جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Edge Computing
• +۴ مورد دیگر

Sergio Moreschini is a Postdoctoral Researcher in Computing Sciences, focusing on Artificial Intelligence, Edge Computing, and MLOps. His research explores the integration of AI techniques in microservices, cloud-edge continuum systems, and distributed home automation frameworks. He has contributed to foundational studies such as a Systematic Mapping Study on AI in Microservices Life-Cycle and developed frameworks like Flexconnect for mobile computational offloading. Education: He holds a Bachelor of Science in Technology (2012) and a Higher-Degree in Computing from Università Degli Studi Roma Tre (2016). His work aligns with UN Sustainable Development Goal 4 (Quality Education) through contributions to educational tools and methodologies. Research Interests : Moreschini investigates AI lifecycle management, edge-cloud system orchestration, vulnerability analysis in open-source components, and generative AI applications in software architecture. Key areas include fault-tolerant distributed systems, cognitive cloud continuum frameworks, and MLOps tool ecosystems. Recent Trends in Publications : Recent work emphasizes MLOps adoption challenges, self-organizing edge computing for visual SLAM, and best practices in resource provisioning for cognitive systems. He has explored trade-offs between continuous training and transfer learning in edge environments, and evaluated vulnerability severity metrics in open-source software. Awards : Won the Best Paper Award in 2022 for contributions to industrial edge service scheduling. Data Contributions : Co-created datasets like RARE (cloud-native memory anomalies) and CIVIT (integral microscopy recordings). His collaborative projects include the 6GSoft initiative for edge-cloud continuum systems and the OSSARA tool for open-source component risk assessment. Active in international conferences like IoT and SEAA, he bridges academic research with industrial applications in edge computing and AI infrastructure.

Anni Noraمشاهده پروفایل

استادیار مهمان

• Neuroscience
• Speech Processing
• Developmental Language Disorders
• +۹ مورد دیگر

Anni Nora is a Visiting Assistant Professor at the Aalto University Department of Neuroscience and Biomedical Engineering , where she investigates neurocognitive mechanisms underlying speech and language processing. She earned her Master's degree in Social Sciences University of Helsinki in 2011 and leads the RCF Academy Project (2020-2025) focused on developmental language disorders and dyslexia. Her research integrates magnetoencephalography (MEG) and machine learning to study cortical dynamics in word learning , phonological processing , and memory systems . Active project: Developmental Language Disorder (Principal Investigator, 2020-2025) Key collaborations: University of Jyväskylä , University of Helsinki Her work explores speech processing and phoneme recognition deficits in children with developmental disorders. She has published extensively on cortical tracking mechanisms, temporal lobe function, and auditory cortex abnormalities. Her 2024 article in the Journal of Neuroscience demonstrated impaired speech cortical tracking in developmental language disorder, while her 2021 NeuroImage study linked dyslexia risk to left-hemispheric memory deficiencies . Earlier research (2017-2020) examined right-lateralized word learning , dynamic time-locking , and phonological short-term memory . She has presented findings at conferences since 2014, including 2023-2022 talks on speech processing deficits and 2017-2019 presentations on phonological learning. Media outlets like Aalto University Press (2021) and international news platforms have highlighted her work on nonsense word learning and dyslexia risk .

Ilkka Nissiläمشاهده پروفایل

پژوهشگر

• Biomedical Optics
• Neuroimaging
• Optical Tomography
• +۷ مورد دیگر

Ilkka Nissilä, Ph.D., is a Staff Scientist at the Department of Neuroscience and Biomedical Engineering , Aalto University. With a career spanning over two decades, his work focuses on diffuse optical tomography , near-infrared spectroscopy , and neonatal brain imaging . He served as a Principal Investigator for the Academy of Finland-funded project Multimodal neuroimaging of children (2016–2018) and has collaborated internationally through visiting researcher appointments. Education : Doctoral Degree in Engineering, Helsinki University of Technology (2004) Master's Degree in Engineering, Helsinki University of Technology (1998) Research Themes : Biomedical optics and optical tomography for brain imaging Neurovascular coupling and hemodynamic responses Developmental neuroscience in infants/children Emotional and sensory processing in early life Algorithm development for image reconstruction Integration of NIRS with TMS/MEG/EEG Article Trends : Recent work combines deep learning with diffuse optical tomography for improved brain imaging Studies maternal mental health impacts on child brain development Advances frequency-domain data utilization and 3D anatomical modeling in neonatal studies Activities : Visiting Researcher (2001–2008) at multiple foreign institutions Conference Presentations Media Impact : 2023: AI-Mind General Assembly participation 2022: Co-developed a skin-stroking device for alcohol cravings 2019: Maternal anxiety effects on infant brain covered in Finnish media Collaborations : International partnerships in biomedical optics Interdisciplinary work with pediatric and psychiatric researchers

Marko Virtaمشاهده پروفایل

استاد

• Antimicrobial Resistance
• Environmental Science
• Microbial Ecology
• +۳ مورد دیگر

Marko Virta is a Professor at the Department of Microbiology, University of Helsinki, and leads the Helsinki One Health (HOH) and Institute of Sustainability Science (HELSUS) initiatives. His research focuses on antibiotic resistance in human-impacted environments, spanning Europe, Africa, and Asia. He directs the Doctoral Programme in Microbiology and Biotechnology and teaches life sciences at the university level. Key research areas: Antimicrobial Resistance, Environmental Science, Microbial Ecology, Metagenomics, and One Health. His work integrates molecular microbiology with environmental data to understand resistome dynamics across ecosystems. He employs advanced techniques like epicPCR and metagenomic analysis to study gene transfer and microbial interactions in wastewater, soil, and aquatic systems. Recent publications highlight global surveillance of resistance genes, environmental mitigation strategies, and cross-sectoral health impacts. Scientific awards: Marlene DeLuca Prize (2000), TOYP of Finland Award (2002). Marko Virta actively contributes to media engagement, public outreach, and international collaborations, including the Multidisciplinary Center of Excellence for Antimicrobial Resistance Research (since 2022). His projects address antibiotic resistance in Indonesia, European wastewater patterns, and sustainable solutions for contaminated environments.

• Additive Manufacturing
• Digital Transformation
• Supply Chain Management
• +۷ مورد دیگر

Siavash Khajavi Haghighat is an Assistant Professor at the Department of Industrial Engineering and Management of Aalto University . His research bridges digital technologies with industrial applications, focusing on additive manufacturing, digital transformation, and supply chain optimization. University: Aalto University Department: Industrial Engineering and Management Research Interests: His work explores the intersection of digital manufacturing and operational efficiency, with emphasis on: Industrial applications of Additive Manufacturing (3D printing in construction, automotive spare parts, and clothing) Integration of Machine Learning for waste sorting and process optimization Emerging technologies like Digital Twins and Blockchain for security and IP protection Collaborative innovation models such as Crowdsourcing in mega hackathons Strategic Supply Chain Management and Operations Management in volatile environments Publication Trends: Recent works highlight the transformative potential of human-AI symbiosis in manufacturing, hybrid digital systems , and sustainability through localized production. His studies often employ comparative case analyses and interdisciplinary frameworks. Contact: Email is siavash.khajavi@aalto.fi .

Kaisu Lankinenمشاهده پروفایل

استاد مهمان

• Neuroscience
• Neuroimaging
• Magnetoencephalography
• +۲ مورد دیگر

Kaisu Lankinen is a Visiting Professor at the Department of Neuroscience and Biomedical Engineering at Aalto University . Her research focuses on Magnetoencephalography (MEG) , neural synchrony , and social interaction , combining machine learning and neuroimaging techniques. Education Diplomi-insinööri (Master of Science in Technology), Aalto University, 2011 Tekniikan kandidaatti (Bachelor of Science in Technology), Elektroniikan ja sähkötekniikan koulutusohjelma, 2009 Research Trends : Her recent work explores social conflict resolution through neural alignment, letter processing in sensory cortices, and open-source software development for MEG/EEG analysis. Themes include ecological validity and neural dynamics . Labs & Collaborations : She collaborates with institutions like University of California, Berkeley (2017 visiting researcher) and contributes to tools like HNN-core .

• Materials Science
• Quantum Physics
• Applied Physics
• +۶ مورد دیگر

Arsalan Hashemi Petrudi is a Visiting Professor in the Department of Applied Physics , with expertise in Multiscale Statistical and Quantum Physics . His academic qualifications include a Doctor of Technology (Tekn. toht.) in Technical Physics and a Master's degree in Natural Sciences from Isfahan University of Technology. He contributes to the United Nations Sustainable Development Goal (SDG) for Education through his research and academic work. Research Focus: Density Functional Theory (DFT) , electrochemical reactions, surface science, and water purification technologies. Key Themes: Quantum mechanical modeling of materials, redox-active compounds for energy storage, and interfacial energy manipulation. Recent publications highlight his work on nitrate removal membranes , boron isotope effects , and superhydrophobic surfaces , aligning with applications in environmental engineering and quantum materials. Collaborations span institutions in computational chemistry and applied physics.

• Scanning Probe Microscopy
• Atomic Force Microscopy
• Machine Learning in Microscopy
• +۳ مورد دیگر

Niko Oinonen is a Visiting Professor at the Department of Applied Physics , Aalto University, specializing in scanning probe microscopy and atomic force microscopy (AFM) techniques. His research focuses on integrating machine learning with nanoscale surface analysis to automate tip functionalization, image interpretation, and structure discovery. Collaborations include researchers from Aalto University and international institutions. Research Trends: Recent work emphasizes computational methods for AFM image analysis, automated microscopy workflows, and machine learning-driven molecular reconstruction. Publications span journals like ACS Nano , Computer Physics Communications , and Science Advances . Contact: Email: ext-niko.oinonen@aalto.fi

• Neuroscience
• Biomedical Engineering
• Magnetoencephalography (MEG)
• +۳ مورد دیگر

Silvia Cotroneo is a Doctoral Researcher at the Department of Neuroscience and Biomedical Engineering within Aalto University . Her work focuses on advancing neuroimaging techniques through innovative signal processing methodologies. Specializes in Magnetoencephalography (MEG) data analysis Develops computational solutions for artifact removal in brain imaging Applies machine learning and information theory to neuroscience challenges Recent research explores reproducible extraction of neural responses using independent component analysis and automated artifact correction strategies. Her publications highlight interdisciplinary approaches at the intersection of neuroscience and biomedical engineering.

Mika Aaltoمشاهده پروفایل

پژوهشگر ارشد

• Agent-Based Modelling
• Biofuel Quality Modelling
• Biomass Logistics Systems
• +۵ مورد دیگر

Mika Aalto is a Post-doctoral researcher at the LUT School of Energy Systems, part of Lappeenranta University of Technology in Finland. His research focuses on agent-based modelling, numerical methods in biofuel quality, and biomass logistics systems. He is based in Mikkeli, Finland, and has contributed to projects such as the SairilaSIM circular economy simulation and biosavu biomass availability studies. His work integrates spatial data analysis, remote sensing technologies (e.g., LiDAR, multispectral imaging), and machine learning to address challenges in forest resource management, sustainable energy systems, and circular economy frameworks. Key emphases include optimizing biomass supply chains, evaluating transportation logistics, and enhancing the sustainability of forest-based energy production. Publications highlight advancements in agent-based simulation for biomass terminal operations, lifecycle assessments of supply chains, and the application of computational methods to analyze forest thinning and tree growth. His research bridges theoretical modeling with practical applications, aiming to improve the efficiency and environmental impact of bioenergy systems. No scientific awards or grants are explicitly mentioned in the provided text. Mika collaborates on interdisciplinary projects, such as EcoSairila circular economy facilities and the PUUSTI initiative leveraging digital tools for sustainable wood supply.

• Power Systems
• Renewable Energy Integration
• Microgrid Control
• +۳ مورد دیگر

Edris Pouresmaeil is an Associate Professor in the Department of Electrical Engineering and Automation at Aalto University , Finland. He leads the Renewable Energies for Power Systems research group and has held academic and research roles globally, including at the University of Southern Denmark, University of Waterloo, and Technical University of Catalonia. His research focuses on power electronics for grids, renewable energy integration, microgrid control, and hybrid energy storage systems using green hydrogen and batteries. He is a Senior Member of the IEEE and serves as an Associate Editor for journals such as IEEE Transactions on Smart Grid and IEEE Systems Journal . Notable research interests include grid stability, fault detection, and sustainable energy systems. He has secured grants for projects like ECO-H2 (2024) and Soft4PES (2024), advancing green hydrogen integration and software frameworks for power systems. His recent articles emphasize advanced control techniques (e.g., model predictive control), fault-tolerant converter design, and cybersecurity in power systems. Projects like SolarX (2019) and Unlocking Potentials of Green Hydrogen (2024) highlight his contributions to renewable energy scalability and grid resilience.

• Celiac Disease
• Autoimmunity
• Type 1 Diabetes
• +۷ مورد دیگر

Katri Lindfors is a Professor in Biomedicine with a prominent research profile in autoimmune diseases, particularly celiac disease and type 1 diabetes. Her work spans immunology, gastrointestinal pathology, and environmental determinants of autoimmunity. She is actively involved in translational research, utilizing advanced imaging, stem cell models, and molecular techniques to understand disease mechanisms. Academic Rank: Professor Department: Biomedicine Her research interests are deeply rooted in understanding immune responses in celiac disease, including gluten immunogenicity (especially in oats), intestinal epithelial transport of gliadin, and microvascular changes in the small intestine. She also investigates the early markers of autoimmunity in children at risk for type 1 diabetes, contributing to large-scale studies like the TEDDY Study Group. The recent trend in her publications (2024–2025) shows a strong focus on mechanistic immunology, advanced imaging (e.g., X-ray microtomography), and the use of iPSC-derived models to study disease. Her work integrates molecular, cellular, and clinical perspectives, often in collaboration with leading experts such as Katri Kaukinen and others in Finnish and international consortia. Scientific Awards and Recognitions: No specific awards mentioned in the provided text. Advising and Grants: Katri Lindfors actively supervises students at all levels, including bachelor’s, master’s, and doctoral candidates. She has served as an examiner and supervisor in multiple thesis projects. Her involvement in the Multisociety Celiac Disease Consortium indicates leadership in collaborative research. She also contributes as a reviewer for scientific journals and participates in organizing scientific events. Labs and Teams: She collaborates closely with research groups focusing on celiac disease, intestinal immunology, and stem cell models. Her work is associated with advanced imaging and in vitro modeling labs, particularly those using hiPSC-derived cells and microfluidic systems.

• Transcranial Magnetic Stimulation
• Functional Connectivity
• Neuroscience
• +۷ مورد دیگر

Roberto Guidotti is a Lecturer and Visitor Faculty member in the Department of Neuroscience and Biomedical Engineering at Aalto University's School of Science. His research focuses on the intersection of neuroscience and biomedical engineering, particularly in the areas of transcranial magnetic stimulation, brain network analysis, and neuroimaging data processing. Dr. Guidotti's research interests span several key areas in modern neuroscience and biomedical engineering. He specializes in Transcranial Magnetic Stimulation (TMS) , where he investigates state-dependent stimulation protocols and their effects on brain network dynamics. His work in Electroencephalography (EEG) and Magnetoencephalography (MEG) involves developing advanced signal processing techniques to analyze brain connectivity. He has made significant contributions to Hidden Markov Model applications in neuroscience, particularly for studying brain state transitions during neuromodulation. His research also encompasses functional connectivity analysis , cross-frequency coupling , and the development of multi-locus brain stimulation approaches. Analysis of Dr. Guidotti's recent publications reveals a strong focus on integrating control theory with neuromodulation techniques, advancing multi-locus transcranial magnetic stimulation methods, and developing novel analytical approaches for EEG/MEG data. His work demonstrates a consistent trajectory toward more precise and targeted brain stimulation techniques that account for dynamic brain states. Dr. Guidotti actively collaborates with leading researchers in the field, including Risto J. Ilmoniemi, Vittorio Pizzella, and Laura Marzetti, contributing to the advancement of non-invasive brain stimulation technologies and their clinical applications.

• Electrochemistry
• Catalysis
• Materials Science
• +۳ مورد دیگر

Benjin Jin is a Doctoral Researcher at Aalto University , affiliated with the Chemistry and Materials research group. Their work focuses on advanced electrocatalysis and materials engineering for sustainable energy applications. Research Interests : Electrochemistry Catalysis Nanomaterials for Energy Conversion CO2 Reduction Water Splitting Graphene-Based Composites Publication Trends : Recent works (2024–2025) analyze novel catalysts for oxygen evolution reaction (OER), CO2-to-formate conversion, and graphene-supported bimetallic systems. Techniques include quantum dot engineering, hydrophilic-hydrophobic domain design, and computational modeling with machine-learned potentials. Collaborations : Active in multidisciplinary teams with researchers like Tanja Kallio, Hua Jiang, and Junjie Shi. Contact : benjin.jin@aalto.fi

Cristian A. Galvis Florezمشاهده پروفایل

پژوهشگر

• Quantum Machine Learning
• Quantum Algorithms
• Quantum State Tomography
• +۷ مورد دیگر

Cristian A. Galvis Florez is a doctoral researcher at Aalto University's School of Electrical Engineering, supervised by Professor Simo Särkkä. As part of the QuantLearn project funded by the Research Council of Finland, he explores quantum machine learning algorithms with applications in computational science. His academic journey spans Colombia, Oxford, and Finland, bridging quantum mechanics and machine learning. Education: Master’s in quantum computing, PhD ongoing at Aalto University Research Focus: Quantum state tomography, Gaussian process algorithms, and NISQ device optimization His work integrates quantum computing with machine learning , emphasizing probabilistic modeling and quantum hardware implementation . Recent publications highlight advancements in quantum-assisted regression and state estimation techniques . The QuantLearn project underpins his research, developing algorithms with potential to revolutionize computational domains. His publications demonstrate cross-disciplinary expertise in quantum theory and statistical modeling , leveraging low-rank Gaussian processes for quantum applications.