جستجوی استاد راهنمای دانشگاهی

• Steel and Composite Systems
• Perforated Beams
• Structural Topology Optimisation
• +۷ مورد دیگر

Konstantinos Daniel Tsavdaridis is a Full Professor in Civil Engineering at City, University of London, leading the Steel, Steel-Concrete Composite and Hybrid Structures group. He holds dual roles as a researcher, educator, and industry consultant, with expertise in structural design, seismic resilience, and sustainable construction. His academic journey includes a PhD from City University London and post-doctoral appointments at Leeds University and City University. Education: BEng in Civil Engineering (City University London, 2005) MSc in Structural Engineering (Imperial College London, 2006) PhD in Civil/Structural Engineering (City University London, 2010) Research focuses on innovative steel and composite systems, including perforated beams, topology optimization, and seismic-resistant design. His group pioneered 3D-printed modular connections and lightweight composite flooring. Key contributions include over 160 peer-reviewed publications and patents in structural engineering. Professional roles: Senior Fellow, Royal Academy of Engineering (2019) Membership: Institution of Civil Engineers (Fellow), Engineering Council (Chartered Engineer), and multiple international engineering societies. Grants and funding: EPSRC grants for modular building resilience and energy-efficient design Royal Academy Fellowship for 3D-printed connections Labs/Teams: Leads the Steel-Composite Structures Group and the 3DMBC (3D-Printed Modular Building Connections) initiative, collaborating with industry and global partners.

Boris Blagojevicمشاهده پروفایل

پژوهشگر

• Computational Design
• Construction Engineering
• Cyber-Physical Systems
• +۳ مورد دیگر

Boris Blagojevic is a Doctoral Researcher at the Institute for System Dynamics (ISYS) within the Cluster of Excellence IntCDC at the University of Stuttgart. His work focuses on integrative computational design and construction systems for architecture. Research Projects FGC Building System – Design, Optimisation, Production, Reuse Cyber-Physical Fabrication of Functionally Graded Concrete Prestressed Basalt Reinforced Graded Concrete Components His research spans computational design, construction engineering, and sustainable material systems.

• Parallel and Distributed Systems
• Graph Optimization
• Big Data
• +۷ مورد دیگر

Tomaž Dobravec is an Assistant Professor at the Faculty of Computer and Information Science, University of Ljubljana, Slovenia. He is actively involved in research and teaching in computer science, with a focus on system software, algorithms, and distributed computing. His work is supported by national research programmes and structural funds projects. His research interests include: Parallel and Distributed Systems Graph Optimization and Big Data Combinatorial Scientific Computing Mobile and Industrial Operating Systems Interactive Educational Software Development The trend in his research projects indicates a strong emphasis on algorithmic efficiency, large-scale data processing, and practical software solutions for both industrial and educational contexts. His involvement in long-term ARRS programmes (e.g., P2-0095) highlights sustained contributions to core computing disciplines. He has participated in several research and development projects, including: P2-0095 - Parallel and distributed systems (2020–2026) N2-0171 - Graph Theory and Combinatorial Scientific Computing (2021–2023) PKP6 - Mobile Operating System for Industrial Use (MobiIOS) (2020) Graph Optimisation and Big Data (2016–2019) Development of the Visual Assistant project (2016–2017) Design and programming of interactive electronic textbooks (2017) He teaches key undergraduate courses such as System Software Programming 2 , Algorithms and Data Structures 2 , and The C Programming Language , indicating a strong foundation in core computer science education. While no formal advisees are listed, his role in research projects suggests mentorship of students and junior researchers. There is no mention of scientific awards in the provided text.

• Hydrothermal Liquefaction
• Process Design and Optimisation
• Minerals Processing
• +۳ مورد دیگر

Dr Thomas Scott is an early career teaching academic and researcher at the University of Adelaide's School of Chemical Engineering within the Faculty of Sciences, Engineering and Technology. He holds a Bachelor of Engineering (Honours) in Chemical and a PhD in Engineering (Process and Resource Engineering), both from the University of Adelaide. His research expertise centers on hydrothermal liquefaction with key interests in process design and optimisation. He has expanded his research portfolio to include minerals processing, winery sustainability, brewery engineering, and water & wastewater engineering. As the teaching laboratory coordinator for the School of Chemical Engineering, he oversees the Unit Operations Laboratory course and coordinates practical components in core chemical engineering courses. Dr Scott is eligible to supervise Masters and PhD students as a co-supervisor, reflecting his growing role in academic mentorship despite being early in his career. His professional activities demonstrate a strong commitment to both research innovation and hands-on chemical engineering education.

Shervan Babamohammadiمشاهده پروفایل

پژوهشگر ارشد

• CO2 Capture and Utilisation
• Hydrogen Production Processes
• Environmental Engineering and Sustainability
• +۳ مورد دیگر

Shervan Babamohammadi is a Research Fellow in the Chemical Engineering Department at the University of Wolverhampton , specializing in CO2 capture technologies, blue hydrogen production, and gas separation. His expertise includes process modelling and optimization for carbon capture systems, development of novel solvents, and supervision of PhD/undergraduate students. He previously held a postdoctoral position at Brunel University London (2022) and earned his PhD from the University of Malaya (2021). Education PhD in Chemical Engineering (University of Malaya, 2021) MSc in Chemical Engineering (University of Technology of Malaysia, 2012) B.Eng. in Chemical Engineering (University of Mazandaran, 2008) Research Interests: Focused on sustainable CO2 capture methods using novel solvents, hydrogen production optimization, environmental engineering for renewable energy integration, and mass transfer behavior in gas absorption systems. His work involves lab-scale and pilot-scale experiments. Publications: His recent works highlight advancements in hydrogen production with machine learning integration (2023), design of experiments for blue hydrogen systems (2023), bio-based sorbents for carbon capture (2022), and solvent solubility studies (2015-2023). Professional Memberships: Graduate Engineer, Board of Engineers Malaysia (BEM) since 2020 Associate Member, Institute of Chemical Engineers (IChemE) since 2020 Graduate Member, American Institute of Chemical Engineers (AIChE) since 2020 Full Member, Iranian Association of Chemical Engineers (IAChE) since 2020 Early Career Researcher Member, UKCCSRC since 2022 Industry Experience: Engaged in freelance consultancy projects related to chemical engineering and carbon capture.

Andreas Miroslaus Wichertمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۷ مورد دیگر

Andreas Miroslaus Wichert is an Associate Professor at the University of Lisbon, affiliated with INESC-ID (GAIPS research group). His academic journey includes studies in computer science at the University of Saarland and a PhD in computer science from the University of Ulm (2000). He has taught courses like Artificial Intelligence, Machine Learning, Deep Learning, and Quantum Artificial Intelligence at institutions including University of Lisbon and Technical University Munich. Born in Wrocław, Poland, with a grandfather who was a Polish officer (Katyn massacre memorialized) Current affiliations: University of Lisbon, INESC-ID, GAIPS research group Research Interests Andreas specializes in Artificial Intelligence , Machine Learning , Quantum Artificial Intelligence , and Neural Networks . His work explores intersections between quantum computing and AI, as detailed in his 2024 book Quantum Artificial Intelligence with Qiskit . He also investigates cognitive systems and high-dimensional data indexing through the HEIDI project. Scientific Awards Recipient of multiple teaching excellence awards for courses in: Logic for Programming (24/25) Machine Learning (21/22, 23/24, 24/25) Decision Support Systems (14/15) Intelligent Multimedia Databases (14/15) Advising Currently supervises PhD students Maria Osorio, Jose Miguel Penedo Ramos, and Joaquim Domingos Mussandi. Past advisees include Dr. Luis Tarrataca, Dr. Angelo Cardoso, Dr. Joao Sacramento, Dr. Catarina Pinto Moreira, and Dr. Luis Sa-Couto. Projects & Labs Lead developer of the HEIDI project (High-Dimensional Indexing), and active member of the GAIPS research group since 2009.

• Process Control
• Instrumentation
• Process Design and Optimisation
• +۵ مورد دیگر

Dr Nam Nghiep Tran is a Senior Lecturer in the School of Chemical Engineering at the University of Adelaide, serving as Associate Dean of Internationalisation (Southeast Asia) within the Faculty of Sciences, Engineering and Technology (SET). His work focuses on fostering academic collaborations between Australia and Southeast Asia, particularly Vietnam. Education: BEng (Chemical Engineering) from Can Tho University, MEng (Chemical System Engineering) from the University of Tokyo, and PhD from the University of Adelaide. Dr. Tran's research interests span process control, renewable energy, reaction engineering, thermal/non-thermal plasma technologies, and ESG principles. He plays a key role in promoting sustainable technologies through interdisciplinary research. He co-founded the Adelaide University Vietnamese Students Association (AVA) and leads the South Australia chapter of the Vietnam-Australia Scholars & Experts Association (VASEA), enhancing academic networks between Australia and Vietnam. Additionally, he serves as Associate Editor-in-Chief of Green Processing and Synthesis (GREENPs).

Alessandro Checcoمشاهده پروفایل

استادیار

• Crowdsourcing
• Human Computation
• Distributed Systems
• +۷ مورد دیگر

Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems. His educational background includes: 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks) 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers. His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field. Among his notable achievements: All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award) Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland. His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.

• Genetic Programming
• Evolutionary Algorithms
• Combinatorial Optimisation
• +۶ مورد دیگر

Dr. Edgar Galván is an Associate Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. He is a leading expert in Genetic Programming (GP) and Evolutionary Algorithms, with a focus on semantic-based approaches, neutrality, and multi-objective optimization. His work spans applications in combinatorial optimization, gaming (e.g., Carcassonne), and software engineering, including neuroevolution for deep learning architectures. Current Affiliation: Maynooth University Previous Roles: Senior Researcher at University College Dublin, Trinity College Dublin, and INRIA Paris-Saclay Research interests include: Semantic-based Genetic Programming Multi-objective Evolutionary Algorithms Monte Carlo Tree Search Circular Economy Applications Privacy-Preserving Optimization Neuroevolution in Autonomous Systems His recent publications analyze semantic diversity in GP, neural architecture search, and privacy-aware swarm optimization. Key awards include being ranked among the top 1% of GP researchers by University College London (2020), a Marie Curie Fellowship (2014), and a Best Paper Award at ECTA 2015. Current Projects: REBUILD (Circular Economy Buildings, 2024-2027), VISION (Circular Business Models, 2023-2026) Previous Grants: Stochastic Bio-inspired Algorithms (2014-2017, €267k), circAI (2022-2023, €142k) Dr. Galván serves on program committees for IEEE, ACM, and Springer conferences, and as Scientific Adviser for institutions in Ireland, France, and Mexico. His work bridges theoretical GP analysis with real-world applications in energy optimization and AI.

• Fracture mechanics
• Acoustic emission monitoring
• Hybrid composite-concrete structures
• +۳ مورد دیگر

Sven De Sutter is a Visiting Professor (Paid guest professor) in the Mechanics of Materials and Constructions research group at Vrije Universiteit Brussel (VUB) , Belgium. His affiliation with VUB centres on advancing structural engineering solutions for lightweight, high-performance composite and concrete systems. Research Focus: Fracture mechanics and damage characterisation of cementitious and composite materials Acoustic emission monitoring and digital image correlation for real-time structural health assessment Development of hybrid textile- or fibre-reinforced concrete beams for lightweight construction His investigations integrate experimental validation with analytical modelling, aiming to optimise safety and durability while reducing material usage in civil infrastructure. Publication Trends: Across 26 outputs captured between 2013 and 2019, De Sutter’s work consistently targets composite-concrete hybrid beams , employing acoustic emission as a primary non-destructive evaluation tool. Key themes include fracture monitoring, damage source identification, and the structural performance of carbon- and textile-reinforced lightweight systems, reflecting a trajectory towards sustainable, resilient construction technologies. Scientific Recognition: While the provided text does not list any specific awards or honours, his publications have attracted 230 citations (Scopus) and an h-index of 6, indicating growing impact within the engineering community. Supervision & Grants: De Sutter has co-supervised at least one Master’s thesis (2012) entitled “Analyse en haalbaarheidsstudie van een innovatief lichtgewicht composiet bekistingssyteem voor betonnen balken” . Further doctoral supervision or grant details are not disclosed in the text. Laboratory & Collaboration: He conducts research within the VUB Mechanics of Materials and Constructions laboratories, collaborating closely with colleagues such as Prof. T. Tysmans, Dr. S. Verbruggen, Dr. D. Angelis, and others, forming an active network around advanced composite and concrete experimentation.

• Computational Intelligence
• Evolutionary Multi-objective Optimization
• Evolutionary Machine Learning
• +۵ مورد دیگر

Professor Hisao Ishibuchi is Chair Professor of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China, a role he has held since April 2017. Previously, he spent nearly three decades at Osaka Prefecture University, progressing from Research Associate (1987-1993) to Assistant Professor (1993), Associate Professor (1994-1999), and full Professor (1999-2017). He is an IEEE Fellow , served as Vice-President of the IEEE Computational Intelligence Society (2010-2013) , and is currently President of the Japan Society for Evolutionary Computation (2016-2018) . He is Editor-in-Chief of IEEE Computational Intelligence Magazine (2014-2019) and the Journal of the Japan EC Society (2014-2018). Education: Ph.D. in Engineering, Osaka Prefecture University, 1992 M.S. in Engineering, Kyoto University, 1987 B.S. in Engineering, Kyoto University, 1985 Research Focus: Professor Ishibuchi is internationally recognised as a pioneer of computational intelligence , with seminal contributions to evolutionary multi-objective optimisation , evolutionary machine learning , fuzzy systems , neural networks , and hybrid intelligent systems . He introduced the first multi-objective memetic algorithm and early methods for multi-objective fuzzy rule-based classifier design that balance accuracy and interpretability. Publications & Impact: With over 100 journal papers in top-tier venues such as IEEE Transactions on Evolutionary Computation and nearly 500 conference papers, his work has attracted more than 24 000 Google-Scholar citations and an h-index of 68. His recent articles concentrate on many-objective optimisation, fuzzy machine learning, and transfer learning techniques. Honours & Awards: IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award 2019 IEEE Fellow 2014 JSPS Prize 2007 (Japan’s most prestigious mid-career award) Multiple Best Paper Awards from GECCO, FUZZ-IEEE, SCIS & ISIS, WAC, ACIIDS, HIS-NCEI, and others Teaching & Mentoring: At SUSTech he teaches Advanced Algorithms and Advanced Optimization Algorithms , covering greedy algorithms, hyper-heuristics, memetic algorithms, multi-objective optimisation, and performance assessment. His research group actively recruits post-doctoral fellows and research assistants in evolutionary computation, fuzzy systems, and neural networks. Labs & Teams: He leads the Computational Intelligence Research Group at SUSTech, maintaining active collaboration networks across Asia, Europe, and North America, and supervising several post-doctoral researchers and graduate students working on next-generation intelligent systems.

Andrew Wardمشاهده پروفایل

پژوهشگر ارشد

• Wastewater Treatment
• Microalgae Biotechnology
• Anaerobic Digestion
• +۳ مورد دیگر

Dr. Andrew Ward is an ARC Early Career Industry Fellow at the Australian Centre for Water and Environmental Biotechnology (ACWEB) within the Faculty of Engineering, Architecture and Information Technology at The University of Queensland. He leads research projects focused on wastewater treatment, nutrient recovery, and microalgae biotechnology, with significant industrial experience working with water utilities to scale research to pilot and demonstration levels. Dr. Ward holds a PhD from the School of Chemical Engineering at the University of Adelaide, where his thesis focused on the optimisation of halophilic anaerobic digestion of algal biomass. He also earned a Bachelor (Honours) degree from Flinders University. His educational background provides a strong foundation in chemical and environmental engineering principles applied to water and wastewater treatment. Dr. Ward's research primarily focuses on innovative approaches to wastewater treatment and resource recovery. His work spans nutrient recovery via electrodialysis, Anammox processes for domestic and agricultural wastewater treatment, and the development of algae-bacterial aggregated flocs (ABAF) for wastewater remediation. He investigates microalgae's role in energy and nutrient recovery from a circular economy perspective, aiming to transform wastewater treatment facilities into resource recovery centers. His research integrates biological, chemical, and engineering approaches to create sustainable solutions for water management challenges. Dr. Ward has extensive experience scaling laboratory research to pilot and demonstration levels, working closely with industry partners including Urban Utilities. Dr. Ward's publication record demonstrates a consistent focus on advancing wastewater treatment technologies, with recent articles examining deep learning applications, nutrient recovery systems, and sustainable biogas production. His work shows a clear progression toward more integrated, circular economy approaches to water management, emphasizing resource recovery alongside treatment. ARC Early Career Industry Fellowship (2024-2027): "Circular Economy", via renewable energy and resource recovery ARC Industry Fellowship Advance Queensland Industry Research Fellowship (2020-2023): Aggregated algal/bacterial flocs for wastewater treatment and algae industries Dr. Ward serves as lead investigator for Urban Utilities' wastewater microalgae research program and manages multiple research projects with industry partners. He currently supervises PhD students working on "Recovery of high-value coloured organic compounds from wastewater" and previously supervised research on "Algae Bacteria Aggregated Flocs in the Enhanced Treatment of Wastewater." His research has attracted significant funding from the Australian Research Council, Queensland government, and industry partners, demonstrating the practical relevance and impact of his work. Dr. Ward works within the Australian Centre for Water and Environmental Biotechnology (ACWEB), collaborating with researchers across engineering, microbiology, and environmental science disciplines. His team focuses on developing and scaling technologies that address real-world water treatment challenges while recovering valuable resources from wastewater streams.

Yingqian Zhangمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Deep Reinforcement Learning
• +۷ مورد دیگر

Yingqian Zhang is an Associate Professor in the Information Systems group at the Industrial Engineering and Innovation Sciences department of Eindhoven University of Technology (TU/e). She is affiliated with the Eindhoven Artificial Intelligence Systems Institute (EAISI), specifically with the EAISI High Tech Systems and EAISI Foundational groups. Her research focuses on applying Artificial Intelligence to solve complex decision-making problems across various domains including logistics, transportation, manufacturing, and e-commerce. Dr. Zhang received her PhD in Computer Science from the University of Manchester, UK. Prior to joining TU/e, she served as an Assistant Professor in the Econometrics Institute at Erasmus University Rotterdam and as a postdoc researcher in the Algorithmics group at TU Delft. She was also a visiting professor at the Institute for Advanced Computer Studies at University of Maryland, College Park, USA. Her research expertise lies at the intersection of Artificial Intelligence and optimization, with particular focus on machine learning, deep reinforcement learning, and trustworthy data-driven optimization. Dr. Zhang develops socially aware algorithms that can optimize decisions in data-rich environments. Her work bridges the gap between theoretical AI advancements and practical applications in industrial settings, addressing real-world challenges through innovative algorithmic solutions. She is particularly interested in how AI can support human decision-making while maintaining transparency and trustworthiness. Dr. Zhang's recent publications reveal a strong trend toward applying graph neural networks and reinforcement learning to complex scheduling and optimization problems. Her work demonstrates increasing sophistication in handling stochastic elements in decision-making processes, with applications spanning healthcare diagnostics, logistics, transportation, and manufacturing. She has made significant contributions to the field of neural combinatorial optimization, particularly for job shop scheduling problems and vehicle routing. Dr. Zhang has received several prestigious awards recognizing her contributions to the field: Winner of the MLVRP2023 GECCO competition (2023) Best Paper Award from Omega-International Journal of Management Science (2017) Best Industrial Paper Award (2020) Best Student Paper Award (2019) Best Student Paper Award of ICAART 2022 (2022) As a dedicated mentor, Dr. Zhang supervises numerous PhD students including Mohsen Abbaspour Onari, Abdo Abouelrous, Luca Begnardi, Xia Jiang, Chengpeng Hu, Minshuo Li, Robbert Reijnen, Jesse van Remmerden, Bart von Meijenfeldt, Ya Song, and Igor Smit. Her research is supported by various grants, including the LEO (Learning and Explaining Optimization) project co-funded by Holland High Tech | TKI HSTM via the PPP allowance scheme for public-private partnerships. Dr. Zhang actively contributes to the academic community as the Chair of the Benelux Association for Artificial Intelligence (BNVKI) and as a member of the Technical Board for the European Big Data Value Association (BDVA). She serves as an associate editor for the "Annals of Mathematics and Artificial Intelligence" journal and participates in the technical Program Committee for major AI conferences such as IJCAI, AAAI, AAMAS, and ECAI. She is also on the executive committee of the Data Science meets Optimisation (DSO) working group of EURO to promote collaboration between AI and Operations Research communities.

• Animal cell technology
• Systems biology
• CHO cell engineering
• +۸ مورد دیگر

Nicole Borth is Associate Professor (associate Univ.Prof.) at the University of Natural Resources and Life Sciences, Vienna (BOKU) and Deputy Head of the Institute of Animal Cell Technology and Systems Biology . Her work sits at the intersection of cell engineering, systems biology and biopharmaceutical manufacturing, with CHO and HEK293 cells as primary platforms. Research in a nutshell: Genome-wide CRISPR/Cas deletion and activation screens to map essential loci and boost recombinant protein titres. Epigenetic and synthetic-biology toolboxes (dCas9-DNMT, synthetic promoters, RNA devices) for multiplexed gene-control. Glyco-engineering and biomarker discovery to optimise critical quality attributes of monoclonal antibodies. Low-cost, animal-component-free media design and microfluidic single-cell cloning to shorten development timelines. Between 2022-2025 her group released a rapid succession of papers exploiting nanopore Cas9-targeted sequencing to pinpoint transgene integration sites, unveiled novel stress-biomarkers for difficult-to-express mAbs, and provided public-domain glyco-analytics for the NIST CHO reference line. Parallel projects apply similar tool-chains to AAV production in HEK293 and characterise human diamine oxidase biopharmaceuticals. Awards & funding: Specific prizes not enumerated in supplied text; however, the volume and recency of high-impact publications indicate sustained competitive funding. Contact: nicole.borth@boku.ac.at | Tel +43 1 47654-79064 | Muthgasse 11, 1190 Vienna, Austria.

• High Performance Computing
• HPC Interconnection Networks
• Enterprise Data Centre Networks
• +۶ مورد دیگر

Ernst Gunnar Gran is Associate Professor at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), where he heads the communication technology discipline. He also holds an adjunct research scientist position at Simula Research Laboratory, where he headed the Cloud department until December 2016. His research spans high performance computing (HPC), HPC interconnection networks, enterprise data centre networks, cloud computing, and data-intensive processing in multi-clouds. He serves as the Scientific Leader of Communication Technologies in the RCN-funded infrastructure project eX3 (Experimental Infrastructure for Exploration of Exascale Computing) and has significant experience with both RCN-funded and EU-funded research projects, including the H2020 project Melodic (Multi-cloud Execution-ware for Large-scale Optimised Data-Intensive Computing). Gran received his M.Sc. and Ph.D. degrees in computer science from the Department of Informatics, University of Oslo, in 2007 and 2014, respectively. Both theses focused on different aspects of resource management in high performance interconnection networks. He previously headed the RCN-funded project ERAC (Efficient and Robust Architecture for Big Data Clouds) and led the design, implementation, and deployment of the multi-homed IP-based research testbed NorNet Core. Gran also has several years of experience as a system administrator and scientific programmer. His research interests center on the intersection of high performance computing and networking, with particular focus on anomaly detection in time series data, HPC interconnection networks, network virtualization, and cloud computing infrastructure. His work demonstrates a consistent evolution from fundamental networking research to applied solutions for modern computing challenges, particularly in IoT security and smart home applications. His recent publications show a strong emphasis on developing lightweight, real-time anomaly detection systems using deep learning techniques. Analysis of his publication trends reveals a clear progression from traditional HPC networking research toward time series anomaly detection applications, particularly for IoT systems. His 15 most recent publications show dual focus areas: approximately 60% concentrate on anomaly detection methods for time series data (particularly for IoT applications), while the remaining 40% maintain his foundational work in HPC networking, virtualization, and cloud infrastructure. This evolution demonstrates his ability to adapt core networking expertise to emerging application domains while maintaining technical depth. While no specific scientific awards are mentioned in the provided text, Gran's leadership roles in significant research projects (eX3, Melodic, ERAC) indicate recognition of his research capabilities within the academic and research funding communities. His position as Scientific Leader of Communication Technologies in the RCN-funded eX3 project further demonstrates his standing in the Norwegian research community. Gran's teaching responsibilities include serving as course coordinator for DCSG1006 Data Communication and Networks, DCSG2001 Interconnected Networks and Network Security, and Networks: Administration, Programming and Security. His research leadership extends to significant grant-funded projects, including the RCN-funded eX3 infrastructure project and the EU H2020 Melodic project. His previous leadership of the ERAC project and the NorNet Core research testbed demonstrates sustained ability to secure and manage substantial research funding. His laboratory and team affiliations include the Department of Information Security and Communication Technology at NTNU, where he heads the communication technology discipline, and Simula Research Laboratory, where he maintains an adjunct position. The NorNet Core research testbed, which he led the development of, represents a significant infrastructure contribution to the networking research community. His current work with the eX3 project suggests ongoing involvement in experimental infrastructure for exascale computing exploration.