Shreshth Saxena
Research Areas
- Remote and portable methods of eye tracking for large scale in-the-wild studies
- Relationship of eye movements to spatiotemporal attention in the context of music listening
- Deep generative models for audio and visual data
Vita
Academic Education
| 2017–2019 | Master of Science in Computer Science, First Division, University of Delhi, India. Master Thesis: “Predicting Stock Market Indices using Recurrent Neural Network architectures” |
| 2014–2017 | Bachelor of Science (hons.) in Computer Science, First Division, University of Delhi, India |
Professional Experience
| Since 2022 | PhD candidate, Department of Psychology, Neuroscience & Behaviour, Faculty of Science, McMaster University, Canada |
| Since 2022 | Visiting Researcher, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main |
| 2021–2022 | PhD candidate, Music Department, Max Planck Institute for Empirical Aesthetics, Frankfurt am Main |
| 2019–2021 | Computer Vision Researcher, Fitivity Inc |
| 2019 | Data Science Intern at Cvision.ai (now Inspektlabs) |
Publikationen
Publikationen
Saxena, S., Lange, E. B., & Fink, L. (2022). Towards efficient calibration for webcam eye-tracking in online experiments. In Proceedings ETRA 2022: ACM Symposium on Eye Tracking Research and Applications (pp. 1-7). doi:10.1145/3517031.3529645.
Projects
- Musik und Eye-Tracking
Untersuchungen der Blickposition, der Pupille und des Blinzelns sind wichtig, um Aufmerksamkeitsprozesse im visuellen Bereich zu verstehen. So ist beispielsweise seit langem bekannt, dass die visuell-räumliche Aufmerksamkeit stark mit dem Blick ...