Find Academic Supervisors

• Metallurgical Engineering
• Blast Furnace Engineering
• Computational Fluid Dynamics
• +3 more

Debanga Mondal is a faculty member at the Faculty of Science and Technology of Åbo Akademi University, where he conducts research in metallurgical engineering with a focus on sustainable steel production processes. His work contributes to the UN Sustainable Development Goals related to industry, innovation, and infrastructure. Dr. Mondal's research expertise spans multiple domains of industrial process engineering: Blast Furnace Engineering and Optimization Computational Fluid Dynamics for Industrial Applications Numerical Modeling of Gas Flow and Temperature Patterns Process Optimization in Metallurgical Systems Sustainable Production Methods in Steel Manufacturing Image Analysis Applications for Industrial Process Monitoring His publication record demonstrates a consistent focus on improving blast furnace operations through advanced computational methods. Recent research has particularly addressed challenges related to burden descent patterns, gas flow dynamics, and temperature distribution in blast furnaces. Dr. Mondal employs sophisticated modeling techniques including CFD and discrete element methods to analyze and optimize these complex industrial processes, with emphasis on sustainability and efficiency improvements. Dr. Mondal has established productive research collaborations with colleagues across multiple institutions, as evidenced by his co-authored publications. His work has garnered citations in the scientific literature, indicating recognition within the metallurgical engineering community. The research shows particular strength in numerical investigation methods applied to blast furnace engineering problems. His research on sustainable steel production methods aligns with global efforts to reduce the environmental impact of heavy industry while maintaining production efficiency. This work has potential applications for improving the sustainability profile of steel manufacturing worldwide, contributing to cleaner industrial processes and resource optimization in the steel industry.

• High-Temperature Corrosion
• Oxide Compounds
• Oxidation Reactions
• +6 more

Juho Lehmusto, holding the title of Academy Research Fellow at Åbo Akademi University within the Faculty of Natural Sciences and Engineering , specializes in Molecular Science and Engineering Technologies for a sustainable future . His work aligns with UN Sustainable Development Goals, particularly in corrosion science and sustainable energy solutions. Current research focuses on high-temperature corrosion mechanisms, biomass pyrolysis kinetics, and industrial corrosion monitoring Active project: Initiation and propagation of high-temperature corrosion reactions in complex oxygen-containing environments (2022-2027) Recent publications highlight advancements in: Multi-oxidant corrosion analysis using isotopic tracers Comparative studies of Indian and Finnish biomass feedstocks under high-pressure pyrolysis Novel electrochemical methods for low-temperature corrosion monitoring Scientific recognition includes: Academy Research Fellow grant from Finland's Academy of Finland Active in international knowledge exchange through conference presentations, academic collaborations, and seminar leadership, with 15 recorded professional activities between 2022-2024.

Timo SaarinenView profile

Visiting Professor

• Neuroscience
• Speech Perception
• Working Memory
• +9 more

Timo Saarinen is a Visiting Professor at Aalto University's Department of Neuroscience and Biomedical Engineering since 2003. His research bridges neuroscience and biomedical engineering, focusing on cortical dynamics, speech perception, and cognitive-motor integration. Education: Master of Psychology (University of Helsinki, 2015) Research Interests Speech rhythm and cortical entrainment Magnetoencephalography (MEG) applications Brain network connectivity in cognitive tasks Motor cortex dynamics in speech and handwriting Recent publications emphasize AI-driven dementia risk estimation, neural synchrony in naturalistic speech, and motor control mechanisms. His earlier work (2000s) explored IT investment consistency and e-commerce business models. 2015 Scientific Award He has collaborated internationally, with affiliations in Finland, Spain, and Belgium, and contributed to 12 peer-reviewed publications since 2003.

Henrik EbelView profile

Assistant Professor

• Robotics
• Cooperative Robotics
• Model Predictive Control
• +6 more

Henrik Ebel is an Assistant Professor (Tenure Track) in Mechanical Engineering at Lappeenranta-Lahti University of Technology (LUT), specifically within the LUT School of Energy Systems. He joined LUT in 2024 after previously working at the University of Stuttgart's Institute of Engineering and Computational Mechanics from 2016 to 2024. Dr. Ebel's research focuses on the intersection of artificial intelligence, machine learning, and mechanical engineering, with particular emphasis on: Distributed cooperative robotics Model predictive control systems Non-holonomic robot control Data-driven approaches to mechanical engineering problems Automation systems development His research aims to bring cooperative robotics from laboratory settings to real-world applications in Finland, focusing on using multiple simple and cost-efficient robots that collaborate to solve problems rather than relying on single complex machines. He believes automation promotes sustainability through better energy conservation, generation, and storage compared to manual processes. His recent publications demonstrate consistent advancement in cooperative robotics, control systems, and machine learning applications in mechanical engineering. As an educator, Dr. Ebel supervises doctoral students and finds fulfillment in seeing them grow and succeed in their research. He values the human aspect of academia and enjoys teaching as a complement to his research work, noting that honing teaching skills helps him explain research better and pass on important future-oriented knowledge.

Marina WaldenView profile

Senior Lecturer

• Formal Methods
• Software Engineering
• Autonomous Systems
• +7 more

Marina Walden serves as a Senior Lecturer in Information Technology at Åbo Akademi University's Faculty of Natural Sciences and Engineering. Her research focuses on formal methods and software engineering with applications to autonomous systems, particularly in maritime contexts. She leads significant research projects including the Cyber security training cooperation network (2023-2025) and previously served as Principal Investigator for ADVICeS and Digihybrid projects. Dr. Walden's research interests span formal verification, Event-B modeling, autonomous ship navigation, distributed systems, and safety-critical systems development. Her work demonstrates a strong focus on applying rigorous formal methods to real-world engineering challenges, particularly in maritime autonomous systems where safety and compliance with international regulations (COLREGs) are critical. She has developed expertise in multi-vessel navigation systems, role-based workflow modeling, and agile development methods. Her publication record shows consistent output with 125 publications spanning from 1988 to 2024, with recent work focusing on autonomous vessels, formal verification techniques, and workflow modeling. The research trends indicate a progression from foundational work in formal methods toward increasingly complex applications in maritime autonomous systems and cyber security. Dr. Walden actively supervises research, with Yevheniia Yehorova being one documented advisee with whom she co-authored a 2024 publication. She has secured significant research funding through Academy of Finland projects and collaborations with government agencies. Her current research activities include hosting academic visitors and leading the active Cyber security training cooperation network project that runs through 2025, demonstrating continued engagement in both research and academic community building.

Christian Pansch-HattichView profile

Professor

• Marine Ecology
• Ocean Acidification
• Climate Change
• +7 more

Christian Pansch-Hattich is a Professor of Marine Ecology at Åbo Akademi University's Faculty of Natural Sciences and Engineering, specializing in Environmental and Marine Biology. His research explores eco-physiological responses in marine organisms, focusing on interactions across environmental scales from microhabitats to large-scale climate shifts. Expertise : Marine heatwaves, ocean acidification, salinity gradients, and microbial ecology Projects : Active contributor to the SOS: Center for Sustainable Marine Science (2024-2028) Collaborations : Regular collaborator with Baltic Sea Research Institute, Leibniz-Institute, and EU Biodiversa project BaltVib Current work examines: Climate change impacts on Vibrio pathogens Acclimatization mechanisms in benthic ecosystems Interspecific competition in phytoplankton communities Thermal habitat variability effects on marine vegetation Recent publications highlight: 2025: Vibrio prevalence in Baltic salinity gradients 2024: Heatwave acclimation in temperate ecosystems 2024: Eutrophication controls on Vibrio vulnificus 2022: Eco-evolutionary dynamics in microalgal adaptation

Ella PeltonenView profile

Assistant Professor

• Ubiquitous Computing
• Large-scale Data Analysis
• Applied Machine Learning
• +5 more

Ella Peltonen is an Assistant Professor at the M3S research unit, University of Oulu, Finland. She joined the Ubicomp Oulu research centre and 6Genesis research programme in November 2018. Prior to this position, she was a postdoctoral researcher at the Insight Centre for Data Analytics in Cork, Ireland. She completed her PhD in the Nodes group at the University of Helsinki, Finland, working on the Carat project of collaborative energy diagnostics for mobile devices. Her educational background includes: PhD in Computer Science, University of Helsinki, Finland (Carat project on collaborative energy diagnostics) Ella Peltonen's research focuses on ubiquitous computing, large-scale data analysis, and applied machine learning. Her work particularly emphasizes everyday sensing and mobile and wearable devices. She aims to apply machine learning algorithms to large, complex data in real-time systems, with a focus on distributed machine learning and data analysis of smart devices. Her research spans various applications including energy consumption monitoring of mobile devices, wearable technology for measuring physiological signals, and exploring future sensing technologies. Peltonen has expressed interest in how future devices might sense human states, become smarter, and provide greater benefits, potentially through innovations like augmented reality glasses or subcutaneous chips. Analysis of her recent publications shows a strong focus on edge computing, vehicular networks, and sustainable computing systems. Her work bridges the gap between theoretical machine learning approaches and practical applications in transportation, healthcare, and environmental monitoring. Many of her papers address challenges in distributed systems, real-time data processing, and privacy-preserving techniques for edge intelligence. Her notable scientific awards include: Nominated to the list of 10 Rising Stars in Networking and Communications by N2 Women 2017 Selected as one of 50 Finnish Researchers by the Finnish Union of University Researchers and Teachers Nokia Scholarship 2015 and 2016 Jorma Ollila Grant 2018 Young Teacher of the Year 2012 Young Researcher of the Year 2015 Peltonen is actively involved in teaching and mentoring, with a teaching philosophy focused on supporting students' independent learning rather than lecturing from above. She enjoys guiding small groups where she can discuss topics together with students and get to know them personally. As a researcher, she describes herself as precise, detail-oriented, and committed to verifying the correctness of her work carefully. She values the combination of mathematical work with experimental work and creativity in technology, noting that research tasks are diverse and can apply different types of methodology. She is part of international research collaborations with several major universities worldwide, as required by Finnish Academy funding. Peltonen is also an advocate for diversity in technology fields, noting that technology is used by all kinds of people from various backgrounds, yet the producers of technology lack diversity. She has highlighted the importance of encouraging more women to pursue technology careers from an early age.

• Computer Science
• Edge Computing
• Federated Learning
• +4 more

Xiang Su serves as Associate Professor in the Department of Agricultural Sciences and Docent in the Department of Computer Science at the University of Helsinki, while supervising the Doctoral Programme in Sustainable Use of Renewable Natural Resources. Her contact includes email xiang.su@helsinki.fi and phone +358504722824. Her research bridges computer science and sustainability, specializing in edge computing, federated learning, and 5G networks for Industrial IoT and transportation systems. Key applications include energy-efficient base stations, privacy-preserving edge inference, and autonomous vehicle interaction studies, all directed toward sustainable resource management through projects like InterEarth RESET. Recent publication trends show concentrated output in mobile/edge computing (9 articles in 2025), with strong representation in IEEE Transactions on Mobile Computing and Transportation Research journals. Her work demonstrates consistent growth in federated learning applications and transportation system modeling. She currently supervises doctoral students through the Sustainable Use of Renewable Natural Resources programme. Active funding includes the NordForsk project 'Active Nordic Univ Cooperation on Edge Intelli' (2024-2028) as Principal Investigator and the Academy of Finland's €2.8M 'InterEarth RESET' project (2023-2028) as core participant. Research is conducted through university departments and Nordic collaborative networks rather than a dedicated lab, leveraging the University of Helsinki's Biokeskus 3 facilities and cross-institutional partnerships for edge computing and sustainable resource applications.

Martha Arbayani ZaidanView profile

Adjunct Professor

• Environmental Sensing
• Air Quality Monitoring
• Atmospheric Science
• +4 more

Dr. Martha Arbayani Zaidan serves as an Academy Research Fellow at the University of Helsinki's Department of Computer Science and holds the prestigious Docent title (equivalent to Adjunct Professor) at the Institute for Atmospheric and Earth System Research (INAR) and Helsinki Institute of Sustainability Science (HELSUS). Her interdisciplinary work bridges computer science, atmospheric physics, and sustainability science to advance environmental sensing technologies. Her educational foundation includes a PhD in Automatic Control and Systems Engineering from the University of Sheffield (2014), where she developed Bayesian approaches for complex system prognostics, complemented by an MSc in Control Systems (2009) and BEng in Electrical Engineering (2007). Dr. Zaidan's research focuses on environmental sensing systems , particularly drone-based air quality monitoring and machine learning applications for atmospheric data analysis. She investigates critical phenomena including black carbon distribution in Asian megaregions, urban-suburban air quality disparities in East Africa, and aerosol size distribution modeling. Her work emphasizes practical applications for sustainability challenges through advanced computational methods. Her scientific contributions have earned significant recognition, including the competitive Academy Research Fellowship from Finland's Academy of Finland (2023) and the HIIT Research Fellowship (2022), reflecting her leadership in environmental AI research. As an active research leader, Dr. Zaidan directs the Academy of Finland project on AI-enhanced sensing technologies and participates in the large-scale InterEarth RESET initiative. She co-founded the annual EnvSys workshop series, fostering international collaboration in environmental sensing for smart cities. Her supervision record includes mentoring graduate students in computational environmental science.

• Energy Systems
• Smart Grids
• Demand Response
• +3 more

Mikko Nykyri is a Post-doctoral researcher at the Department of Electrical Engineering within the School of Energy Systems at Lappeenranta-Lahti University of Technology (LUT). His research focuses on energy systems with particular emphasis on smart grids, energy communities, and demand response mechanisms. His work bridges theoretical approaches with practical applications in the energy sector, aligning with LUT's strategic focus on energy transition. Dr. Nykyri's research interests center around the intersection of energy systems and digital technologies. He investigates how machine learning, particularly deep reinforcement learning, can optimize energy efficiency in buildings and industrial processes. His work on energy communities explores economic models, blockchain-based settlement systems, and educational approaches through serious games. He also maintains research interests in power electronics, including inverter technologies and semiconductor device characterization. His research demonstrates strong interdisciplinary connections across electrical engineering, computer science, and energy economics. An analysis of Dr. Nykyri's publication history reveals a clear evolution from fundamental power electronics research toward increasingly complex system-level applications. His early work focused on specific technical challenges in power conversion and semiconductor devices, while his recent publications address holistic energy system challenges including community-scale economics, AI-driven optimization, and educational frameworks. This progression reflects the broader energy transition from component-level improvements to integrated system solutions, with particular emphasis on the role of digitalization in enabling new energy paradigms. Dr. Nykyri has established a robust collaborative network, frequently working with researchers including Tommi J. Kärkkäinen, Saku Levikari, and Pertti Silventoinen. His peer review activity for Applied Energy demonstrates his recognized expertise in the field. His research maintains a practical orientation, with multiple studies involving real-world industrial applications and educational demonstrators that bridge academic research with industry implementation needs.