جستجوی استاد راهنمای دانشگاهی

Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.

• Digital Design and Manufacturing (D2M)
• Sustainable Manufacturing
• Optimization Driven Design
• +۷ مورد دیگر

Pentti Juhana Henttonen is an active Researcher at the University of Helsinki, affiliated with the Swedish School of Social Sciences and the Institute of Humanities and Social Sciences. He serves as a Doctoral Researcher in the Doctoral Program in Human Behavior and works as a project planner, contributing to multiple research initiatives focused on human interaction and psychological phenomena. His research interests span cognitive science with particular emphasis on narcissism, sisu (the Finnish concept of inner strength and perseverance), second language acquisition, and physiological responses during social interactions. Henttonen employs diverse methodologies including physiological measurements, conversation analysis, and experience sampling methods to investigate how individuals process emotions, interact with others, and demonstrate mental fortitude in challenging situations. His publication record shows significant activity with 49 publications spanning from 2009 to 2025, with particular concentration in recent years (2023-2025). His work appears across interdisciplinary journals in psychology, linguistics, and social sciences, demonstrating a trend toward increasingly sophisticated methodologies combining physiological measurements with conversational analysis. Recent publications focus on narcissistic traits and their physiological correlates, the cultural phenomenon of sisu, and second language learner behavior. Henttonen actively contributes to the academic community through peer review services for journals including Scientific Reports, BMC Psychology, and Heliyon. He has organized academic events such as the HSSH workshop on motion energy and pose analysis and the HSSH seminar on VR methodology, demonstrating leadership in advancing methodological approaches in social science research. His research is supported through multiple projects funded by institutions including the Academy of Finland (Suomen Akatemia), with his most recent work focusing on patterns in second language learners' behavior (2023-2024) and previous projects examining narcissism (2019-2023) and neighbor dialogues (2018-2020). His work bridges theoretical psychological concepts with practical applications, as evidenced by his media appearances discussing narcissism and sisu for broader public understanding.

• Cognitive Science
• Narcissism
• Sisu (Finnish concept of inner strength)
• +۵ مورد دیگر

Johanna Virkki is an Associate Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University. Her research focuses on smart textiles, wearable technologies, RFID systems, and their applications in healthcare, assistive communication, and human-computer interaction. She has pioneered projects integrating RFID into clothing and environments for control interfaces, physiological monitoring, and gamified therapies. Key research areas include: Development of e-textiles for AAC (Augmentative and Alternative Communication) RFID-based wearable and furniture interfaces for accessibility Sensor systems for healthcare monitoring and rehabilitation Smart spaces and IoT-enabled environments Her work emphasizes interdisciplinary collaboration, with notable contributions in: Passive RFID sensor platforms for moisture, strain, and physiological signals Co-design approaches involving speech therapists, engineers, and end-users Prototyping wearable devices for children with disabilities and elderly care Recent publications highlight advancements in: Smart furniture and textile-based AAC solutions AI-driven smart spaces and edge-cloud computing Bio-inspired sensors using animal hair and conductive yarns Johanna's research bridges technology and human needs, addressing challenges in healthcare, education, and accessibility through innovative textile and RFID systems.

• Smart Textiles
• RFID Technology
• Wearable Devices
• +۵ مورد دیگر

Ari Huhta is a Professor at the Centre for Applied Language Studies at the University of Jyväskylä. His research focuses on applied linguistics , language assessment , and second language acquisition , with particular emphasis on diagnostic and dynamic assessment frameworks in foreign language education. Active member of the Applied Language Studies and Language Campus follow-up groups Collaborates with institutions like the Finnish National Agency for Education and Research Council of Finland His work integrates language technology and educational evaluation to innovate assessments for L2 writing , reading , and speaking . Recent projects include AI-driven diagnostic tools and automatic speaking evaluation systems. Key collaborations span projects such as Dynamic Diagnostic Language Assessment and ‘Broken Finnish’ , examining societal gatekeeping in language proficiency. His publications address assessment validity , stakeholder involvement , and technological mediation in learning processes.

• Applied Linguistics
• Language Assessment
• Educational Evaluation
• +۷ مورد دیگر

Zheying Zhang is a Lecturer at Tampere University within the Faculty of Information Technology and Communication Sciences , Department of Computing Sciences . She holds a Ph.D. in Computer Science and Information Systems from the University of Jyväskylä (2004) and was awarded a Docent (Adjunct Professor) title in Software Development from the University of Tampere (2013). Education: Ph.D. (2004), Docent (2013) Her research focuses on Requirements Engineering , with specific interests in Requirements Analysis Domain Modelling AI-Assisted Requirements Management Software Quality Assurance Process Improvement Data-Driven Software Development Medical Device Software Current Master's thesis topics include AI for Software Engineering, DevOps pipelines, and cross-disciplinary software ethics. Recent publications highlight trends in AI applications for requirements management, software evolution analysis , and accessibility testing . She actively supervises PhD candidates like Xiaozhou Li and Wenhui Lu, with works spanning open-source projects and medical software quality. Scientific Contributions: 54 research outputs (2003-2025), including 3 2025 conference papers

• Requirements Analysis
• Domain Modelling
• Quality Assurance
• +۱۰ مورد دیگر

Mikko Aro is a Professor of Special Education at the University of Jyväskylä, affiliated with the Department of Education within the Faculty of Education and Psychology. He co-directs the Center of Excellence in Learning Dynamics and Intervention Research (InterLearn), funded by the Academy of Finland (2022–2029). His research focuses on learning disabilities, particularly in literacy and mathematics, and the development of effective interventions. Aro holds a PhD in Psychology from the University of Jyväskylä and has extensive international training in child neuropsychology and neuropsychology. His research interests span typical and atypical learning processes, including the role of cognitive, motivational, and emotional factors in skill acquisition. He has led projects on learning difficulties, intervention efficacy, and assessment practices. Key contributions include studies on reading fluency, math anxiety, and the integration of self-efficacy interventions into educational strategies. Aro’s extensive publications reflect his commitment to advancing understanding of learning disabilities and improving educational support systems. He collaborates with institutions like the Finnish National Agency for Education and the European Commission on projects addressing teacher training, assessment methodologies, and multisite cohort studies. His work emphasizes evidence-based interventions, such as computer-assisted training for struggling readers and strategies to enhance self-efficacy. He advocates for clearer frameworks in educational support, particularly through the Response-to-Intervention (RTI) model. Aro’s research bridges cognitive science, educational policy, and practical classroom applications, aiming to create inclusive and effective learning environments.

• Special Education
• Educational Psychology
• Learning Disabilities
• +۵ مورد دیگر

Kari Systä is a Professor of Software Engineering at Tampere University's Faculty of Information Technology and Communication Sciences. His career spans academia and industry, including 16 years at Nokia Corporation and current leadership in software engineering research. He teaches courses like Continuous Development and Deployment - DevOps and supervises Master's theses. Research Focus: Data-driven software engineering, web/cloud platforms, IoT architectures, energy systems software, and edge computing. Current Projects: LiquidAI (2023-2025) for IoT-Edge-Cloud ML systems; 6GSoft (2023-2026) for 6G software engineering; Microblock (2021-2023) on blockchain micro-credentials; and DELI (2023-2025) for energy research infrastructure. Research Unit: Leads work at TASE (Tampere Software Engineering Research Group). His expertise bridges software engineering theory and practice, with collaborations across Finnish universities and industry. He advocates for integrating AI/ML into software development workflows and optimizing energy systems through programmable edge-cloud solutions.

• Software Engineering
• Web Engineering
• Edge Computing
• +۷ 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.

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

Anna Katariina von Zansen is a University Researcher at the Faculty of Education, University of Helsinki . She leads the AASIS project (Research Council of Finland, 2023–2027), focusing on automated assessment of oral interaction for Finnish L2 learners. Her research explores non-verbal features like gaze and gestures in language testing, integrating educational technology and multimodal analysis . Research Interests : computer-assisted language testing, language assessment, educational technology, multimodality, L2 listening and speaking, Many-facet Rasch measurement, non-verbal cues. Collaborations : Helsinki Institute for Social Sciences and Humanities, AFinLA network, international AI and linguistics teams. Selected Publications analyze automated speaking assessment (Interspeech 2024), multimodal L2 interaction (Ainedidaktisia näkökulmia 2024), and non-verbal communication in language testing (Acta Psychologica 2024). She co-developed the DigiTala tool for oral language evaluation. Scientific Awards : Recipient of the Kari Sajavaaran tunnustuspalkinto (2020) for outstanding applied linguistics research. Her work contributes to language pedagogy and digital assessment frameworks . Contact : anna.vonzansen@helsinki.fi (on parental leave until January 1, 2026; interim contact: Raili Hilden).

• Computer-assisted language testing
• Educational technology
• Language assessment
• +۸ 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.

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

Timo Poranen is a Lecturer at Tampere University's Faculty of Information Technology and Communication Sciences in the Department of Computing Sciences. He focuses on software engineering practices, artificial intelligence applications, and educational technology development. His research spans: AI integration in software development workflows Accessibility and usability in digital platforms Requirements engineering methodologies Collaborative software project management Algorithmic graph theory DevOps and cloud-native systems Recent work examines AI-driven assessment tools, accessibility testing frameworks, and networked educational practices in Finland. He contributes to capstone project guidance and teaches software development fundamentals. Key trends in his 2023-2025 publications: AI-assisted coding patterns Accessibility evaluation metrics Service desk optimization Open-source project dynamics Cloud system monitoring

• Software Engineering
• Artificial Intelligence
• Requirements Engineering
• +۶ مورد دیگر

Alexander Ilin is a Visiting Professor and part-time teacher in the Department of Computer Science at Aalto University, specializing in Artificial Intelligence and Machine Learning. He holds roles in both the Computer Science - Artificial Intelligence and Machine Learning (AIML) research area and the Professors of Practice group. His research focuses on Machine Learning, Reinforcement Learning, and Deep Learning applications, with contributions to areas like neural networks, generative models, and healthcare informatics. Dr. Ilin earned a Doctoral degree in Engineering and Technology from Helsinki University of Technology in 2006. His work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Key projects include the Finnish Center for Artificial Intelligence (FCAI) and the APPIA project on privacy-aware AI applications. His research explores cutting-edge topics such as diffusion models for dynamical systems, reinforcement learning for robotics, and self-supervised forecasting in healthcare. He has led projects like APPIA (2020–2021) and FCAI (2020–2026), securing grants from the Academy of Finland and Business Finland. His work bridges theory and practice, with applications in autonomous systems, nanotechnology, and medical diagnostics. Notable activities include visiting research at the UK Met Office Hadley Centre and presentations at top conferences like NeurIPS and AAMAS. His lab focuses on scalable AI solutions for real-world challenges, emphasizing ethical AI and privacy-preserving techniques.

• Machine Learning
• Artificial Intelligence
• Reinforcement Learning
• +۳ مورد دیگر

Raul Castro Fernandez is an Assistant Professor of Computer Science at the University of Chicago and co-founder and Chief Research Officer at invocate. He originated the concept of 'data ecology,' which frames his research on how data moves through and transforms technological, economic, and social systems—and how we can design interventions to make those ecosystems more valuable, equitable, and resilient. He co-leads the Data Ecology research initiative at the Data Science Institute and co-runs Chicago Data Night, a forum that brings together industry and academia in Chicago. Dr. Castro Fernandez's research centers on data ecology, data discovery, data markets, and data integration. His work develops both theoretical frameworks and practical systems that help organizations find, evaluate, and use data effectively. He approaches data as a socio-technical phenomenon, examining how data shapes our world and how we can shape it back through technical, economic, and social interventions. His research bridges computer science, economics, and social science to address fundamental challenges in data ecosystems. His recent publications reveal a strong focus on applying large language models to data management challenges, particularly for tabular data discovery and integration. He has developed innovative systems like Pneuma for LLM-based tabular data navigation, Solo for natural language data discovery, and Nexus for correlation discovery in spatio-temporal data. His work also addresses critical challenges in data valuation, data markets, and responsible data sharing, with applications across industry and research contexts. SIGMOD Test-of-Time Award (2023) NSF CAREER Award (2024) Sloan Research Fellowship (2025) Dr. Castro Fernandez actively mentors students across multiple levels, advising PhD students including Qiming Wang, Yue Gong, and Zhiru Zhu, as well as numerous master's and undergraduate students. His group has developed influential systems including Data Station (for trustworthy data sharing), Ver (for view discovery), Metam (for goal-oriented data discovery), and Solo (for natural language data discovery). These systems address fundamental challenges in data discovery, sharing, and integration, with applications across various domains. He leads the Data Ecology research group at the University of Chicago, which focuses on developing technical, economic, and social interventions to make data ecosystems more valuable, equitable, and resilient. His team works at the intersection of database systems, machine learning, and economics to build practical systems that address real-world data challenges faced by organizations and individuals, with a particular emphasis on the socio-technical aspects of data sharing and discovery.

• Data Ecology
• Data Discovery
• Data Markets
• +۵ مورد دیگر