PhD Researcher
Email
Phone: +49 89 289 23507
Google Scholar
Andreas Noll
Andreas Noll studied Electrical Engineering and Information Technology, majoring in Signal Processing, Neural Networks and Haptics at the Technische Universität München. He received his Bachelor of Science (B.Sc.) degree in 2015 and his Master of Science (M.Sc.) degree in 2017. He wrote his Master Thesis at the ETH Zürich. In February 2018, he joined the Institute for Media Technology at the Technische Universität München as Ph.D. candidate. His main research interest is signal processing and information theory for haptic applications. He has been a part of CeTI from its start in 2019, where he manages the K1 room.
Projects/Cooperation within CeTI you are involved in:
Haptic Codecs, Teleoperation Setups, Human Haptic Quality Assessment
CeTI rooms within CeTI you are involved in:
K1, TP2, U3
Further Questions:
What do you value most about your work at CeTI?
The opportunity to engage with researchers from many different fields and work on exciting topics that will have a huge impact.
What was your best moment at CeTI so far?
The convention in 2021 where we were able to meet in person again, discuss our topics and find great new potential collaborations.
What else would you like to research?
I would love to research more on the human perception of tactile effects. Additionally, I would love to work on a tactile glove with our experts from the textile institute in CeTI.
How do you spend your spare time?
When the world does not stand still due to viruses, I sing in a choir every week, go swimming, play the piano often, cook and spend time with friends.
Publications:
| 1. | Automated quality assessment for compressed vibrotactile signals using multi-method assessment fusion (Inproceedings) In: Proceedings of the IEEE Haptics Symposium (HAPTICS), 2022. |
| 2. | Perceptual quality assessment of compressed vibrotactile signals through comparative judgment (Journal Article) In: IEEE Transactions on Haptics, vol. 14, no. 2, pp. 291–296, 2021. |
| 3. | Learning-adaptive deadband sampling for teleoperation-based skill transfer over the Tactile Internet (Inproceedings) In: Proceedings of the International Symposium on Wireless Communication Systems (ISWCS), 2021. |
| 4. | VC-PWQ: Vibrotactile signal compression based on perceptual wavelet quantization (Inproceedings) In: Proceedings of the IEEE World Haptics Conference (WHC), 2021. |
| 5. | Adaptive equalization of vibrotactile actuators (Journal Article) In: IEEE Transactions on Haptics, vol. 4, no. 2, pp. 371–383, 2021. |
| 6. | Quality enhancement of compressed vibrotactile signals using recurrent neural networks and residual learning (Journal Article) In: IEEE Transactions on Haptics, vol. 14, no. 2, pp. 316–321, 2021. |
| 7. | Haptic codecs for the Tactile Internet (Book Chapter) In: Fitzek, Frank H. P.; Li, Shu-Chen; Speidel, Stefanie; Strufe, Thorsten; Şimşek, Meryem; Reisslein, Martin (Ed.): Tactile Internet with Human-in-the-Loop, Chapter 5, pp. 105–133, Academic Press, 2021. |
| 8. | On the quality-of-learning for haptic teleoperation-based skill transfer over the Tactile Internet (Inproceedings) In: Proceedings of the IEEE Global Communications Conference (Globecom), 2020. |
| 9. | A rate-scalable perceptual wavelet-based vibrotactile codec (Inproceedings) In: Proceedings of the IEEE Haptics Symposium (HAPTICS), 2020. |