Martha Arbayani Zaidan is an Academy Research Fellow and a Data Scientist working at the Department of Computer Science (CS) and the Institute for Atmospheric and Earth System Research (INAR) as well as InterEarth initiative. His research interests are in artificial Intelligence, health monitoring technologies, intelligent control systems, systems identification, and various applications including bio-medical robotics, twin-rotor dynamics, aircraft gas turbine engines, renewable energies, applied physics, atmospheric and environmental sciences as well as other intelligent engineering systems.
Abdur Rahman is a Doctoral Researcher dedicated to advancing machine learning and deep learning models for the analysis of big scientific data. His primary focus revolves around leveraging AI techniques for processing time-series measurements gathered from research infrastructures, with a particular emphasis on data from SMEAR stations. With a background in Statistics and Applied Mathematics, Abdur’s passion for AI and environmental monitoring drives his commitment to advancing knowledge in these interdisciplinary fields.
Hasan Sarwar is a Doctoral Researcher working on AI for enhancing sensing and scientific instrumentation. Mainly his current focus is on the automation of Stations for Measuring Ecosystem-Atmospheric Relation (SMEAR stations). His research interests include machine learning, Internet of Things (IoT), Artificial Intelligence, Intelligent systems and environmental sensing. He also has a keen interest in mobile application development and Virtual Reality (VR) systems
Samuel Chua is a Doctoral Researcher at INAR, focusing on the measurement of air quality and atmospheric aerosols. His research interests include hydrology, glaciology, aerosol science, and machine learning methods. He has conducted fieldwork in diverse environments, from Southeast Asia to Greenland.
Jani Kuurasuo is joining as a Doctoral Researcher in applying AI for drone-based measurements data especially through hyperspectral cameras. He almost completed his work as a Research Assistant focusing on developing image processing methods on the images obtained from a hyper-spectral camera installed on a drone. He will continue his Master thesis on developing Deep learning methods for the classification of hyperspectral imagery of pine trees.
Dominik Rohal is joining as a Doctoral Researcher in Edge Intelligence to real-time applications of computer vision and natural language processing for environmental monitoring and analytics. He is passionate about bridging research and practical problems and aims to further develop his expertise in AI-related fields during his future PhD studies. Currently, he contributes to the software development aspects of projects at Atmospheric and Earth System Research (INAR). His recent work has focused on the development of IoT devices based on Raspberry Pi, an IoT data platform, and a data visualization application.
Yangyang Wang is a Master's student majoring in Computer Science. Currently, she is focusing on an IoT project involving sensors and the Raspberry Pi. She has previously worked at the WiFi company TP-Link on the Ethernet Tester project and the Wireless Communication Test System (WCTS) project. Her interests include machine learning, large language models, and IoT.
Sergei Panarin is a Master's student majoring in Data Science. Currently, he is focusing on a Data Science project involving combining sensors and LLMs into a single pipeline. His goal is to turn this project into the foundation for a Master's thesis. Earlier he had worked at Valmet as a part of the Database team and Nokia as a part of the DevOps R&D team. His interests include machine learning, data engineering and LLMs.
Marianna Ojanen is a Master's student majoring in Computer Science, specializing in algorithms. She is currently working on her master’s thesis, focusing on multivariate change point detection, inspired by her internship on a collaboration project between the University of Helsinki and Nokia Bell Labs. Her research interests span machine learning, data engineering, and data analysis.
Golam Wasy Arnob is a Master’s student majoring in Computer Science, specializing in Software. During his internship, he contributed to a joint project between the University of Helsinki and Nokia Bell Labs, where he focused on analyzing various data normalization techniques. Based on this foundation, he is now doing his Master’s thesis, where he is further exploring adaptive data normalization methods, applying these techniques to diverse datasets related to telecommunications and IoT sensors. His commitment to refining data preprocessing makes him a valuable contributor in data-driven applications.
Matias Brax is a Master's student majoring in Computer Science. He is currently working on his Master’s thesis, which focuses on processing and analyzing voice and video data on cloud platforms. This work is part of EduSense, a collaboration project between the University of Helsinki and Microsoft. His previous experience in software engineering within accounting sector supports building machine learning pipelines on the project, following MLOps principles. His research interests include machine learning, data analysis, cloud computing, and health & well-being applications.
Advisors are senior faculties who provide general advice about the research vision of this group.
Associate members are key research personnel with whom the leaders of this group collaborate closely.
Research visitors are researchers who are visiting (presently) this group for collaboration.
Omar Al-Jaghbeer is a doctoral researcher specializing in carbon emission modeling from urban traffic as part of the AIforLEssAuto project, which leverages artificial intelligence to advance low-emission, autonomous urban transportation systems. As a Research Visitor, Omar extends his expertise to the field of designing health monitoring devices, integrating IoT and AI technologies to create innovative solutions that enhance environmental sustainability and human well-being.
Alumni are the group's research students and research staff who left the group and continue with their career somewhere else.
Zhanghu Zhao was a Master Student majoring in Computer Science. He worked as a Research Assistant focusing on the development of machine learning methods for new particle formation event classification. He applied deep learning methods to do this task and made comparisons between them.
Qianqian Xia was a Master's student majoring in Computer Science. She focused on machine learning for large-scale, multi-scenario air quality classification using portable sensors in her thesis work. Prior to her academic pursuits, she excelled as an IT Specialist at a leading data technology company in Wuhan, China. Her diverse background positions her as a valuable contributor to the domain of intelligent environmental monitoring and analytics.
Yiling Hu was a Master's student in Atmospheric Science at the University of Helsinki. During the summer, she worked as a summer intern to analyze the performance of air quality low-cost sensors installed at SMEAR III and on the highway (in Espoo). Prior to this, she had worked as a data algorithm engineer for an environmental consulting company in Shenzhen, China.
Research visitors are researchers who visited (in the past) this group for collaboration.
Lian Duan was a visiting Ph.D. student from Fudan University, China, with a research focus on carbonaceous aerosols in megacities of eastern China. Her primary interests lie in the characterization, source apportionment, and health risk assessment of these aerosols. Additionally, she is keenly interested in utilizing statistical and mathematical modeling techniques to evaluate the potential adverse health effects on residents exposed to prolonged high levels of black carbon.