جست‌وجوی استاد و پژوهشگر

Outi Salo-Ahenمشاهده پروفایل

مدرس ارشد

• Pharmaceutical Chemistry
• Molecular Modeling
• Drug Design
• +۵ مورد دیگر

Senior Lecturer Outi Salo-Ahen is affiliated with Åbo Akademi University's Faculty of Natural Sciences and Engineering , Department of Pharmacy. Her research focuses on computational pharmacology, drug design, and pharmaceutical chemistry, particularly targeting chemokine receptors (CCR5/CXCR4) and transient receptor potential channels (TRPA1) for therapeutic applications. Doctor of Pharmacy (2006, University of Kuopio/UEF) MSc in Pharmaceutical Chemistry (2001, UEF) BSc in Pharmacy (1999, UEF) University Pedagogy Modules 1-5 (2012-2015) Her work contributes to UN Sustainable Development Goals through education and pharmaceutical innovation . Recent research trends include: Antimicrobial resistance solutions TRPA1 channel modulation Nanotechnology-enabled drug delivery Multi-target HIV-1 inhibitors 3D printing of biocompatible materials Computational analysis of nucleic acid frameworks She actively supervises doctoral projects, serves on assessment panels, and leads collaborations like Nordic Pharmaceutical Translation and Innovation. Her 60+ publications demonstrate expertise in molecular modeling and drug discovery.

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

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.

• Internet of Things (IoT)
• Industry 4.0
• Digital Twin
• +۳ مورد دیگر

Antti Martikkala is a Postdoctoral Researcher at Tampere University's Department of Automation Technology and Mechanical Engineering. His research focuses on integrating data-driven and model-driven methods for digital-twin engineering, low-cost IoT development, and Industry 4.0 applications. Education: Master of Science (Technology) in Automation Engineering (2012). Research interests include Internet of Things (IoT), Digital Twins, Generative AI in CAD, and Laser-Wire Direct Energy Deposition (LWDED). His recent work explores interoperability of IoT platforms, dynamic route optimization for waste collection, and real-time manufacturing process optimization using AI. Key trends in his publications (2025–2012) span IoT (100% focus), Industry 4.0, CAD, and sustainable manufacturing. Notable collaborations involve A. Daareyni, A. Ylä-Autio, H. Mokhtarian, and I.F. Ituarte. He employs open-source tools and low-cost technologies to democratize IoT systems, with expertise in Arduino-based sensor development, multilayer height detection, and smart textile waste collection optimization.

Lasse Heikkinenمشاهده پروفایل

مدرس ارشد

• Physics
• Applied Physics
• Process Tomography
• +۵ مورد دیگر

Lasse Heikkinen is a Senior Lecturer at the Department of Technical Physics, Faculty of Science, Forestry and Technology, University of Eastern Finland. His work spans applied physics, process tomography, and educational technology, with a focus on innovative teaching methods like flipped classrooms during the pandemic. Current Role: Deputy Head of Department, Senior University Lecturer Research Themes: Electrical impedance tomography for industrial processes, flipped teaching frameworks, and physics education adaptation to remote learning. Recent publications highlight his dual expertise in process tomography (gas-solid flows, pharmaceutical monitoring) and pedagogical innovation (learning analytics, flipped classrooms). He has contributed to educational manuals and toolkits for teacher training. Key Projects: Technology education infrastructure development (2015–2024), pandemic-era teaching adjustments (2022). Collaborations: Active in international process tomography conferences and multidisciplinary teams like the Ameba project.

• Virtual Reality (VR)
• Human-Computer Interaction
• Haptic Feedback Systems
• +۷ مورد دیگر

Roope Raisamo is a Professor in the Department of Computing Sciences at Tampere University, part of the Faculty of Information Technology and Communication Sciences. His research focuses on advanced human-computer interaction, virtual/augmented reality systems, haptic feedback technologies, and their applications in medical, automotive, and assistive technology domains. He leads multidisciplinary projects involving collaboration with industry partners like car manufacturers and healthcare institutions. Key areas of expertise include: (1) Design of immersive XR environments with multimodal feedback integration, (2) Haptic actuator development using smart materials like magnetorheological fluids, (3) Ergonomic interfaces for autonomous vehicles, and (4) Accessibility solutions for seniors and disabled populations. His work bridges theoretical HCI research with practical applications seen in surgical training systems, automotive UIs, and wearable communication aids. Raisamo's research outputs from 2023-2025 show strong focus on: - Sensory augmentation in food perception through XR (2025) - Medical VR applications for surgical planning and tumor visualization (2024-2025) - Haptic-mediating technologies for automotive and industrial interfaces (2023-2025) He has pioneered the use of embedded haptic waveguides in steering wheel interfaces and developed novel textile-based AAC systems for non-verbal communication. Current projects include exploring the medical metaverse for collaborative surgical planning and creating AI-enhanced research tools like TAUCHI-GPT.

Hossein Mokhtarianمشاهده پروفایل

مدرس

• Additive Manufacturing
• Dimensional Analysis
• Modeling and Simulation
• +۴ مورد دیگر

Hossein Mokhtarian is a University Lecturer in Automation Technology and Mechanical Engineering at Tampere University. He holds a Higher-Degree Education qualification from Université Joseph Fourier. His research focuses on Additive Manufacturing (AM), Dimensional Analysis, and modeling frameworks for manufacturing processes. Key areas include functional modeling, materials science, and sustainability in advanced manufacturing. He has contributed to projects like the railway bogie demonstrator using multi-material directed energy deposition and explored AI integration in design processes. Research interests emphasize interdisciplinary approaches, blending graph theory, machine learning, and physics-based modeling. Notable achievements include a Docent title in additive manufacturing (2025) and awards for teaching excellence in DfAM and design optimization. He has organized events like the Finnish Additive Manufacturing (FAME) Symposium 2025 and reviewed for conferences like SEFI. His work addresses challenges in process monitoring, material characterization, and sustainable manufacturing solutions. Education: Higher-Degree Education in Other or Unknown Discipline from Université Joseph Fourier (2015). Awards: Includes innovation grants, teaching excellence, and contest wins for design and AM applications. Collaborations: Global networks in additive manufacturing, with emphasis on Finland's industrial integration.

Pekka Uskiمشاهده پروفایل

پژوهشگر

• Model-Based Definition
• Manufacturing Engineering
• Product Lifecycle Management
• +۳ مورد دیگر

Pekka Uski holds a Master of Science (MSc) in Automation and Mechanical Engineering and is affiliated with Tampere University through a resource agreement. He currently serves as Lead Engineer at Etteplan since October 2018. His research focuses on Model-Based Definition (MBD) applications in manufacturing ecosystems, product lifecycle management, and digital product design. Uski's work emphasizes bridging gaps between theoretical frameworks and practical implementations in mechanical engineering. Education: MSc in Automation and Mechanical Engineering Research interests include optimizing manufacturing processes through MBD, accelerating inspection phases, and resolving challenges in adopting MBD in industrial settings. His studies frequently explore Finnish manufacturing industries and their adoption of digital tools. Collaborations span across academic and industrial sectors, particularly in technical design and lifecycle management. Uski's publications highlight empirical experiments and case studies analyzing MBD's impact on product lifecycle efficiency, one-off production, and manufacturing ecosystems. His work has been peer-reviewed and published in reputable conference proceedings, contributing to advancements in computer-aided manufacturing and sustainable industrial practices.

• Machine Learning
• Cardiomyocyte Research
• Calcium Transient Analysis
• +۵ مورد دیگر

Martti Juhola is a Professor in Computing Sciences at the University of Tampere with extensive research activity spanning over two decades. His academic profile demonstrates significant contributions to interdisciplinary research at the intersection of machine learning, cardiology, and stem cell biology. As evidenced by his supervision of master's students and doctoral candidates, he maintains an active research group focused on computational approaches to medical problems. His primary research interests center on applying machine learning techniques to cardiomyocyte research, particularly using induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) for cardiac disease modeling and drug testing. Additional research streams include biometric verification using eye movement data, medical data mining, and computational approaches to neurological and psychiatric conditions. His work contributes significantly to UN Sustainable Development Goals through healthcare innovation. Analysis of his 246 research outputs reveals a strong focus on cardiac applications of machine learning, with approximately 60% of recent publications addressing calcium transient analysis, drug effects on cardiomyocytes, and cardiac disease classification. His methodology frequently employs advanced machine learning techniques including XGBoost, support vector machines, and deep learning approaches applied to complex medical datasets. Prof. Juhola actively contributes to the academic community through extensive peer review activities for journals including Annals of Biomedical Engineering, Neural Computing & Applications, and Biomedical Signal Processing and Control. His 692 recorded academic activities demonstrate substantial engagement in supervision, examination, and editorial work. His research methodology combines computational approaches with experimental biological data, particularly focusing on calcium transient signals from stem cell-derived cardiomyocytes. This work has established him as a significant contributor to the field of computational cardiology and AI applications in medical diagnostics.

• Robotics
• Human-Robot Collaboration
• Robot Manipulation
• +۸ مورد دیگر

Roel Pieters is a Professor in Automation Technology and Mechanical Engineering, specializing in robotics and human-robot collaboration. His research focuses on advancing automation in industrial settings through innovations in robotic manipulation, sensor-based systems, and cognitive architectures. He has contributed to the development of datasets like the 6DAPose synthetic assembly dataset and the Engine Assembly Dataset, aiding advancements in pose estimation and robotic control. His work aligns with UN Sustainable Development Goals, particularly in fostering innovation and industrial efficiency. Pieters has organized events such as the IEEE Future of Robotics in Finland Seminar and serves as a reviewer for journals like IEEE Transactions on Automation Science and Engineering. His research emphasizes safety, adaptability, and human-centric design in robotics applications, including collaborative tasks and industrial automation. Key themes in his work include multimodal human-robot interaction, cognitive systems for exploration and learning, and the integration of AI with robotics. He explores topics like gesture-based commands, neural curiosity mechanisms, and the personalization of robotics for Industry 5.0. His contributions span both theoretical advancements and practical deployments in manufacturing and service robotics.

• Robotics
• Pose Estimation
• Computer Aided Design
• +۴ مورد دیگر

Kulunu Samarawickrama is a Doctoral Researcher in the Department of Automation Technology and Mechanical Engineering, focusing on advanced robotics and computer vision applications. Their research emphasizes robotic manipulation, pose estimation, and human-robot collaboration in industrial settings. They contribute to the development of synthetic datasets for training robotic systems and sensor-based automation solutions. Research interests include 6D pose estimation, point cloud processing, and vision-based grasping techniques. Their work bridges theoretical advancements with practical industrial applications, such as assembly automation and collaborative robotics. Notable contributions include the 6DAPose dataset for robotic manipulation and studies on sensor-based human-robot collaboration. Their research has been published in conferences like IEEE CASE and ICAR, with peer-reviewed articles in journals like Robotics and Computer-Integrated Manufacturing.

• Control Systems Engineering
• Marine Energy Systems
• Process Optimization
• +۵ مورد دیگر

Jari Böling is a University researcher at Åbo Akademi University, affiliated with the Faculty of Natural Sciences and Engineering in the Department of Process and Systems Engineering. His research focuses on developing technologies for a sustainable future, particularly in marine engineering and control systems with strong connections to UN Sustainable Development Goals. Böling's research expertise spans multiple engineering domains with specialized focus areas including: Distributed control and fault-tolerant control systems Marine energy systems and cruise ship optimization Process engineering applications for sustainability Machine learning integration in industrial control systems Complex system optimization techniques Analysis of Böling's publication trends reveals a strategic evolution from theoretical control systems toward applied sustainable technologies. His recent work demonstrates increasing integration of data analytics and machine learning with traditional control engineering to address environmental challenges in marine transportation. The research shows a clear progression toward practical implementations that reduce energy consumption and emissions in cruise ship operations and other marine applications. Böling actively supervises students, having guided 12 bachelor's theses in energy technology in 2020. His research portfolio includes significant projects funded by Business Finland: DAZE: Data Analytics for Zero Emission Marine (2023-2026) as Co-Principal Investigator INDECS: Integration of design and operation of cruise ship energy systems (2023-2025) as Responsible researcher CASEMATE: Computationally aided systems engineering for marine technology (2022-2025) as Principal researcher CPT: CLEAN PROPULSION TECHNOLOGIES (2021-2023) as Co-Investigator Energy technology development project in Vaasa (2011-2017) as Co-Investigator

Jerker Björkqvistمشاهده پروفایل

استاد

• Sustainable Computing
• Energy-Efficient Algorithms
• Artificial Intelligence
• +۱۲ مورد دیگر

Jerker Björkqvist is a Professor in the Department of Information Technology at Åbo Akademi University, Faculty of Natural Sciences and Technology. His research focuses on sustainable computing, energy-efficient algorithms, and data-driven green transitions in industrial and marine contexts. He leads key projects such as DAZE, WSTAR, and CASEMATE, contributing significantly to zero-emission technologies. His research interests span Sustainable Computing , Energy-Efficient Algorithms for AI , Edge Computing , Marine Technology , and Industrial Sustainability . His work integrates computer science with environmental engineering to support the UN’s Sustainable Development Goals, especially in climate action and responsible innovation. The recent publications reflect a strong trend in applying data analytics and optimization techniques to reduce emissions in maritime and industrial systems. Key themes include digital twins, ultra-reliable communication, and maturity models for sustainability, showing an interdisciplinary blend of computer science, engineering, and environmental science. Jerker Björkqvist actively supervises Master’s students and contributes to academic service through organizing seminars and delivering keynote speeches. He is involved in educational initiatives such as capstone projects and engineering education reform, particularly focusing on the role of AI in practice. He is a principal investigator in multiple externally funded projects including: DAZE (Data Analytics for Zero Emission Marine) – Business Finland WSTAR (Wasa Zero Emission Data Centre) – Academy of Finland CASEMATE – Business Finland FAST – Finnish Software Engineering Doctoral Network These projects involve collaboration with industry and academic partners across Finland. He is associated with research teams and labs focused on sustainable computing and digital transformation, including the WSTAR research group and the DAZE consortium. These teams work on real-world implementations of green IT and marine decarbonization technologies.

• Computer-Aided Design
• Computer-Aided Manufacturing
• Industrial Economics
• +۲ مورد دیگر

Jorma Mettälä is a Lecturer at Seinäjoki University of Applied Sciences (SEAMK), specializing in technical education and industrial management topics. His expertise spans Computer-Aided Design (CAD) Computer-Aided Manufacturing (CAM) Industrial Economics Production Control Human Resources Management . Education: Licentiate of Technology degree . Research trends focus on integrating digital tools into engineering education, particularly CAD teaching methodologies. He has contributed to SEAMK's educational development initiatives, including curriculum design for technical programs. Contact: jorma.mettala@seamk.fi