Research Projects

Click on the projects for details and related publications.

  • Maximally Autonomous AI Assistant (MAMAA)

    Academy of Finland

    Date: 2022 -- Role: Researcher

    Over the last few decades developments in AI have taken it from playing chess to becoming an indispensable part of rapid drug development pipelines. The effect on industry and society has been transformative. However the potential of AI is currently constrained to a minority of problems, those where we can precisely specify an objective or have plenty of good solutions that can be learnt from. In this project we focus on other problems, where no good descriptions of objectives or optimal behaviour are available. This means that we must keep human judgment in the loop, to give feedback to the AI and guide it, while keeping the AI as autonomous as possible. To do this we create AI that automates what it can and relies on the human only when it is uncertain about how it should behave.

    For such a human-AI team to be efficient, the AI must be aware of what it does not know about the goal, so that it can figure it out by asking for information from the user. Thus, the AI needs to know what and how to ask the user to minimize the user’s effort through automation. In this project, we will introduce AI-assistants with advanced user models. With such models, the AI-assistants can design effective and efficient interaction with the user to elicit as much information as possible about the goal, and thereby acquire long-term decision-making skills through reinforcement learning to automate the solutions to the extent the goal is clear.

    We will deploy these AI-assistants on real-world reinforcement learning problems where designing the reward functions is difficult. In particular, we will work in collaboration with companies working on chemical design and autonomous driving, and use their real-world pipelines as our test benches.

  • Artificial Intelligence for Urban Low-Emission Autonomous Traffic (AI4LessAuto)

    Academy of Finland

    Date: 2022 -- Role: Researcher

    At present, road transport contributes a significant amount to the total carbon dioxide (CO2) emissions in the EU. Thus, cities look for practical strategies to make their transport system more efficient and sustainable. Electrification of road transport is the primary technological change needed to meet the carbon reduction targets. However, electrification is unlikely to be sufficient since the electricity production will not be carbon neutral in the near future. There is a second major technological transformation on-going in road transport—digitalization—bringing forth the advent of connected automated vehicles. Connected automated driving will transform traffic flow management into a proactive disaggregated and cooperative paradigm that, via appropriate strategies, may enable a decrease in CO2 emissions. However, the total joint effects of electrification and autonomy on CO2 emissions are not well understood. There are major potential cross-effects, such as an increase of vehicle-km travelled due, for example, to an autonomous car visiting a recharging station. Furthermore, the transitions will not be instantaneous but electric and combustion engines, and automated and human-operated vehicles will co-exist for a significant period, which is not typically taken into account in existing studies. When combined with new possible vehicle ownership models and policies, the impact of automation on urban traffic remains highly uncertain. In the future, digitalisation and communication technologies may also enable much more flexible management of the existing infrastructure.

    AI4LessAuto brings together atmospheric and computer scientists and traffic engineers in active dialogue with municipal stakeholders with the ultimate aim to understand how autonomous electrified traffic should be organized during the transition period in order to reduce CO2 emissions. This is achieved by 1) building a framework of computational modelling tools to evaluate the CO2 emissions originating from electrified automated vehicles, and 2) developing artificial intelligence based control from vehicle-level to city-center wide traffic-level in which CO2 emissions are minimized.

  • Bridging the Reality Gap in Autonomous Learning (B-REAL)

    Academy of Finland

    Date: 2020 -- 2022 Role: Researcher Project No: 328399

    We address the problem of autonomously learning to perform tasks. This is the fundamental challenge in developing genuinely autonomous systems across fields, from robotics and autonomous vehicles to customer services, employable outside the narrowly defined tasks the current hand-crafted solutions require. The challenging bottleneck is that autonomous learning necessarily involves exploration, which in the real world is costly and unsafe. This is the reason why the impressive demonstrations of recent deep learning powered reinforcement learning are not yet available in the real world. B-REAL aims to bridge this reality gap between autonomous learning in real and simulated worlds.

    The core idea is to learn an artificial surrogate model, in which both performance and safety can be checked before real-world action. What is new in this project is that now we believe we are in the position of setting up the currently disjoint modelling methods required for coping with the reality gap into a complete next-generation autonomous system. This requires efficient ways of learning accurate simulators, matching them with the real world, and including safety constraints. Safe and effective operation requires taking into account the uncertainty of the simulation outcomes, which is now possible even for the necessarily flexible simulators due to our recent, award-winning breakthroughs in deep probabilistic modelling.

    Publications of the Project

    Learning Based High-Level Decision Making for Abortable Overtaking in Autonomous Vehicles

    E. Malayjerdi, G. Alcan, E. Kargar, H. Darweesh, R. Sell, V. Kyrki
    Submitted to IEEE Transactions on Intelligent Vehicles
    Publication year: 2022

    Learning Visual Feedback Control for Dynamic Cloth Folding

    Conference Papers
    J. Hietala, D. Blanco-Mulero, G. Alcan, V. Kyrki
    Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
    Publication year: 2022

    Differential Dynamic Programming with Nonlinear Safety Constraints Under System Uncertainties

    Journal Articles
    G. Alcan, V. Kyrki
    IEEE Robotics and Automation Letters, Volume 7, Issue 2, Pages 1760 - 1767
    Publication year: January, 2022

    Planning for Safe Abortable Overtaking Maneuvers in Autonomous Driving

    Conference Papers
    J. Palatti, A. Aksjonov, G. Alcan, V. Kyrki
    24th IEEE International Conference on Intelligent Transportation (ITSC 2021), Indianapolis, United States, September 19-22, 2021
    Publication year: October, 2021

  • State Estimation for Control in Autonomous Driving

    Sensible 4, Finland

    Date: 2021 Duration: 6 months Role: Researcher

  • Machine Learning Techniques for Driver Evaluation in Heavy-Duty Vehicles

    Ford Otosan, Turkey

    Date: 2018 -- 2019 Duration: 1 year Role: Researcher

    Publications of the Project

    Driver Evaluation in Heavy Duty Vehicles Based on Acceleration and Braking Behaviors

    Conference Papers
    M. E. Mumcuoglu, G. Alcan, M. Unel, O. Cicek, M. Mutluergil, M. Yilmaz, K. Koprubasi
    46st Annual Conference of the IEEE Industrial Electronics Society (IECON 2020), Singapore, October 18-21, 2020
    Publication year: 2020

    Driving Behavior Classification Using Long Short Term Memory Networks

    Conference Papers
    M. E. Mumcuoglu, G. Alcan, M. Unel, O. Cicek, M. Mutluergil, M. Yilmaz, K. Koprubasi
    4th International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE 2019) Torino, Italy, July 2-4, 2019
    Publication year: 2019
  • System Identification Methods for Dynamic Calibration of Diesel Engines

    Ford Otosan, Turkey

    Date: 2016 -- 2018 Duration: 3 years Role: Researcher

    Publications of the Project

    Optimization-Oriented High Fidelity NFIR Models for Estimating Indicated Torque in Diesel Engines

    Journal Articles
    G. Alcan, V. Aran, M. Unel, M. Yilmaz, C. Gurel, K. Koprubasi
    International Journal of Automotive Technology, Volume 21, Issue 3, Pages 729 - 737
    Publication year: January, 2020

    Estimating Soot Emission in Diesel Engines Using Gated Recurrent Unit Networks

    Conference PapersJournal Articles
    G. Alcan, E. Yilmaz, M. Unel, V. Aran, M. Yilmaz, C. Gurel, K. Koprubasi
    9th IFAC International Symposium on Advances in Automotive Control (AAC 2019) Orléans, France, June 23-27, 2019
    IFAC-PapersOnLine, Volume 52, Issue 5, Pages 544-549
    Publication year: September, 2019

    Predicting NOx Emissions in Diesel Engines via Sigmoid NARX Models Using A New Experiment Design for Combustion Identification

    Journal Articles
    G. Alcan, M. Unel, V. Aran, M. Yilmaz, C. Gurel, K. Koprubasi
    Measurement, Volume 137, Pages 71-81
    Publication year: April, 2019

    Diesel Engine NOx Emission Modeling Using a New Experiment Design and Reduced Set of Regressors

    Conference PapersJournal Articles
    G. Alcan, M. Unel, V. Aran, M. Yilmaz, C. Gurel, K. Koprubasi
    18th IFAC Symposium on System Identification (SYSID 2018) Stockholm, Sweden, July 9-11, 2018
    IFAC-PapersOnLine, Volume 51, Issue 15, Pages 168-173
    Publication year: October, 2018
  • Design and Development of a National Endoscopic Device for Medical Applications Based on Hydrodynamic Cavitation

    The Scientific and Technological Research Council of Turkey

    Date: 2013 -- 2016 Duration: 3 years Role: Researcher Project No: 113S092

    Publications of the Project

    Biomedical Device Prototype Based on Small Scale Hydrodynamic Cavitation

    Journal Articles
    M. Ghorbani, C. Sozer, G. Alcan, M. Unel, S. Ekici, H. Uvet, A. Kosar
    AIP Advances, Volume 8, Issue 3
    Publication year: March, 2018

    Characterization and Pressure Drop Correlation for Sprays under the Effect of Micro Scale Cavitation

    Journal Articles
    M. Ghorbani, G. Alcan, A. K. Sadaghiani, A. Mohammadi, M. Unel, D. Gozuacik, A. Koşar
    Experimental Thermal and Fluid Science, Volume 91, Pages 89-102
    Publication year: February, 2018

    Design, Prototyping and Control of a Flexible Cystoscope for Biomedical Applications

    Conference Papers
    C. Sozer, M. Ghorbani, G. Alcan, H. Uvet, M. Unel, A.Kosar
    4th International Conference on Mechanics and Mechatronics Research (ICMMR 2017), Xi'an, China, June 20-24, 2017
    Publication year: June, 2017

    Visualization of Microscale Cavitating Flow Regimes via Particle Shadow Sizing Imaging and Vision Based Estimation of the Cone Angle

    Journal Articles
    M. Ghorbani, G. Alcan, M. Unel, D. Gozuacik, S. Ekici, H. Uvet, A. Sabanovic, A. Kosar
    Experimental Thermal and Fluid Science, Volume 78, Pages 322–333
    Publication year: November, 2016

    A New Visual Tracking Method for the Analysis and Characterization of Jet Flow

    Journal Articles
    G. Alcan, M. Ghorbani, A. Kosar, M. Unel
    Flow Measurement and Instrumentation, Volume 51, Pages 55-67
    Publication year: October, 2016

    Single Droplet Tracking in Jet Flow

    Book ChaptersConference Papers
    G. Alcan, M. Ghorbani, A. Kosar, M. Unel
    International Conference on Image Analysis and Recognition (ICIAR 2016), Póvoa de Varzim, Portugal, July 13-15, 2016
    Lecture Notes in Computer Science, Volume 9730, Pages 415-422
    Publication year: July, 2016

    Visualization and Image Processing of Spray Structure Under the Effect of Cavitation Phenomenon

    Conference PapersJournal Articles
    M. Ghorbani, G. Alcan, D. Yilmaz, M. Unel, A. Kosar
    9th International Symposium on Cavitation (CAV 2015), EPFL, Lausanne, Switzerland, December 6-10, 2015
    Journal of Physics: Conference Series, Volume 656, Article Number: 012115
    Publication year: December, 2015

    Vision Based Cone Angle Estimation of Bubbly Cavitating Flow and Analysis of Scattered Bubbles Using Micro Imaging Techniques

    Conference Papers
    G. Alcan, M. Ghorbani, A. Kosar, M. Unel
    41st Annual Conference of the IEEE Industrial Electronics Society (IECON 2015), Yokohama, Japan, November 9-12, 2015
    Publication year: November, 2015