods (controlled experiments, case studies) Construct validity frameworks Agile and Lean practices Microservices architecture Software quality and maintainability Scientific Achievements: Led Simula Research Laboratory's Software Engineering department ranked #1 globally (2004-2008) Developed Guidelines for Construct Validity in software engineering research Extensive publication record in top venues like IEEE Transactions and Journal of Systems and Software Academic Background: Cand.scient. in Informatics (University of Oslo, 1987) PhD in Software Engineering (University of Glasgow, 1993) Professional Involvement: Co-founder and board member of three IT companies Former research director at Simula Research Laboratory (2001-2008) Current head of the Programming and Software Engineering research section at Ifi

Frans KaashoekView profile

Professor

• Computer Security
• Operating Systems
• Distributed Systems
• +4 more

Frans Kaashoek is the Charles Piper Professor in MIT's Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads the Parallel and Distributed Operating Systems (PDOS) group, focusing on secure systems, formal verification, and distributed computing. His work emphasizes crash-safe systems, concurrent programming, and cryptographic security. Education: PhD in Computer Science from Vrije Universiteit Amsterdam (1992), thesis on group communication in distributed systems under Andy Tanenbaum. Research interests include operating systems, networking, programming languages, and computer architecture. Notable projects: FSCQ (verified crash-safe file system), Perennial (framework for verifying concurrent systems), and Noria (high-performance web backend). Awards: ACM SIGOPS Mark Weiser Award (2001), ACM Prize in Computing (2010), National Academy of Engineering membership (2006), and American Academy of Arts and Sciences membership (2012). Publications: Over 150 papers on systems software, verification, and security. Authored textbooks like Principles of Computer System Design: An Introduction and xv6 commentary.

• Cloud Computing
• Distributed Systems
• Data Processing
• +4 more

Luis Antunes Veiga is an Associate Professor and Senior Researcher at INESC-ID Lisbon, affiliated with the Distributed Systems Group and the Computing Systems and Communication Networks Laboratory. His research focuses on Cloud Computing, Edge Computing, Distributed Systems, and Big Data processing. He teaches courses such as 'Cloud Computing and Virtualization' and 'Operating Systems, Virtualization and Cloud Computing.' His work emphasizes scalable systems, network-aware workflows, and resource-efficient data processing. Research Interests: His primary areas include distributed systems architectures, edge computing frameworks, graph processing algorithms, and software-defined systems. He explores topics like latency-aware network design, resource auction mechanisms for edge environments, and interoperable service workflows. His contributions span theoretical frameworks and practical implementations, such as the RATEE system for edge resource trading and the VeilGraph incremental graph processing framework. Publications: His recent work addresses challenges in distributed systems, such as elastic scaling of stream processing, efficient graph processing in Spark, and latency optimization in internet-scale workflows. These publications reflect a trend toward integrating software-defined approaches with edge and cloud infrastructures. Notable Awards: Best Young Researcher INESC-ID, Excellence in Teaching (IST 2012), and a Best-Paper Award at ACM/IFIP/Usenix Middleware 2007. Labs & Teams: Active in the Computing Systems and Communication Networks Laboratory, leading projects on edge computing and distributed systems.

Mario Di FrancescoView profile

Professor

• Wireless Networking
• Mobile and Ubiquitous Computing
• Internet of Things
• +4 more

Mario Di Francesco is a Professor at the Department of Computer Science, Aalto University. He holds the position of Professor in Computing Systems (ComputingSystems) Research Area and leads multiple research projects in networking and IoT. Previously, he was a research associate and adjunct faculty at the University of Texas at Arlington (2012–2014), and completed his PhD in Information Engineering at the University of Pisa under Prof. Giuseppe Anastasi. He also served as a research fellow at Scuola Superiore Sant'Anna in 2009. Research Interests : His work focuses on wireless networking, mobile and ubiquitous computing, and the Internet of Things (IoT). Key areas include edge computing, fog networks, virtual/augmented reality, and AI-driven resource management. His research contributes to UN Sustainable Development Goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), and industry/infrastructure development (SDG 9). Publications : His recent work spans topics like private virtual reality conversations, cloud-based network measurement frameworks (CLAIM), microservice connectivity analysis, and edge-DNN optimization. These publications reflect a trend toward integrating AI with distributed systems for real-time, low-latency applications in IoT and edge computing. Awards : Recipient of the Google Internet of Things Technology Research Award (2016) and MobileHCI Honorable Mention (2020). Grants & Projects : CRUISE (2023–2025): Cross-system architecture for autonomous wireless networks using lifelong machine learning. MeXICO (2020–2024): Mobile cross-reality through immersive computing. ASPECT (2016–2018): Spectrum utilization for mobile video. Labs & Teams : Leads research groups focused on edge computing, IoT systems, and immersive technologies. Collaborates with international partners on projects like fog radio networks and autonomous system design.

• Artificial Intelligence
• Machine Learning
• Internet of Things
• +13 more

Edoardo Patti is an Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He is actively involved in research and teaching, focusing on artificial intelligence, machine learning, IoT, smart grids, energy communities, co-simulation, and digital twin technologies. He is a member of the EDA (Electronic Design Automation) research group and the Interdepartmental Center IAM@PoliTo for Integrated Additive Manufacturing. His research interests span Artificial Intelligence, Machine Learning, Internet of Things, Smart Grids, Energy Communities, Co-simulation, Distributed Software Infrastructure, Digital Twin, Physics-Informed Neural Networks, and Reinforcement Learning . His work is closely aligned with Sustainable Development Goals such as Affordable and Clean Energy (Goal 7), Sustainable Cities (Goal 11), and Climate Action (Goal 13). The latest publications reveal a strong trend in AI-driven modeling for energy systems, including digital twins for wave energy converters, urban electric mobility simulation, real-time battery health estimation, and co-simulation platforms for integrated energy systems. His work combines machine learning with physical models and large-scale distributed systems to address sustainability challenges. He supervises several PhD students, including Maria Adelaide Loffa, Matia Torlini, Rafael Natalio Fontana Crespo, Pietro Rando Mazzarino, Claudia De Vizia, and Marco Massano. He has led numerous research projects funded by EU (H2020), PNRR, regional initiatives, and corporate contracts, particularly in additive manufacturing, smart grids, and IoT platforms. He is involved in multiple research groups and centers: EDA - Electronic Design Automation (DAUIN) Interdepartmental Center IAM@PoliTo - Integrated Additive Manufacturing