Find Academic Supervisors

• Optimization
• Operations Research
• Renewable Energy Systems
• +3 more

António Ismael Freitas Vaz serves as Associate Professor with Habilitation at the School of Engineering, University of Minho, and holds a Senior Researcher position at the ALGORITMI Research Centre. As a core member of the SEOR (Systems Engineering and Operations Research) R&D Group, he directs research in mathematical optimization methodologies with applications spanning energy systems, additive manufacturing, and biomedical engineering. His institutional profile includes verified metrics: h-index 17, 1,505 citations, and 41 publications including 34 in Q1/Q2 journals. His research program centers on developing advanced optimization frameworks including multi-objective, derivative-free, and semi-infinite programming techniques. Key application domains feature renewable energy integration (demand-response co-optimization, cost-effectiveness analysis), 5-axis 3D printing (curved layer path planning, build orientation optimization), and medical diagnostics (automated tumor detection in wireless capsule endoscopy). Methodological innovations focus on particle swarm optimization, DC programming, and gradient descent complexity for complex constrained problems. Analysis of his 15 most recent publications (2018-2022) reveals three dominant research thrusts: energy systems optimization (33% of output), additive manufacturing (33%), and medical imaging (13%), with foundational optimization theory comprising the remainder. This distribution demonstrates strategic application of core methodologies to high-impact engineering challenges, particularly in sustainable energy transition and advanced manufacturing. The consistent publication in top-tier venues like Renewable and Sustainable Energy Reviews and Applied Energy underscores disciplinary influence. Scientific Awards: No specific awards, fellowships, or medals were documented in the provided profile information. Regarding academic advising, the source material contains no listings of PhD or Master's students supervised. The funding section explicitly indicates zero recorded projects ("Fundings (0)"), suggesting either institutional management of grants outside individual reporting or incomplete profile documentation. His h-index and publication volume imply significant research leadership despite absent grant details. As an integral contributor to the SEOR R&D Group at ALGORITMI, Vaz participates in a cross-disciplinary research ecosystem focused on operational research applications. The group maintains industry partnerships in energy, manufacturing, and healthcare sectors, facilitating translation of optimization algorithms into practical solutions for industrial partners and public administration through the Centre's thematic lines.

• Multi-objective Optimization
• Nonlinear Optimization
• Evolutionary Algorithms
• +4 more

Lino António Antunes Fernandes Costa is an Associate Professor (with tenure) at the Department of Production and Systems, School of Engineering, University of Minho, Portugal. He conducts his research activities at the ALGORITMI R&D Centre as a member of the Systems Engineering and Operational Research (SEOR) research group. His academic credentials include a PhD in Production and Systems Engineering, an MSc in Informatics, and a DEng in Informatics and Systems Engineering. These qualifications form the foundation for his interdisciplinary research bridging engineering, computer science, and mathematical optimization. Dr. Costa's research focuses on multi-objective optimization, nonlinear optimization, evolutionary algorithms, and applied statistics. His work demonstrates significant application to real-world industrial problems, particularly in manufacturing optimization, agricultural technology (with emphasis on olive cultivation), emergency response systems, and quality control. His methodological approaches often combine traditional optimization techniques with modern machine learning and artificial intelligence methods. His publication record shows a clear evolution toward Industry 4.0 applications, with recent work emphasizing the integration of optimization techniques with smart manufacturing systems, agricultural technology, and emergency management. His research demonstrates strong interdisciplinary connections between operations research, computer science, and domain-specific applications in manufacturing and agriculture. h-index: 17 Total Publications: 126 Total Citations: 1,193 Q1/Q2 Journal Publications: 40 Dr. Costa serves as a regular reviewer for prestigious journals including IEEE Transactions on Evolutionary Computation, Evolutionary Computation, IEEE Intelligent Systems, and European Journal of Operational Research. He has contributed to over 40 international scientific events as a program committee member, including major conferences such as ACM GECCO, IEEE CEC, and EMO. His professional activities extend to project-based learning initiatives in industrial engineering education, demonstrating his commitment to both research and teaching excellence. His laboratory work centers around the ALGORITMI Centre's SEOR research group, where he collaborates on developing optimization frameworks for distributed manufacturing systems, agricultural technology applications, and emergency resource management. Current projects include applying multi-objective optimization to olive cultivation challenges and developing intelligent systems for firefighting resource allocation.

Ernani DamascenoView profile

Researcher

• Business Intelligence
• Data Mining
• Grid Computing
• +3 more

Ernani Damasceno is an Associate Researcher and PhD candidate at the University of Vigo, Spain, specializing in Intelligent and Adaptable Software Systems. His research develops computational solutions for business failure analysis using Business Intelligence and Data Mining methodologies. Academic background: PhD in Intelligent and Adaptable Software Systems, University of Vigo (2020-present) Master of Management Consultancy, Porto Accounting and Business School (2017) MBA in IT Management, Anhanguera University of São Paulo (2014) Bachelor of Information Systems, Atenas College (2012) Bachelor of Arts in English, Federal University of Minas Gerais (2005) Research focuses on applying Grid and Utility Computing to business intelligence systems for failure detection and resolution. His work integrates distributed computing with operational business analytics to create robust decision-support frameworks, with particular emphasis on translating computational tools into practical corporate solutions for failure prevention and system recovery.

• Sustainable Tourism
• Recreational Trail Management
• Environmental Conservation
• +5 more

Dr. Goda Lukoseviciute is a Researcher at the University of Algarve's Centre for Tourism, Sustainability and Well-being (CinTurs), specializing in sustainable trail tourism and recreational management. Holding a PhD in Tourism with distinction from the University of Algarve's School of Management, she integrates environmental conservation with economic development through innovative research on trail-related recreation. Her research focuses on sustainable trail development , economic impact analysis , and community engagement in tourism contexts. Key contributions include the application of Recreation Opportunity Spectrum frameworks to European Atlantic trails, machine learning models for visitor flow prediction, and income multiplier assessments for coastal tourism economies. Her work bridges academic research with practical policy applications, particularly in Portuguese coastal regions. Dr. Lukoseviciute's publication record demonstrates consistent output in high-impact journals including Journal of Outdoor Recreation and Tourism and Tourism Management Perspectives , with recent work emphasizing digital technologies in trail management and seasonal tourism strategies. Her research shows strong interdisciplinary connections between tourism economics, environmental science, and data analytics. Emerging Trail Leaders Scholarship (American Trails, 2022) FCT PhD Scholarship recipient (2020-2024) Multiple Erasmus+ and COST Action research grants Competitive short-term scientific mission awards Recognition for 'Very good with distinction' PhD defense (2024) As an active researcher, she leads the FCT-funded 'Trail-related tourism and sustainable territorial development' project (2021-2025) while collaborating on EU initiatives including TrailGazersBID and MARE NOSTRUM. Her work with CinTurs research center emphasizes transdisciplinary approaches to sustainable tourism challenges, regularly engaging stakeholders from local communities to European policy bodies. Dr. Lukoseviciute directs research activities through the Centre for Tourism, Sustainability and Well-being, focusing on practical applications of sustainable tourism frameworks. Her team develops tools for trail classification, economic impact assessment, and visitor experience optimization that directly inform regional management practices in Portugal's coastal areas.

• Meteorology
• Climatology
• Atmospheric Sciences
• +5 more

Margarida L. R. Liberato is an Associate Professor at the University of Trás-os-Montes and Alto Douro in Vila Real, Portugal, where she works within the School of Sciences and Technology. Her academic career focuses on meteorology and climatology, with particular expertise in extreme weather events and their societal impacts. Dr. Liberato earned her PhD in Physics from the Faculty of Sciences at the University of Lisbon in 2008. Her doctoral work laid the foundation for her subsequent research in atmospheric sciences and climate dynamics. Her research interests span several critical areas of climate science, with a particular emphasis on: Analysis of extratropical cyclones and their impacts on the Iberian Peninsula Drought monitoring and assessment across multiple regions including the Amazon Basin and Iberian Peninsula Moiré transport mechanisms and their role in precipitation patterns Extreme weather event characterization and ranking methodologies Impacts of climate extremes on infrastructure, particularly power systems Application of crowdsourcing techniques for weather event annotation Dr. Liberato's publication record demonstrates a consistent focus on understanding climate extremes and their societal implications. Her work bridges fundamental atmospheric science with practical applications for risk assessment and infrastructure resilience. Recent research shows increasing emphasis on interdisciplinary approaches, connecting meteorology with energy systems, forest management, and water resources. She has been actively involved in numerous research projects and collaborations: Principal investigator and team member for multiple Portuguese Foundation for Science and Technology grants Active participant in European COST Actions including MEDCYCLONES (CA19109) and DAMOCLES (CA17109) Collaborator on international projects studying Mediterranean cyclones, compound climate events, and ocean syntheses Extensive peer review activities for leading climate and meteorology journals Dr. Liberato's work demonstrates significant impact in both academic and practical domains, with research that informs climate adaptation strategies and infrastructure planning in Portugal and beyond.

• Renewable Energy Forecasting
• Probabilistic Forecasting
• Collaborative Forecasting
• +2 more

Carla Silva Gonçalves is a Postdoctoral Researcher at the Centre for Power and Energy Systems, INESC TEC, Portugal. She holds a Ph.D. (2021) and M.Sc. (2015) in Applied Mathematics from the Faculty of Sciences of the University of Porto (FCUP), and previously served as an Invited Auxiliary Professor at the University of Porto for two semesters. Education: Ph.D. in Applied Mathematics, FCUP, 2021 M.Sc. in Applied Mathematics, FCUP, 2015 Her research pioneers probabilistic and collaborative forecasting methods for renewable energy systems, with critical innovations in data privacy preservation and monetization frameworks. She develops incentive mechanisms to overcome data-sharing barriers in energy forecasting through auction-based markets and blockchain architectures. Recent publications reveal a cohesive trajectory toward privacy-aware collaborative forecasting, emphasizing blockchain-integrated data markets and interpretable regression models. Her work bridges theoretical advances in spline LASSO methods with practical industry applications in wind and solar forecasting, published in Q1 journals like IEEE Transactions on Sustainable Energy. Advising and Projects: Supervised Tiago Guedes Teixeira's 2024 thesis on energy data markets at UP-FCUP H2020 Smart4RES project contributor (until 2022) Current participant in ENERSHARE and GREEN.DAT.AI European projects As core member of INESC TEC's Power and Energy Systems Centre, she maintains active industry collaborations with REN, EDP Renewables, RTE, and EDP Gestão on real-world forecasting implementations.

Rosalind EggoView profile

Professor

• Infectious Disease Dynamics
• Mathematical Modeling of Infectious Diseases
• Epidemiology
• +5 more

Professor Rosalind Eggo is a Professor of Infectious Disease Dynamics at the London School of Hygiene & Tropical Medicine (LSHTM), where she works within the Department of Infectious Disease Epidemiology and Dynamics in the Faculty of Epidemiology and Population Health. She leads research at the intersection of mathematical modeling, infectious disease dynamics, and public health policy. Her work spans multiple research centers including the Centre for Mathematical Modelling of Infectious Diseases, Health in Humanitarian Crises Centre, and Global Health Economics Centre. Professor Eggo's research focuses on mathematical modeling of infectious disease transmission, vaccine impact assessment, and health inequalities. Her work addresses critical questions in epidemic preparedness, vaccine policy, and healthcare system responses to infectious disease threats. She has made significant contributions to understanding the transmission dynamics of influenza, norovirus, pneumococcal disease, and SARS-CoV-2, with particular attention to vulnerable populations and humanitarian settings. Her recent publication portfolio demonstrates a strong emphasis on mathematical modeling approaches to evaluate the health and economic impact of vaccination strategies across various settings, from national health systems to humanitarian crises. Her work frequently leverages large-scale healthcare data through platforms like OpenSAFELY to address pressing public health questions related to disease transmission, healthcare utilization, and health inequalities. Member of SAGE Subgroup on COVID-19 and Ethnicity (2020-2021) Member of SAGE Task & Finish Working Group on COVID-19 and Children (2020-2021) Member of SPI-M-O (2020) Member of WHO Technical Advisory Group on COVID-19 and Educational Establishments (2020) Professor Eggo leads multiple research grants funded by major organizations including the Medical Research Council, National Institute for Health Research, World Health Organisation, and Bill & Melinda Gates Foundation. Her current research portfolio addresses critical areas such as health inequality from infectious disease dynamics, epidemic preparedness toolkits, winter pressures in primary care, and next-generation influenza vaccines. She also leads the Women in Infectious Disease Modelling initiative at LSHTM.

Ovidiu Petru StanView profile

Associate Professor

• Dependability
• Cyber-Physical Systems
• E-Health
• +2 more

Ovidiu Petru Stan serves as Associate Professor in the Department of Automation at the Faculty of Automation and Computer Science, Technical University of Cluj Napoca, Romania, while concurrently directing the institution's Socio-Economic Relations Department since joining the university in 2008. His research spans critical interdisciplinary domains including Dependability engineering, Cyber-Physical Systems integration, E-Health applications, Internet-based Information Management, and distributed Cloud-Fog-Edge Computing architectures. This portfolio demonstrates a consistent focus on resilient systems design for healthcare technology and infrastructure-critical computing environments. Professional Recognition: Senior IEEE Member Dr. Stan has significantly contributed to academic discourse through organizational leadership in seven IEEE conferences and one IFMBE conference since 2012, though specific student mentorship activities or research funding details remain unreported in the source material.

Myoungsoo JungView profile

Professor

• Computer Architecture
• Operating Systems
• Solid State Drives
• +6 more

Myoungsoo Jung is the KAIST Endowed Chair Professor and Full Professor at Korea Advanced Institute of Science and Technology, holding primary appointment in the School of Electrical Engineering with additional affiliations in the School of Semiconductor System Engineering, Graduate School of AI Semiconductor, Graduate School of System Architect, and Graduate School of AI. His research focuses on cutting-edge computer architecture and operating systems with specialization in memory and storage systems. Professor Jung's research interests span computer architecture, operating systems, flash memory, solid-state drives, non-volatile memory, file systems, parallel processing, and heterogeneous computing. He has pioneered work in CXL-based memory expansion, computational SSDs, and memory disaggregation technologies that are transforming modern data centers and AI infrastructure. His recent publications demonstrate significant advancements in CXL-driven architectures, computational storage, and memory systems. The research trends show increasing integration of storage and memory technologies with AI workloads, particularly in large-scale graph processing, federated learning, and billion-scale data management. His team's work frequently appears in top-tier venues including ISCA, HPCA, SOSP, and USENIX ATC. Hall of Fame, IEEE/ACM ISCA (2024) Digital Innovation Award from Minister of Science and ICT (2024) CES Innovation Award Winner, CXL-Enabled AI Accelerator (2025) Korea Innovative Startup Award, Ministry of Science and ICT (2025) Samsung Best Paper Award Winner (Grand Prize) (2022) Professor Jung has successfully advised numerous PhD students including Miryeong Kwon (recipient of KAIST Outstanding PhD Dissertation Award) and Donghyun Gouk. His CAMEL research lab has secured over $13M in funding from sources including DOE, NSF, and Korean government agencies. The lab maintains strong industry partnerships with Samsung, SK Hynix, and Panmnesia, focusing on translating research into practical systems. Current projects include CXL-based memory expansion, computational SSDs for AI acceleration, and next-generation storage architectures for hyperscale data centers.