Research topics

Machine Learning for Self-driving vehicles and Smart Mobility

1. Perception in self-driving vehicles

  • Deep learning-based Sensor Fusion 
    • Multi-modal Object detection(using LIDAR, camera, radar and sound sensors)
    • Radar-Camera sensor fusion
    • LIDAR-Camera sensor fusion

  • Deep learning-based 3D object detection
    • LIDAR Object detection
    • Camera-based 3D Object detection

  • Sensor's for Self-driving environment 
  • Calibration methods for sensors
  • Sensor configuration optimization


  • Higher attribute classification/recognition
  • Target object Intention decision making
  • Trajectory estimation
  • Mobility/Traffic rare event detection

2. Dataset generation and improvement      for self-driving vehicle and mobility applications
  • Domain adaptation 
  • Knowledge distillation
  • Generative models
3. SLAM (Simultaneous Localization and Mapping)
  • Localization (Vehicle pose estimation)
  • LIDAR odometry using Deep learning
  • Map updates using multi measured vehicles
  • Spatial AI
4. Decision making using Reinforcement Learning
  • Stop and Go problems
  • Lane change problems
  • Pedestrian vague crossing problems