Biography

Rahul Chaudhari works as a Senior Researcher at the Chair of Media Technology since August 2019.

He earned his doctoral degree (Summa cum Laude) in Communications and Signal Processing from TUM in 2015. His PhD thesis was titled "Data Compression and Quality Evaluation for Haptic Communications". He earned his Master's degree in Communications Engineering at TUM in 2009, and prior to that his Bachelor's degree in Electronics and Telecommunications from the University of Pune, India.

After his doctorate, he spent several years in the industry in various roles - as Software Engineer and as Technical Project Manager. He worked for various Munich-based start-ups (Artisense, NavVis, and Advanced Navigation Solutions) in the area of sensor fusion (camera, IMU, LIDAR) for 3D Mapping, Positioning and Navigation.

Research interests

The Human Activity Understanding research at LMT builds models of human interaction with the environment using Computer Vision, Sensor Fusion, and AI techniques. The insights gained from these models can be used to build technology that improves human well-being, comfort and convenience.

Current focus: Understanding Human-Object Interactions using Computer Vision and Machine Learning

Under this topic, we build models of human-object interactions using camera data (RGB and Depth) recorded in indoor environments. Depending on the availability, wearable sensors (e.g. Inertial Measurement Units) or sensors installed in the environment (RFID, motion detectors, etc.) may be fused together with RGB-D data.

Keywords: Human Activity, AI, IoT, Intelligent Environments, Ambient Assisted Living