جستجوی استاد راهنمای دانشگاهی

• Network Science
• Temporal Networks
• Multilayer Networks
• +۵ مورد دیگر

Arash Badie-Modiri is a Visiting Professor at Aalto University's School of Science, Department of Computer Science. His research focuses on temporal networks, multilayer networks, and computational modeling of complex systems. Institution: Aalto University School: School of Science Department: Department of Computer Science Rank: Visiting Professor Email: ext-arash.badie-modiri@aalto.fi His work spans network science, statistical physics, and software development, with particular emphasis on temporal network analysis , multilayer network modeling , and dynamic connectivity estimation . Recent publications highlight contributions to epidemic modeling, crowdsourcing methodological improvements, and open-source software tools like the pymnet library. Collaborations with researchers such as Kimmo Kaski, Jari Saramäki, and Mikko Kivelä reflect his integration into multidisciplinary academic networks. Research outputs demonstrate expertise in temporal network theory , weighted event graphs , and percolation dynamics applied to complex systems.

• large scale learning
• extreme multi-label classification
• deep learning
• +۲ مورد دیگر

Rohit Babbar serves as an Assistant Professor in the Department of Computer Science at Aalto University, Finland, leading a research group dedicated to advancing large-scale machine learning methodologies. His team specializes in tackling computational challenges inherent in extreme classification problems with massive output spaces while ensuring model robustness. His primary research domains encompass large-scale learning systems, extreme multi-label classification architectures, deep learning integration, sequential data processing, and robustness engineering. This work directly addresses industry pain points like computational inefficiency in massive label spaces and model vulnerability to distribution shifts, with applications spanning natural language processing, information retrieval, and recommendation systems. Publication trends reveal a strategic focus on algorithmic innovation for extreme classification, featuring breakthroughs in dynamic sparsity techniques, large language model integration for zero-shot scenarios, and calibration of extreme classifiers. Recent work demonstrates consistent emphasis on computational efficiency through optimized negative sampling, lightweight frameworks like InceptionXML, and specialized metrics for long-tail performance evaluation. Scientific recognition includes: Outstanding Reviewer Award at ACL 2021 Conference (July 2021) for exceptional contributions to computer science peer review As research group leader, Babbar directs collaborative efforts on next-generation classification systems while mentoring emerging scholars in machine learning. His team maintains active partnerships with industry leaders in search and recommendation technologies. The research group operates at the intersection of theoretical machine learning and practical deployment, developing frameworks that balance computational feasibility with predictive accuracy in extreme-scale environments. Current initiatives focus on integrating foundation models with specialized classification architectures while addressing real-world challenges like data sparsity and concept drift.

• Neuroscience
• Digital Phenotyping
• Functional Brain Connectivity
• +۴ مورد دیگر

Ana Triana Hoyos is a Researcher in the Department of Computer Science at Aalto University, Finland, holding a Contingent Worker position (T313) while serving as a Visitor (Faculty) within Professor Jari Saramäki's research group. Her work bridges computational methods with clinical neuroscience through advanced digital phenotyping and neuroimaging techniques. Her primary research investigates functional brain connectivity using fMRI combined with real-world behavioral monitoring, focusing on mental health disorders including depression, ADHD, and psychosis. She pioneers digital phenotyping methodologies through mobile sensing and develops analytical tools like the Niimpy behavioral data analysis toolbox, enabling longitudinal assessment of environmental and lifestyle impacts on neural function. Analysis of her 2019-2025 publications reveals consistent innovation in integrating neuroimaging with real-world behavioral data, particularly through multimodal longitudinal designs. Key contributions include establishing digital biomarkers for mood disorders, mapping connectivity alterations in psychiatric conditions, and developing rigorous methodological frameworks for fMRI preprocessing and behavioral data analysis. Scientific Awards: No awards were documented in the source materials. Advising and Grants: No student advisement records or grant funding details were specified in the available information. She actively contributes to Professor Saramäki's research ecosystem at Aalto University, collaborating with multidisciplinary teams spanning computer science, clinical psychiatry, and neuroscience to advance computational approaches in mental health research.

• Laser Scanning
• Photogrammetry
• Remote Sensing
• +۵ مورد دیگر

Matti Tapio Vaaja is an Assistant Professor at Aalto University's Department of Built Environment, specializing in digital photogrammetry and laser scanning technologies. He also holds an Associate Professorship at Shinshu University's Institute of Mountain Science (Japan) focused on laser scanning applications in forestry. His research spans close-range laser scanning, 3D point cloud processing, environmental change detection, and forest mapping. With over 100 publications and significant contributions to geoinformatics, he coordinates the 4D GEO-IT doctoral education network and supervises 10 doctoral theses in photogrammetry and remote sensing. Notable Achievements: National Open Science Prize (2019) Over 2,700 citations with H-index 24 Contributions to 3D urban modeling, biomass estimation, and smart city development Recent publications demonstrate cross-disciplinary integration of UAV photogrammetry, terrestrial laser scanning, and game engine visualization techniques for urban vegetation monitoring and watershed analysis. His work bridges technical advancements with practical applications in environmental science and urban planning.

Juhi Kulshresthaمشاهده پروفایل

استادیار

• Computational Social Science
• Social Computing
• Misinformation
• +۳ مورد دیگر

Juhi Kulshrestha serves as an Assistant Professor in the Department of Computer Science at Aalto University, Finland, specializing in Computational Social Science and Social Computing with a focus on digital ethics, societal impacts of technology, and policy implications. Her research addresses critical challenges at the intersection of human behavior and digital systems. Her scholarly work investigates misinformation propagation, algorithmic bias in search/social media, and AI's societal consequences through interdisciplinary approaches. Key research themes include affect-driven information seeking, Holocaust representation in AI-generated content, digital divides in AI adoption, and cross-national vaccine misinformation dynamics. She employs large-scale data analysis combining computational methods with social science theories. Recent publications (2022-2025) reveal a strong emphasis on real-world societal issues: analyzing ChatGPT user demographics in Germany, examining visual Holocaust representations across search engines, and studying conspiracy theory ecosystems (e.g., flat earth/9-11 theories). Her collaborative work spans public health, political science, and psychology, frequently appearing in top venues like PLOS One and New Media and Society. Kulshrestha leads the Digital Ethics, Society and Policy (Digital-ESP) research group, which examines ethical frameworks and policy interventions for digital technologies. No information regarding student supervision or research grants is provided in the source material.

• Optics
• Nanotechnology
• Electromagnetic Theory
• +۳ مورد دیگر

Fahime Seyedheydari is a Postdoctoral Researcher at Aalto University's Department of Electrical Engineering and Automation. Her research focuses on advanced optical and electromagnetic phenomena in nanostructures, particularly in the near-infrared regime. Institution: Aalto University Department: Electrical Engineering and Automation Rank: Researcher Her work bridges nanotechnology , optics , and materials science , with a focus on plasmonic effects , core-shell nanoparticles , and light propagation in engineered materials. She investigates how electromagnetic responses of metal-semiconductor-oxide systems can enhance sensor capabilities in the near-infrared spectrum. Recent publications highlight her expertise in anisotropic nanoparticles , dielectric modeling , and photonic applications of semiconductor microinclusions. Her collaborations span computational materials science and experimental photonics. Email: fahime.seyedheydari@aalto.fi Phone: +358503059998

• Urban Planning
• Transportation Engineering
• Smart Cities
• +۴ مورد دیگر

Jenni Partanen is an Assistant Professor at Aalto University, specializing in Built Environment research. Her work focuses on urban planning and computational social science, with particular emphasis on transportation systems, smart city technologies, and sustainable urban development. She is affiliated with the Planning and Transportation research group. Her research explores innovative approaches to urban challenges through computational modeling and data-driven analysis. Key areas include pedestrian safety optimization, wind comfort in public spaces, 15-minute city concepts, and urban vitality enhancement using big data. Recent publications highlight her contributions to computational urban planning, environmental design, and spatial analysis. Her methodological approach combines agent-based modeling, cellular automata simulations, and integration of socio-economic metrics with traditional urban data.

• Materials Science
• Computational Chemistry
• Pyroelectricity
• +۳ مورد دیگر

Kim Eklund is a Doctoral Researcher at the Chemistry and Materials department of Aalto University. Their work focuses on computational materials science, particularly in modeling inorganic materials and ferroelectric systems using hybrid density functional methods. Research Interests: Pyroelectric and ferroelectric materials Density functional theory (DFT) simulations Crystal structure and bonding analysis Electronic and magnetic properties of metal oxides Nanomaterials and thin film characterization Recent publications highlight expertise in materials modeling , with emphasis on ferroelectrics (BaTiO3, KNbO3, PbTiO3), doped carbon nanotubes , and transition metal oxides . They collaborate with researchers like Antti J. Karttunen and Florian Kraus, contributing to fields such as Crystal Growth and Design , Chemistry of Materials , and Inorganic Chemistry .

• Mobile Cloud Computing
• Cloud Computing
• Computer Science
• +۳ مورد دیگر

Zeyu Yang serves as a Researcher in the Department of Information and Communications Engineering at Aalto University, actively contributing to the Mobile Cloud Computing research group. His role focuses on advancing mobile application infrastructure through cloud integration within the university's technical research ecosystem. His primary research domain is Mobile Cloud Computing, specializing in optimizing mobile user experiences via cloud resource allocation. This work intersects with broader disciplines including Cloud Computing, Computer Science, and Wireless Communications, addressing critical challenges in latency reduction, energy efficiency, and scalable mobile service delivery across heterogeneous networks. Within the Mobile Cloud Computing research group, Yang engages in collaborative projects developing next-generation mobile-cloud frameworks. His technical contributions support the group's mission to bridge theoretical research with practical implementations for emerging mobile technologies and edge computing paradigms.

Bhanu Pratap Yadavمشاهده پروفایل

پژوهشگر

• Coding Theory
• Error-Correcting Codes
• Discrete Mathematics
• +۳ مورد دیگر

Bhanu Pratap Yadav is a Postdoctoral Researcher in the Department of Information and Communications Engineering at Aalto University. His work focuses on coding theory and its applications to discrete mathematics. Research interests include: Asymptotic properties of additive cyclic codes Structural analysis of self-dual and LCD codes Negacirculant code constructions Applications of ring theory to coding Error-correcting code optimization Recent publications demonstrate expertise in: Discrete Mathematics Computer Science Information Theory Algebraic Coding

• Machine Learning
• Robotics
• Autonomous Driving
• +۳ مورد دیگر

Jatan Shrestha is a Doctoral Researcher at Aalto University, affiliated with the Department of Electrical Engineering and Automation. His research focuses on applying machine learning techniques to solve complex problems in robotics and autonomous systems. Department: Electrical Engineering and Automation Email: jatan.shrestha@aalto.fi Research Interests: Jatan's work spans machine learning, robotics, and optimization. Key areas include autonomous driving algorithms, multi-agent trajectory planning, visibility-aware navigation, and GPU-accelerated computing for real-time robotic applications. Publication Trends: His research output demonstrates expertise in applying machine learning to hardware optimization (2024), advancing autonomous driving algorithms in dense traffic scenarios (2023), and developing GPU-based optimization frameworks for robotic navigation (2021-2022).

• Artificial Intelligence
• Knowledge Graphs
• Mobile Computing
• +۳ مورد دیگر

Changyi Li is a Doctoral Researcher at the Department of Information and Communications Engineering, Aalto University, specializing in mobile cloud computing and knowledge graph technologies. Their work focuses on enhancing human-machine interaction through advanced natural language processing techniques. Research interests include: Knowledge graph construction and query generation Integration of large language models with database systems Mobile cloud computing architectures Semantic web technologies and data integration Current work explores text-to-Cypher pipelines for knowledge graph interactions, combining AI with information retrieval systems. Publications demonstrate expertise in applying machine learning to structured data querying.

• Signal Processing
• Machine Learning
• Communications Engineering
• +۳ مورد دیگر

Diyako Ghaderyan is a Postdoctoral Researcher in the Department of Information and Communications Engineering at Aalto University, affiliated with the Risto Wichman Group. His research focuses on signal processing and machine learning, particularly in decentralized and federated learning frameworks. Research Interests: Quantile Regression Non-Convex Optimization Distributed Signal Processing Sparse Signal Reconstruction Recent publications address advanced optimization techniques for decentralized and federated networks, including ADMM and proximal gradient methods. His work appears in journals such as IEEE Signal Processing Letters and IEEE Transactions on Signal and Information Processing over Networks .

• Artificial Intelligence
• Machine Learning

Suvi-Tuuli Marjatta Murumäki serves as a Lecturer at Aalto University, a premier Finnish institution renowned for innovation in technology and interdisciplinary research. Her role integrates teaching responsibilities with active participation in the university's academic ecosystem, though specific school or departmental affiliations remain unspecified in available records. Her research centers on Artificial Intelligence and Machine Learning, with particular emphasis on joint learning methodologies that enable collaborative multi-agent systems. This work explores adaptive algorithms for distributed knowledge sharing, aiming to enhance robustness in real-world AI applications across healthcare and autonomous systems domains. She contributes to Aalto University's Joint Learning research initiative, which fosters cross-disciplinary partnerships between computer scientists, engineers, and industry collaborators to address complex challenges in scalable machine learning architectures.

• Software Engineering
• Human Factors
• Diversity
• +۸ مورد دیگر

Fabiana Mendes is a Postdoctoral Researcher at Aalto University's Department of Computer Science . Her research bridges Software Engineering with Human Factors , Gender Diversity , and Privacy Compliance . Research Trends from her 15 most recent publications (2022-2025) show a focus on: Gender Dynamics in tech workplaces Privacy Requirements aligned with LGPD and ISO standards Usability Studies for medical and educational software Cybersecurity Awareness in Brazilian public organizations Value-Based Decision Making in software projects Work-Life Balance in ICT professions Notable Collaborations include researchers from Brazil and Finland, with publications in journals like Information and Software Technology and conferences like IEEE/ACM ICSE and CBSoft. Key Projects involve tools like PT4Researchers for personality data collection and 3SW for web server security measures.