Computer Science
ITSC 2021: The Second International Workshop on Application of Multi-Sensor Fusion Technology for Autonomous Driving
Read more: A Workshop on 24th IEEE International Conference on Intelligent Transportation (ITSC2021)
Algorithmics and Computational Intelligence Group (ACI)
The research of the laboratory is centered around techniques and methods for algorithm design and computational intelligence, with the emphasis on both theory and applications. The foundations of the research are machine learning, probabilistic inference, discrete mathematics and theoretical computer science. In particular, the research of kernel methods, Bayesian analysis, probabilistic and information-theoretical modeling, combinatorial algorithms and intelligent systems has been pursued. The research of the laboratory is based on the long tradition of combining basic research on algorithm development and analysis with active cooperation with companies and academic partners on solving real-life problems by the use of combinatorial optimization and latest techniques on computational intelligence methods.
Selected research topics on algorithmics and computational intelligence:
- Classification and regression methods
- Clustering methods
- Combinatorial algorithms and applications
- Cross-validation methods
- Data compression
- Feature selection methods for high-dimensional data
- Industrial algorithms
- Information retrieval
- Information theoretic methods
- Multi-task and transfer learning
- Preference learning and ranking
- Probabilistic Bayesian methods
- String algorithms
- Tensor product kernels for pairwise learning
Recent Publications
- Associations between gut microbiome and circulating cytokines: a cross-sectional analysis in the FINRISK 2002 population cohort
Diab, Hassan; Langén, Ville; Yeo, Li-Fang; Salomaa, Veikko; Havulinna, Aki; Lahti, Leo; Pärnänen, Katariina; Knight, Rob; Jalkanen, Sirpa; Salmi, Marko; Niiranen, Teemu; Palmu, Joonatan - Super Level Sets and Exponential Decay: A Synergistic Approach to Stable Neural Network Training
Chaudary, Jatin; Nidhi, Dipak; Heikkonen, Jukka; Merisaari, Harri; Kanth, Rajiv - Annotated textual dataset PV600 of perovskite bandgaps for information extraction from literature
Sipilä, Matilda; Mehryary, Farrokh; Pyysalo, Sampo; Ginter, Filip; Todorovic, Milica - Social Microbial Transmission in a Solitary Mammal
Petrullo, Lauren; Webber, Quinn; Raulo, Aura; Boutin, Stan; Lane, Jeffrey E.; McAdam, Andrew G.; Dantzer, Ben - Genome-wide association study of pulpal and apical diseases
Salminen, Aino; Hyvärinen, Kati; Ritari, Jarmo; Leppilahti, Jussi M.; Palotie, Ulla; Vuollo, Ville; Kambur, Oleg; FinnGen; Estonian Biobank Research Team; Reis, Kadri; Reigo, Anu; Palta, Priit; Perola, Markus; Sinisalo, Juha; Havulinna, Aki S.; Mäntylä, Päivi; Gürsoy, Ulvi Kahraman; Suominen, A. Liisa; Rice, David P.; Anttonen, Vuokko; Nieminen, Pekka; Pussinen, Pirkko J.; FinnGen; Estonian Biobank Research Team - Interaction Analysis by Humans and AI: A Comparative Perspective
Teimouri, Maryam; Ginter, Filip; Suovuo, Tomi - YOLO for Urban Traffic: Insights from Helsinki Port Surveillance
Sharma, Shahil; Singotam, Siddarth; Kayastha, Abhinav; Jafari, Omid; Happonen, Aki; Skön, Jukka-Pekka; Heikkonen, Jukka; Kanth, Rajeev - Multi-modal Fusion of LiDAR and PRISMA Data for Cobalt Mapping: A Case Study from the Áramo Mine, Spain
Farahnakian, Fahimeh; Farahnakian, Farshad; Sheikh, Javad; Downey, Steven; Williams, Vaughan; Heikkonen, Jukka - Towards practical federated learning and evaluation for medical prediction models
Kazlouski, Andrei; Montoya, Perez Ileana; Noor, Faiza; Högerman, Mikael; Ettala, Otto; Pahikkala, Tapio; Airola, Antti - Peatland pixel-level classification via multispectral, multiresolution and multisensor data using convolutional neural network
Zelioli, Luca; Farahnakian, Fahimeh; Middleton, Maarit; Pitkänen, Timo P.; Tuominen, Sakari; Nevalainen, Paavo; Pohjankukka, Jonne; Heikkonen, Jukka
Recent Publications before 2021
- The Role of Music in 21st Century Education-Comparing Programming and Music Composing (2020)
Samuli Laato, Sampsa Rauti, Erkki Sutinen - Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects (2020)
Julkunen H., Cichonska A., Gautam P., Szedmak S., Douat J., Pahikkala T., Aittokallio T., Rousu J. - Autonomous Corrosion Assessment of Reinforced Concrete Structures Feasibility Study (2020)
Woubishet Zewdu Taffese, Ethiopia Nigussie - Holistic model for designing a climate service application on the KaiOS platform (2020)
Ville Myllynpää, Jani Haakana, Julius Virtanen, Erkki Sutinen - Deep Learning Based Multi-Modal Fusion Architectures for Maritime Vessel Detection (2020)
Fahimeh Farahnakian, Jukka Heikkonen - GeFeS: A generalized wrapper feature selection approach for optimizing classification performance (2020)
Golnaz Sahebi, Parisa Movahedi, Masoumeh Ebrahimi, Tapio Pahikkala, Juha Plosila, Hannu Tenhunen - Effects of regular use of scalable, technology enhanced solution for primary mathematics education (2020)
Kurvinen Einari - Predictive models as early warning systems for student academic performance in introductory programming (2020)
Veerasamy Ashok Kumar - Comparing CNN-Based Object Detectors on Two Novel Maritime Datasets (2020)
Valentin Soloviev, Fahimeh Farahnakian, Luca Zelioli, Bogdan Iancu, Johan Lilius, Jukka Heikkonen - Assessing the prediction uncertainty in a route optimization model for autonomous maritime logistics (2020)
Alaleh Maskooki, Petra Virjonen, Markku Kallio