Deep Learning, Machine Vision, Temporal Modeling, Affective Computing, Image Processing, Software Engineering.
- N. Rodriguez-Diaz, D. Aspandi, S. Federico M., and X. Binefa, “Machine Learning-Based Lie Detector Applied to a Novel Annotated Game Dataset,” Future Internet, vol. 14, no. 1, Art. no. 1, 2022, doi: https://doi.org/10.3390/fi14010002.
- D. Aspandi, F. Sukno, B. Schuller, and X. Binefa, “An Enhanced Adversarial Network with Combined Latent Features for Spatio-Temporal Facial Affect Estimation in the Wild,” in International Conference on Computer Vision Theory and Applications (VISAPP), Vienna, Austria, 2021, vol. 16, pp. 172–181. doi: 10.5220/0010332001720181.
- D. Aspandi, O. Martinez, F. Sukno, and X. Binefa, “Composite recurrent network with internal denoising for facial alignment in still and video images in the wild,” Image and Vision Computing, p. 104189, 2021, doi: https://doi.org/10.1016/j.imavis.2021.104189.
- D. Aspandi, A. Mallol-Ragolta, B. Schuller, and X. Binefa, “Latent-Based Adversarial Neural Networks for Facial Affect Estimations,” in 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), 2020, pp. 606–610. doi: 10.1109/FG47880.2020.00053.
- J. Comas, D. Aspandi, M. Ballester, L. Ballester, F. Carreras, and X. Binefa, ““Short-term Impact of Polarity Therapy on Physiological Signals in Chronic Anxiety Patients",” in International Conference on Bioinformatics and Computational Biology (ICBCB 2020), Taiyuan, China, 2020, vol. 8. [Online]. Available: http://www.icbcb.org/ICBCB2020.html
- J. Comas, D. Aspandi, and X. Binefa, “End-to-end Facial and Physiological Model for Affective Computing and Applications,” in 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), 2020, pp. 93–100. doi: 10.1109/FG47880.2020.00001.
- D. Aspandi, O. Martinez, F. Sukno, and X. Binefa, “Fully End-to-End Composite Recurrent Convolution Network for Deformable Facial Tracking In The Wild,” in 2019 14th IEEE International Conference on Automatic Face Gesture Recognition (FG 2019), 2019, pp. 1–8. doi: 10.1109/FG.2019.8756630.
- D. Aspandi, O. Martinez, and X. Binefa, “Heatmap-Guided Balanced Deep Convolution Networks for Family Classification in the Wild,” in 2019 14th IEEE International Conference on Automatic Face Gesture Recognition (FG 2019), 2019, pp. 1–5. doi: 10.1109/FG.2019.8756557.
- D. Aspandi, O. Martinez, F. Sukno, and X. Binefa, “Robust Facial Alignment with Internal Denoising Auto-Encoder,” in 2019 16th Conference on Computer and Robot Vision (CRV), 2019, pp. 143–150. doi: 10.1109/CRV.2019.00027.
- D. Äspandi-Latif, S. "Goldin, and Sumaryono, “Texture Based Classification Of High Resolution Remotely Sensed Imagery Using Weber Local Descriptor,” in Asia GIS 2014 International Conference, 2014, vol. 10. [Online]. Available: http://www.asiagis.org/
Summer 2021-2022, Machine Learning, Teaching Fellow.
Summer 2021-2022, Deep Learning and Human Computer Interaction, Teaching Fellow.
Universitat Pompeu Fabra:
Spring 2019-2020 ,Deep Learning, Teaching Fellow.
Spring 2017-2018 ,Computer Organization, Teaching Fellow.
University of Mulawarman:
Spring 2013 ,Algorithm and Programming Language, Lecturer Assistant.
Spring 2013 ,Data Structure, Lecturer Assistant, Lecturer Assistant.
Fall 2010-2012 ,Computer Networking, Practicum Assistant.
Spring 2009-2012 ,Algorithm and Programming Language, Practicum Assistant.
Decky Aspandi received his Bachelor in Computer Science from the University of Mulawarman, Indonesia, and M.,Sc. degree in Computer Engineering from King Mongkuts University of Technology Thonburi, Thailand. He received Ph.D. in Information and Communication Technologies at the Universitat Pompeu Fabra, Barcelona, Spain. He is currently a postdoctoral researcher at Universitat Stuttgart, and his research interests include cross sections of Deep Learning with Affective Computing alongside their real life applications.