M.Sc. Computer Science
TU Kaiserslautern. Thesis on physics-informed dynamic pressure map generation from videos.
AI vision / graphics / embedded intelligence
Lala Shakti Swarup Ray
PhD researcher building multimodal human motion understanding systems with 3D physics simulation, wearable sensing, and physics-informed learning.
Experience
A path through computer vision, embedded intelligence, and simulation-based research.
Research Assistant
Image Processing group, Fraunhofer ITWM Kaiserslautern.
PhD Researcher
Embedded Intelligence Lab, DFKI Kaiserslautern.
PhD, Computer Science
RPTU Kaiserslautern. 3D physics-based simulation and multimodal learning for human motion modeling.
Skills
Research code that lives between graphics engines and embedded signals.
Multimodal motion AI
Simulation-assisted learning, sensor fusion, human activity recognition, and reconstruction.
Models that learn motion
Self-supervised, contrastive, generative, diffusion, and physics-informed models.
Sensors and edge signals
IMU, pressure, capacitive textiles, bio-impedance, ambient light, camera fusion.
3D worlds and geometry
Blender, Unreal, Three.js, meshes, deformable surfaces, synthetic data, differentiable simulation.
Selected publications
Recent work across wearable computing, ubiquitous sensing, and simulation-assisted learning.
TxP: Reciprocal generation of ground pressure dynamics and activity descriptions
ChairPose: Pressure-based chair morphology grounded sitting pose estimation
SimPHAR: Impedance-based activity recognition using 3D simulation and text-to-motion models
Origami single-end capacitive sensing for continuous shape estimation
Achievements
Awarded research with a practical systems backbone.
Best Paper, ACM ISWC 2023
Best WIP Runner Up, IEEE PerCom 2024
Distinguished Paper, ACM IMWUT 2024
Best Paper, IEEE AMPS 2025
HASCA Challenge Winner, ACM UbiComp 2025
Contact