Nouh Alhindawi is an Associate Teaching Professor at Arizona State University's School of Computing and Augmented Intelligence. His research focuses on Software Engineering, Natural Language Processing, and Machine Learning applications in education. He actively teaches courses like Software Enterprise, Programming Languages, and Software Factory Capstone projects. Key research interests include improving software testing quality, analyzing code complexity, and leveraging AI for education technology. Notable work includes studies on student performance prediction, IoT security, and Arabic text emotion classification. His teaching portfolio spans both undergraduate and graduate levels, emphasizing practical software development methodologies. Prominent publications address challenges in localization techniques, network security, and deep learning applications across healthcare and education sectors.
Dr. Xueqin Amy Liu is a Senior Lecturer at Queen’s University Belfast (QUB) in the School of Electronics, Electrical Engineering and Computer Science. She holds a Ph.D. from QUB (2009) through a joint program with Zhejiang University. Her research bridges power systems and data analytics, focusing on smart grid challenges, energy storage, and renewable integration. She leads industry-driven projects like the €6.7M INTERREG SPIRE2 initiative, advancing energy storage solutions and grid stability. Dr. Liu is a Senior Member of IEEE and serves as an Associate Editor for IET Energy Conversion & Economics. She has supervised 13 PhD students and 2 postdocs, many employed in energy sectors. Notable achievements include the Best Graduate Student Poster Award (2021) and the Outstanding Associate Editor Award (2024). Education: Ph.D., Electrical and Electronic Engineering, Queen’s University Belfast (2009), joint with Zhejiang University Research Interests: Smart Grid data analytics, machine learning for grid stability, energy storage optimization, and renewable integration. Her work addresses real-world challenges with industry partners like EirGrid and SONI, developing tools for grid oscillation detection and energy market strategies. Recent Articles: Focus on oscillation mode identification, dynamic mode decomposition for grid analysis, and machine learning for electricity price forecasting. These contributions enhance grid stability and renewable integration. Awards: EPSRC Impact Acceleration Award (2022) Outstanding Associate Editor Award (IET, 2024) Best Graduate Student Poster Award (IEEE PES, 2021) Advising & Grants: Supervised 13 PhD students (e.g., Javier Lopez Lorente, Mark Rafferty) and led projects totaling millions in funding. Active in the SPIRE2 project and EU INTERREG programs. Labs/Teams: Her team develops diagnostic tools for grid oscillations and behind-the-meter analytics, collaborating with transmission system operators to enhance grid visibility and flexibility.
Dr. Kieran McLaughlin is a Reader at Queen's University Belfast, leading research in cyber security for operational technologies (OT), including smart grids and industrial control systems (ICS). He focuses on threat analysis, intrusion detection/prevention, and digital twins for incident response. His work addresses SCADA systems, ICS protocols (e.g., IEC61850), and cyber-physical resilience. He leads projects like XANDAR (H2020) and CAPRICA, and collaborates with UK's RITICS institute. He teaches Network Security (CSC3064) and actively publishes in top-tier venues. His research spans over 100 publications, with recent focus on digital twins, AI-driven malware detection, and secure IoT communications. Projects include EU-funded initiatives targeting critical infrastructure security and embedded system safety. He advises on cybersecurity for energy sectors and contributes to global standards like DO-326A for avionics systems. Key areas of innovation include deception platforms using digital twins, lightweight AI for IoT security, and blockchain-based predictive maintenance in vehicular networks. His work integrates machine learning for automated response and explores novel networking architectures (e.g., Named Data Networking) to enhance security.
Giuseppe Andrea Ferro is a Full Professor at the Department of Structural, Geotechnical and Building Engineering (DISEG) at Politecnico di Torino, where he also serves as Vice-Rector for Student Recruitment and Job Placement. He is a member of the Interdepartmental Center SISCON - Safety of Infrastructures and Constructions, and leads a research group focused on structural mechanics, fracture behavior, and sustainable construction materials. His academic leadership extends to supervising PhD programs in Civil and Environmental Engineering and Biomedical Engineering, and serving on multiple doctoral school committees. Education: Ph.D. in Structural Engineering, Politecnico di Torino (1994) Master's in Civil Engineering, University of Catania (1988) His research spans structural mechanics , fracture mechanics of concrete , seismic risk , and high-performance eco-friendly materials , with a focus on 3D printing, exoskeletons, and satellite-based monitoring. Recent publications highlight innovations in foamed concrete , fiber-reinforced composites , and performance-based structural optimization . His work integrates experimental, numerical, and sustainability-driven approaches to address modern infrastructure challenges. The trend in his recent publications demonstrates a strong shift toward sustainable construction , digital fabrication , and resilience-based design . Key themes include the use of recycled and bio-based materials, advanced monitoring via satellite data, and computational optimization of structural systems. His research bridges theoretical mechanics with practical applications in seismic zones and infrastructure rehabilitation. Scientific Awards and Honors: Fellow, European Structural Integrity Society (ESIS), 2010–present President, ESIS, 2002–2010 Secretary, ESIS, 2002–present Fellow, Italian Fracture Group, 2005–2011 Treasurer, Italian Fracture Group (IGF), 1998–2005 President, Italian Group of Fracture, 2004–present Ferro has advised numerous PhD students in earthquake engineering , structural monitoring , and sustainable materials . He leads multiple EU and nationally funded projects, including DiPreTreat, FORSEES, 3DP_Future, and RECODE, with total funding spanning competitive grants and industrial collaborations. His editorial roles include serving on the boards of Theoretical and Applied Fracture Mechanics , Procedia Structural Integrity , and guest editing for Fatigue & Fracture of Engineering Materials & Structures . He is actively involved in structural consultancy for public and private entities, including seismic assessments for hospitals, bridges, and public housing. His lab and research team focus on material testing , structural simulation , and innovative construction technologies , contributing to national safety standards and infrastructure resilience.
Roman Neunteufel is a dedicated researcher at the University of Natural Resources and Life Sciences, Vienna (BOKU) , affiliated with the Institute of Sanitary Engineering and Water Pollution Control under the Department of Landscape, Water and Infrastructure . His work focuses on critical intersections of water management, climate change, and sustainable infrastructure, with over 15 years of experience in analyzing Austrian water systems. Education: PhD in 2008, Graduate Engineer (2001) Dr. Neunteufel’s research spans water demand modeling, climate change adaptation strategies, benchmarking in water utilities, and household consumption patterns. His recent projects address drought resilience, groundwater sustainability, and innovative heat extraction from water supply systems, reflecting a commitment to environmental policy and engineering solutions. Key trends in his publications highlight collaborations with international experts on cross-border benchmarking, macroeconomic assessments of climate impacts, and guidelines for water loss reduction (e.g., ÖVGW Richtlinie W 63). His work emphasizes data-driven decision-making and integrating scientific insights into Austrian water policy. Scientific Awards: ÖVGW Studienpreis (2009) Leistungsstipendium (1998) Dr. Neunteufel has supervised numerous theses and contributed to strategic asset management frameworks, including the DATMOD-Leitfaden for model creation and calibration. His presentations at global conferences like the IWA World Water Congress and World Congress of Environmental and Resource Economists underscore his influence in shaping sustainable water practices.
Kasper Barslund Hansen is a Research Fellow at the Technical University of Denmark (DTU), affiliated with the Department of Civil and Mechanical Engineering. His work focuses on improving maintenance strategies through configurational approaches, modularization, and data-driven optimization in offshore energy systems. Research Interests: Modularization, offshore oil and gas engineering, maintenance planning, spare parts management, and performance improvement. Publications Trends: Recent studies emphasize offshore energy transitions, end-to-end maintenance performance frameworks, and stock optimization techniques using historical and predictive data. External Collaborations: Active in international networks, particularly in industrial maintenance and offshore energy sectors.
Professor Karl Jenkins is a Professor of Computational Engineering at Cranfield University , where he leads the Centre for Computational Engineering Sciences . His expertise spans Computational Fluid Dynamics (CFD) , Turbulent Combustion , High Performance Computing (HPC) , and Multiphase Flow Modeling . Jenkins has published over 100 papers and received the Gaydon Prize for his contributions to combustion research. His research focuses on reacting flows , turbulence modeling , and compressible multiphase flows , with recent work addressing green hydrogen production , aircraft component segmentation , and virtual reality applications in aviation safety. He has developed high-order numerical methods for shock wave analysis and interface-capturing in unstructured mesh environments . A former Sir Arthur Marshall Research Fellow at Cambridge University, Jenkins combines academic rigor with industrial collaboration , having worked with companies like Rolls-Royce plc , Airbus SE , and Siemens AG . He mentors research students including Yiren Tong and actively contributes to LES/DNS computational frameworks for aerospace and environmental applications .
Jiasi Shen is an Assistant Professor in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology. She leads the HKUST Automated Reasoning and Transformation of Software research group. PhD and Master's from Massachusetts Institute of Technology Bachelor's from Peking University Her research focuses on automating software development through program analysis , program transformation , and active learning . She explores how to systematically introduce safety checks, optimize performance, and enable cross-platform adaptation while maintaining core functionality. Recent work includes: Dynamic graph-based fingerprinting for cryptomining detection Benchmarking LLMs for operating system verification tasks Improving program comprehension via deimplicitization techniques She has received the Distinguished Artifact Award at SLE 2017 and serves on program committees for OOPSLA, Onward!, and SPLASH conferences. Her group supervises multiple PhD and MPhil students while developing systems like Konure (database application modeling) and KumQuat (parallel Unix command synthesis).
Luis Miguel Da Rocha De Matos is an Assistant Professor in the Department of Information Systems and Technologies at Universidade Lusófona, Lisbon, Portugal. He is affiliated with the ALGORITMI Research & Development Center (IDS Group), where he contributes to cutting-edge research in artificial intelligence and machine learning applications in industrial and commercial domains. His research focuses on Machine Learning, Artificial Intelligence, Anomaly Detection, Predictive Maintenance, and Data Preprocessing . He develops intelligent systems for industrial monitoring, worker safety, and marketing optimization, leveraging deep learning, time series analysis, and AutoML techniques. His work bridges theoretical innovation with practical deployment in real-world settings. The analysis of his recent publications reveals a consistent trend toward applying advanced machine learning methods—particularly deep learning and unsupervised models—to solve industrial challenges such as production defect prediction, acoustic anomaly detection, and ergonomic risk prevention. His research spans multiple sectors including manufacturing, automotive, textiles, and digital marketing. His scientific contributions have been recognized with honors including: Best Paper Award at ICCSA 2021 Conference He actively contributes to the academic community as a peer reviewer for Q1 and Q2 journals and participates in scientific committees, session chairing, and workshops. His software contributions include the open-source Python module Cane , widely adopted for categorical data transformation. He also engages in public outreach through keynotes and media appearances. He is involved in major research initiatives such as Factory of the Future, TexBoost, and EasyRide , which focus on digitizing and optimizing industrial processes using AI-driven decision support systems.
Max Finne is an Associate Professor in the Department of Information and Service Management at Aalto University School of Business. His research focuses on operations and service management, with strong contributions to sustainability, circular economy, and collaborative project governance. He actively publishes in leading journals and contributes to pedagogical innovation in higher education. His research interests lie at the intersection of service operations, supply chain sustainability, and organizational collaboration. Key areas include servitization, green supply chains, ecodesign, and performance measurement in complex service environments. He investigates how organizations manage triadic relationships, leverage installed base information, and implement circular economy practices across national contexts. The recent publications show a consistent trend in applying qualitative and theoretical frameworks to real-world challenges in logistics, education, and multinational sustainability projects. His work often employs case study methods and mid-range theory building, particularly in service triads and collaborative governance. There is a strong emphasis on practical implications for middle managers and policy. The Nigel Slack Teaching Innovation Award (2018) The Nigel Slack Teaching Innovation Award (2016) The Nigel Slack Teaching Innovation Award (2015) Max Finne has supervised at least two theses and has been involved in multiple collaborative research projects across Europe, including a visiting position at Warwick Business School (2014–2018). His work is supported by institutional affiliations and academic networks that enable interdisciplinary and international research on sustainability and service innovation. No specific grants are mentioned in the text, but his sustained output suggests active funding. He was a visiting researcher at Warwick Business School from 2014 to 2018, contributing to research and teaching. His work forms part of a broader network focused on sustainable operations and service management, as reflected in co-authorships and collaborative outputs.
Richard Anderson is the Co-Director and Managing Director of the Transport Strategy Centre (TSC) at Imperial College London, leading a multidisciplinary team of 30+ researchers in the Department of Civil and Environmental Engineering. His work focuses on transport benchmarking, urban rail systems, and performance analytics, generating £3.5M+ annual income. Anderson expanded the TSC's global reach to include metros, railways, and airports across Asia and established new consortia for bus and light rail operations. He holds a First Class Honours degree in Civil Engineering and an MSc in Transport from Imperial College London. Anderson's research spans: Transport Economics : Funding models, cost efficiency, and pricing strategies. Urban Mobility : Metro operations, congestion management, and passenger behavior analytics. Infrastructure Optimization : Rail reinvestment, capacity modeling, and lifecycle analysis. Benchmarking Methodologies : Performance measurement frameworks for global transit systems. His publications emphasize data-driven approaches, econometric modeling, and practical solutions for sustainable transport governance. Awards include: President's Award for Excellence in Innovation and Entrepreneurship (2015) Rees Jeffreys Road Fund Bursary (1994) University of Salford Award for Civil Engineering (1994) Anderson advises global transport authorities, leads £3.5M+ annual research initiatives, and sits on committees like the Committee on Transit Management and Performance (2017-2021). The TSC collaborates with 100+ organizations worldwide, driving innovations in low-carbon transport and smart city integration.
Dr. Amy M. Kim is a Professor of Transportation Engineering and Co-Director of URSY at the University of British Columbia (UBC), within the Faculty of Applied Science. She leads research in transportation systems analysis, focusing on multimodal networks, infrastructure planning under climate change, and resource allocation strategies. Her work integrates disciplines such as civil engineering, environmental science, and decision-making frameworks to enhance system adaptability and resilience. Dr. Kim holds a BASc from the University of Waterloo, and MS/PhD degrees from UC Berkeley. She previously taught at the University of Alberta and worked in engineering consulting before joining UBC in 2021. Her research emphasizes wildfire evacuation planning, winter road infrastructure resilience, and airport leakage dynamics. She was awarded the 2022 UBC Killam Accelerator Research Fellowship for her contributions. Her research interests span transportation infrastructure adaptation, air-ground system integration, and optimization under climate uncertainty. Courses taught include CIVL 340 (Transportation Engineering I), CIVL 440 (Transportation Engineering II), and CIVL 586 (Urban Transportation System Analysis). Her Mobility Lab at UBC explores topics such as disaster response logistics, supply-demand modeling, and multi-criteria decision analysis. Key publications focus on highway recovery post-disasters, subarctic traffic patterns, wildfire evacuation networks, and climate-driven infrastructure decisions. She collaborates widely on projects like the Mackenzie Valley Highway resilience assessment and winter road prioritization frameworks in Canada.
Rajesh Krishnan is an Honorary Research Fellow at the Department of Civil and Environmental Engineering, Imperial College London. His work focuses on Intelligent Transport Systems (ITS), traffic data analysis, and urban traffic management. He holds a PhD from Imperial College London and a B.Tech from Indian Institute of Technology Madras. His research spans over 50 publications in areas like traffic sensor technology, real-time data analysis, and public transport optimization. Education: PhD in Civil Engineering, Imperial College London (2003-2008) B.Tech in Civil Engineering, Indian Institute of Technology Madras (1991-1995) Research Interests : Optimization of traffic signal systems for buses and autonomous vehicles Machine learning applications in traffic prediction and anomaly detection Public-private collaboration models for traffic information systems Data fusion techniques using GPS, Bluetooth, and camera sensors Recent work highlights include developing real-time congestion detection algorithms and frameworks for integrating autonomous vehicles into mixed traffic flows. His publications emphasize practical ITS solutions for urban mobility challenges. No student advisees or grants are explicitly listed in the provided materials.
Ning Xiong is a Professor at Mälardalen University, affiliated with the School of Innovation, Design and Engineering and the Division of Intelligent Future Technologies. His research focuses on advanced artificial intelligence, machine learning, optimization algorithms, and cyber-physical systems. He explores applications ranging from digital twin frameworks in distributed systems to predictive maintenance using explainable AI and anomaly detection in timeseries data. His work integrates techniques like federated learning, Bayesian classifiers, and bio-inspired computing (e.g., membrane clustering) to address challenges in smart systems and data science. Key research areas include: Machine Learning & Deep Learning Cyber-Physical Systems Optimization Algorithms Smart Systems & IoT Data Science & Big Data Recent publications highlight advancements in digital twin frameworks for resilient distributed systems, ensemble learning for imbalanced data, and lightweight object detection methods for UAV imagery. His contributions emphasize practical applications in energy grids, predictive maintenance, and industrial automation while addressing theoretical challenges in model explainability and scalability. His research is characterized by interdisciplinary collaboration, combining software engineering, systems architecture, and domain-specific expertise to develop innovative solutions for dynamic environments.
Axel Parmentier is a Lecturer and researcher at the École Nationale des Ponts et Chaussées, where he founded the AI for Air Transport industry research chair with Air France. His work focuses on the intersection of operations research and machine learning, particularly in data-driven combinatorial optimization and stochastic optimization, with industrial applications in air transportation, supply chain, and predictive maintenance. He holds a Ph.D. and has been recognized with awards including the AMIES Dissertation Award (2017) for applied mathematics with industrial impact and the Robert Faure Prize (under 35) from ROADEF. His research also includes contributions to structured reinforcement learning, optimization layers in machine learning, and explainable AI for operational decisions. Awards: AMIES Dissertation Award, Robert Faure Prize Labs/Teams: CERMICS laboratory, AI for Air Transport Chair (collaboration with Air France) Grants/Projects: Continent-scale inventory routing solutions, Renault’s logistics optimization His advising includes students like Victor Cohen, whose work on predictive maintenance was featured on France Culture.
