DC05 - Models and algorithms for human sensing and gesture recognition
Description | Using wireless network signals as seamless sensors for environment/human perception, learning and smart interaction |
Host institution | POLIMI |
Country | (IT) |
Supervisor | Prof. Monica Nicoli (POLIMI, IT) |
Co-supervisors | Prof. Andre Kokkeler (UT, NL), Dr. Pieter Crombez (TELEVIC, BE) |
Objectives | To design models and signal processing algorithms for high-precision sensing of multiple humans inside the coverage of next-generation wireless network (e.g., 6G) exploiting the high-precision sensing capability of mmWave MIMO systems in the 6D domain (position and angles), enabling human sensing and positioning, shape recognition and pose/gesture estimation for smart remote services. Cooperative and Bayesian signal processing algorithms and machine learning methods will be considered. |
Expected Results | Documented characterization of the impact of the interaction of the radio signals with the environment and with humans, design of efficient data-driven models and learning algorithms. |
PhD enrolment | POLIMI (IT) |
Planned secondments | UT, NL (M18-20, mentor & co-supervisor: Prof. Andre Kokkeler): train DC05 on body motion influence on radio signal properties. |
| TELEVIC, BE (M31-33, mentor & co-supervisor: Dr. Pieter Crombez): train DC05 on practical off-the-shelf motion solutions |
Candidate profile | expertise in telecomunication engineering, or/and computer science, or/and automation and control engineeting or/and electronics |
Desirable skills and interests | machine learning, signal processing, 6G networks |
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