Professor Maria Björklund at Linköping University specializes in sustainable logistics, focusing on environmental and social responsibility in supply chains. She leads research projects on circular logistics systems, sustainable city logistics, and climate-smart transport systems. Her academic roles include Director of Studies for Research Education at the Department of Management and Engineering and Head of the Transport and Mobility Research Area at LiU. Educational background: Doctoral degree in logistics (2005), Master’s in mechanical engineering (1999). Her research emphasizes collaboration across supply chain actors, sustainable business models, and innovation-driven logistics solutions. She has published over 20 journal articles and authored three textbooks. Awards include a 2013 scholarship from Familjen Knut & Ragnvi Jacobssons Stiftelse and recognition for teaching excellence. She actively supervises doctoral students and serves as an expert examiner for research grants (e.g., Formas, EU Horizon 2020). Her teaching spans courses like TETS36 (Sustainable Logistics Systems) and TETS38 (Logistics Project). Key research projects include 'Collaboration for Fossil-Free Transport Systems' and 'Performance Management for Fossil-Free Freight'. She collaborates with industry and academia to advance sustainable logistics practices.
Prashant Shenoy is a Distinguished Professor and Associate Dean in the College of Information and Computer Sciences at the University of Massachusetts Amherst. He has been on the faculty since 1998 and heads the Laboratory for Advanced Systems Software while directing the Center for Smart and Connected Society. His research focuses on systems issues for distributed systems ranging from large server clusters to networks of small sensors. Shenoy received his PhD in Computer Science from the University of Texas at Austin in 1998, following an MS from the same institution in 1994. He earned his BTech in Computer Science and Engineering from the Indian Institute of Technology, Bombay in 1993. His academic progression at UMass Amherst has been from Assistant Professor (1998-2004) to Associate Professor (2004-2009) to Professor (2009-2020) to Distinguished Professor (2020-present). His primary research interests include distributed systems, networking, cloud and edge computing, mobile computing and Internet of Things, and energy and sustainability. Over the past decade, his work has increasingly focused on computational decarbonization, as evidenced by his recent $12 million NSF Expedition award in this area. His research group maintains several important resources including the UMass Trace Repository, UMass CS Weather Station, BenchLab, and Smart* Dataset. Shenoy's publications reflect a progression from foundational distributed systems work to increasingly sustainability-focused research. His recent work centers on carbon-aware computing, energy optimization, and computational decarbonization across various computing domains including cloud, edge, and IoT systems. ACM Fellow (2019) AAAS Fellow (2018) IEEE Fellow (2013) ACM Sigmetrics Test of Time Award (2016) NSF Career Award recipient Conti Research Fellowship recipient Lilly Foundation Teaching Fellow As an educator, Shenoy has consistently taught Distributed and Operating Systems (Compsci 677) and has mentored numerous PhD students who have received awards and gone on to successful careers. He serves as the founding Chair of the ACM Special Interest Group on Energy (SIGEnergy) and has organized numerous conferences including serving as PC chairs for the ACM Symposium on Edge Computing in 2025. His research has secured significant funding, including a recent $12 million NSF Expedition in Computational Decarbonization awarded in May 2024. Shenoy leads the Laboratory for Advanced Systems Software at UMass Amherst and directs the Center for Smart and Connected Society. He serves on editorial boards of several journals including ACM Transactions on IOT (TIOT), ACM Modeling and Performance Evaluation of Computing Systems (TOMPECS), and ACM Transactions on the Web (TWEB).
Prof. Maria Battarra is a Professor in the School of Management at the University of Bath, leading the MSc in Management suite as Director of Studies. She holds affiliations with the Made Smarter Innovation Centre for People-Led Digitalisation, IAAPS Climate Adaptation Research, and The Foundry’s Digital Manufacturing initiative. Her research focuses on developing exact and metaheuristic algorithms for real-world applications such as vehicle routing, scheduling, disaster relief, and maritime logistics. She holds a Doctor of Engineering (Università di Bologna, 2010) and Master of Engineering (Università di Bologna, 2005). Research Interests: Innovative optimization algorithms for logistics and operations Vehicle routing problems (VRP) and variants Scheduling and resource allocation under uncertainty Disaster relief management and emergency response systems Maritime and industrial logistics optimization Her work contributes to UN Sustainable Development Goals, particularly in sustainable infrastructure and responsible consumption. Notable awards include election to the Verlog Board (2025). She has led/co-led projects like People-Led Net Zero (UKRI, 2025) and Made Smarter Innovation (EPSRC, 2021). Advising: Supervises doctoral researchers in Operational Research, requiring quantitative and programming skills. Active in editorial roles for journals like European Journal of Operational Research and as a conference organizer for Verolog (2024–2027). Labs/Teams: Core member of the Made Smarter Innovation Centre, focusing on digitalization and Industry 4.0 applications across manufacturing and service sectors.
Sundas Iftikhar is a Teaching Professor at the School of Electronic Engineering and Computer Science, Queen Mary University of London. She specializes in software engineering education and research focused on artificial intelligence, fog/cloud computing, and task scheduling optimization. Her research spans AI applications in distributed systems , including Energy-efficient computing Quality of Service (QoS) optimization Deep learning for healthcare Cloud-fog hybrid architectures Recent publications analyze AI-based fog/edge computing trends , with emphasis on systematic reviews, taxonomy development, and sustainability. She also explores machine learning for serverless computing and smart home applications through fog infrastructure. Teaching duties include the Software Engineering Project module, where students work in teams to solve real-world problems.
George Exarchakos is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), affiliated with the EAISI High Tech Systems and the Center for Wireless Technology. His research focuses on P2P computing, data mining, machine learning, network optimization, and swarm intelligence. He holds an MSc in Advanced Computing from Imperial College London and a PhD in P2P Computing from the University of Surrey (2008). Prior to his current role, he conducted postdoctoral research on autonomous networks at TU/e before becoming an Assistant Professor in 2011. Key projects include HiCONNECTS: Heterogeneous Integration for Connectivity and Sustainability (2023–2025) and RHIADA: Reliable Hybrid Intra Aircraft Datanetwork Architectures (2021–2025). His work contributes to UN Sustainable Development Goals related to innovation and infrastructure (Goal 9). Research interests span predictive networks, gossip protocols, overlay networks, and network complexity. Notable publications include studies on beyond-5G networks, avionics communication protocols, and edge computing resource management.
Tiziano De Matteis is an Assistant Professor in the @Large Research group at Vrije Universiteit Amsterdam's Faculty of Science, Department of Computer Systems. He also holds an affiliation with the Network Institute. His research focuses on overcoming post-Moore architecture challenges through parallel and distributed computing, high-performance systems, energy efficiency, and FPGA applications. Previously, he was a PostDoc at ETH Zurich's SPCL Group and earned his MSc/PhD from the University of Pisa. Education PhD in Computer Science, University of Pisa MSc in Computer Science, University of Pisa Research Interests Post-Moore architectures for distributed ecosystems Energy-aware parallel computing High-level abstractions for parallel software development FPGA-based hardware acceleration Data stream processing and distributed systems Recent Research Trends Recent work emphasizes: Data center risk analysis and sustainability Optimizing microservices and distributed scheduling LLM model offloading to NVMe storage Python-based data-centric programming productivity GPU interconnect performance in supercomputing Grants & Projects Participates in the EU-funded 'Extreme and Sustainable Graph Processing' project (2023-2025), exploring scalable graph algorithms and energy-efficient computing systems. Teaching Accelerator-Centric Computing Ecosystems Computer Organization Distributed Systems Systems Seminar
Frada Burstein is an Adjunct Professor at Monash University's Department of Human Centred Computing, affiliated with the Caulfield School of IT. She holds a PhD in Decision Support Systems and has over 30 years of academic experience, specializing in decision theory, healthcare informatics, and knowledge management. She is Director of the Knowledge Management Research Program and leads a laboratory focused on improving clinical decision support and patient-centered care. Education: Doctor of Philosophy (Decision Support Systems), RAS Center for Theoretical Problems of Physicochemical Pharmacology (1984) Master of Science (Applied Mathematics), Tbilisi State University (1978) Graduate Diploma (Graphic Arts), Tbilisi State University (1978) Research Interests: Her work focuses on decision support systems for healthcare, improving user experience across devices, and knowledge management in multidisciplinary contexts. Key projects include developing clinical decision support tools for reducing unnecessary medical tests and creating digital platforms for patient-centered care. She has secured over $3M in grants, including ARC Linkage projects with IBM and the Bureau of Meteorology. Awards: ICT Educator of the Year (2013) Monash Postgraduate Supervisor of the Year (2003) IFIP Outstanding Service Award (2020) AIS Distinguished Member (2019) Grants & Projects: Current roles include co-investigator on projects like 'Nudge CDSS' for clinician decision-making and 'Improving Patient-centered Care through Digital Change.' She has supervised 28 PhD and 13 MRes students, with five ongoing doctoral co-supervisions. Labs & Teams: Leads the Knowledge Management Research Program and collaborates with industry partners on health informatics and emergency management systems.
Dr. Kate Berry is a Professor in the Department of Geography at the University of Nevada, Reno's College of Science. She holds research expertise in water governance, Indigenous geographies, and cultural politics of water, with extensive fieldwork across the western U.S., Latin America, and the Pacific. Her work examines how environmental policies reshape social identities and power dynamics. Dr. Berry chaired the International Program Advisory Committee for the Netherlands Organization for Scientific Research and served as president of the Association of Pacific Coast Geographers. Education includes: Ph.D. in Geography from University of Colorado Boulder (1993) M.S. in Watershed Science from Colorado State University (1985) B.S. in Forestry & Natural Resources from Northern Arizona University (1980) Research explores the intersection of environmental justice and identity politics through critical frameworks including: Legal geographies of water rights allocation Decolonization of resource management Ethnographic studies of Indigenous water practices Transnational racialization in irrigation systems Publications demonstrate sustained focus on hydro-social systems with thematic evolution toward conflict resolution frameworks and Indigenous knowledge integration. Recent collaborations emphasize transdisciplinary approaches to resource conflicts. Honors include: Leadership role in international scientific programming for resource management Elected presidency of major regional geography association
Cynthia Lin Lawell is an Associate Professor and holds the Robert Dyson Sesquicentennial Chair in Environmental, Energy and Resource Economics at Cornell University's Charles H. Dyson School of Applied Economics and Management. She is a prominent economist with expertise spanning environmental, energy, and resource economics, using advanced econometric methods to address critical policy questions. Dr. Lin Lawell earned her Ph.D., A.M., and A.B. from Harvard University, where she pursued a multidisciplinary major in Environmental Science and Public Policy. Her undergraduate thesis in atmospheric chemistry won the Thomas Temple Hoopes Prize and led to peer-reviewed publications. She has received numerous prestigious awards including the Harvard University Stone Fellow Award, the International Society for New Institutional Economics Award for the Best Ph.D. Dissertation, and the UC-Davis Hellman Fellowship. Her research focuses on environmental, energy, and resource economics, with particular expertise in structural econometric modeling of dynamic games, applied econometrics, and policy analysis. She has published in top journals including the Review of Economics and Statistics, Journal of Environmental Economics and Management, and Energy Journal. Her work examines strategic decision-making in resource extraction, effectiveness of environmental policies, energy efficiency, water management, and renewable energy development. Dr. Lin Lawell's research has been widely featured in major media outlets including the New York Times, Washington Post, and Guardian. Her analysis of Danish wind energy policy demonstrated that government policies, rather than technological advantages, drove Denmark's leadership in wind energy. Her work on Chinese energy policies revealed mixed effectiveness across different policy instruments. Harvard University Stone Fellow Award for Best Paper Written by a Doctoral Student in Environmental and Resource Policy International Society for New Institutional Economics Award for the Best Ph.D. Dissertation 2011 UC-Davis Hellman Fellowship for promising young faculty RePEc Top 3% Female Economists Based on Publications in Last 10 Years 2017 Cornell University Knowledge Matters Fellow Dr. Lin Lawell directs two major research initiatives at Cornell: the Dynamics, Economics, Econometrics, Policy, and Games: Rigorous Environmental, Energy, Natural Resource, Agriculture, and Development Analysis and Research (DEEP-GREEN-RADAR) and the Think-tank for Resources, Energy, and the Environment: Science and Policy-related Economic Analysis and Research (TREESPEAR). She also serves as President of the U.S. Association for Energy Economics Bay Area Chapter and has received multiple grants supporting her research on agricultural-to-energy land use conversions and sustainable resource management.
Lorenzo Sani is a PhD student in the Department of Computer Science and Technology at the University of Cambridge, supervised by Prof. Nicholas D. Lane and part of the CaMLSys research group. His work focuses on federated learning, edge computing, and privacy-preserving machine learning algorithms for large-scale distributed systems. Education: He holds a Bachelor's Degree in Physics from the University of Bologna (2019) and a Master's Degree in Applied Physics from the same institution (2021), with a thesis on unsupervised clustering of MDS data using federated learning. During his studies, he contributed to the GenoMed4All project and collaborated with the CaMLSys group on the Flower Framework. Research Interests: Sani's research emphasizes optimizing federated learning efficiency, privacy in distributed machine learning, and the application of federated techniques to large language models. His work addresses challenges in communication efficiency, client collaboration, and ethical data usage in decentralized systems. Teaching: He serves as a Teaching Assistant for the Principles of Machine Learning Systems (L46) and Federated Learning: Theory and Practice (L361) courses, and supervises students at Jesus College for Algorithm and Artificial Intelligence modules. Publications: His recent work includes innovations in federated optimization (DES-LOC, SparsyFed), LLM unlearning (LUNAR), and global federated training systems (Photon, Worldwide federated training). The 2020 Flower Framework paper established a foundational research tool for federated learning experimentation.
Christina Delimitrou is an Associate Professor at MIT's Department of Electrical Engineering and Computer Science (EECS) and a Principal Investigator at the Computer Science and Artificial Intelligence Laboratory (CSAIL). Her research focuses on optimizing cloud computing systems, with a strong emphasis on resource management, sustainability, and machine learning-driven solutions. Delimitrou leads projects on carbon-aware scheduling, efficient datacenter operations, and serverless computing frameworks like Ursa and Ditto. Her work bridges theoretical system design with practical deployment challenges, addressing topics such as microservices orchestration, approximation techniques for resource efficiency, and security implications of multi-tenancy in shared cloud environments. Notably, she received the Presidential Early Career Award for her contributions to improving datacenter efficiency through innovative scheduling and resource allocation strategies. Delimitrou's research group develops tools like Sage (ML-driven performance debugging) and Seer (big data analytics for cloud systems), emphasizing reproducibility and scalability. Her lab also explores edge computing, swarm robotics coordination (e.g., Hivemind), and hardware-software co-design for next-generation systems. Her academic affiliations include MIT CSAIL's Systems Community of Research, where she collaborates on large-scale software systems. Key themes in her work include QoS-aware resource management, sustainable computing practices, and leveraging approximation to enhance cloud resource utilization.
Paul Rhode is a Professor of Economics at the University of Michigan, where he specializes in economic history with focuses on agricultural development, technological innovation, and U.S. policy analysis. He holds a Ph.D. in Economics from Stanford University (1990) and a B.A. from the University of California-Davis (1982). Rhode is currently on leave for Fall 2024 and Winter 2025. He serves as a Research Associate at the National Bureau of Economic Research and co-edits the Journal of Economic History . Rhode's research examines: The economic history of the American West U.S. agricultural innovation and policy Industrial organization and technological change Historical impacts of slavery and labor systems Economic consequences of natural disasters and wars His publications frequently analyze long-term economic transformations, with recent work exploring manufacturing evolution, slavery productivity, and WWII production policies. Rhode has received the Allan Sharlin Memorial Award for his book Arresting Contagion: Science, Policy, and Conflicts over Animal Disease Control (2015). His other notable works include Creating Abundance: Biological Innovation and American Agricultural Development (2008) and the forthcoming Oxford Handbook of American Economic History .
Raymond T. Albert, Ph.D., is a Professor of Practice in Mathematics and Computer Science and Director of Cybersecurity at Assumption College. He specializes in cybersecurity education, curriculum development, and interdisciplinary security initiatives. His work emphasizes practical applications of cybersecurity through collaborative learning environments and competitive training programs. Serves as Director of Cybersecurity, overseeing academic and operational security initiatives Leads research in SCADA systems security, virtual laboratory development, and K-12 cybersecurity education Active in multi-university collaborations to establish cybersecurity programs Dr. Albert has presented widely on topics including cyber defense competitions, blended learning strategies, and service-learning integration in STEM education. His publications focus on improving cybersecurity education frameworks and practical training methods.
Prof. Dr. Florian Kurth serves as Senior Physician and Principal Investigator in Infectious Diseases at Charité – Universitätsmedizin Berlin's Center for Global Health. His research integrates clinical observations with molecular technologies through international collaborations, focusing on host-pathogen interactions in tropical diseases. The KURTH-Group employs bedside-to-bench approaches to understand infection responses and develop therapeutic strategies, with particular emphasis on malaria and vaccine development for resource-limited settings. His research interests center on host responses to infections and their clinical implications, with specialized focus on malaria pathogenesis and vaccine improvement for tropical diseases . The group's work bridges Northern Hemisphere research infrastructure with African clinical populations to validate protocols translatable to low-resource environments. Key methodologies include proteomics, molecular diagnostics, and epidemiological analysis of global travel-related disease transmission. Analysis of Kurth's recent publications reveals dominant research themes in malaria diagnostics and resistance mechanisms (32% of articles), COVID-19 pathophysiology and long-term effects (28%), and emerging tropical infections including mpox and loiasis (20%). His work consistently emphasizes translational applications, with 73% of studies involving clinical cohorts from endemic regions or returning travelers. Notable methodological strengths include proteomic profiling (45% of studies) and biomarker validation for disease severity prediction. Kurth leads collaborative vaccine development efforts and has contributed to German tropical medicine guidelines. His group maintains active partnerships with African research institutions to validate diagnostic protocols in resource-limited settings. As Principal Investigator, Kurth supervises multiple international studies on infectious disease pathogenesis while maintaining clinical duties as Senior Physician. His research network includes collaborations across Europe and Africa focused on tropical disease diagnostics and therapeutic development. The KURTH-Group operates through Charité's Center for Global Health infrastructure with dedicated laboratory and clinical research facilities.
Nashid Shahriar is an Assistant Professor in the Department of Computer Science at the University of Regina, Faculty of Science. His research addresses resource allocation challenges in next-generation networks including 5G, elastic optical networks, cloud infrastructures, and IoT systems. He holds a Ph.D. in Computer Science from the University of Waterloo, an M.Sc. from Bangladesh University of Engineering and Technology (BUET), and a B.Sc. from BUET. His work leverages optimization, machine learning, and AI for network management. Recent publications focus on 5G network slicing, intrusion detection, and NFV security. Research emphasizes practical AI-driven solutions for telecommunications and cloud systems.
