Contact Chandni Saha
Background
Chandni is a Navigation Engineer with experience in applied AI, resilient positioning, computer vision, and multi-sensor systems for connected and autonomous platforms.Her work focuses on developing robust localisation and perception solutions using GNSS, IMU, Visual-Inertial Odometry, SOoP, and machine learning-based methods. At Cranfield University, she contributes to ESA NAVISP research projects with industry and academic partners, working across algorithm development, sensor integration, data acquisition, performance evaluation, and hardware-in-the-loop validation. She has hands-on experience with Factor Graph Optimisation, Error-State Kalman Filtering, federated sensor fusion, ML-corrected VIO, GRU/LSTM-based drift correction, and computer vision pipelines using YOLO, DeepSORT, and pose estimation. She is skilled in Python, C++, MATLAB, PyTorch, TensorFlow, Scikit-learn, Docker, Linux, and real-world sensor data processing. Her research and engineering interests lie in resilient autonomy, GNSS-denied navigation, multi-modal perception, AI-enabled positioning, and reliable machine learning systems that can be tested and deployed in real-world environments. She enjoys working at the intersection of research, software, hardware, and field validation, turning technical ideas into practical and measurable engineering outcomes.
Current activities
Chandni Saha is currently working as a Research Assistant in Positioning and Sensor Fusion. At Cranfield University, she contributes to ESA NAVISP research projects with industry and academic partners, working across algorithm development, sensor integration, data acquisition, performance evaluation, and hardware-in-the-loop validation. She has hands-on experience with Factor Graph Optimisation, Error-State Kalman Filtering, federated sensor fusion, ML-corrected VIO, GRU/LSTM-based drift correction. She is skilled in Python, C++, MATLAB, PyTorch, TensorFlow, Scikit-learn, Docker, Linux, and real-world sensor data processing. Her research and engineering interests lie in resilient autonomy, GNSS-denied navigation, multi-modal perception, AI-enabled positioning, and reliable machine learning systems that can be tested and deployed in real-world environments. She enjoys working at the intersection of research, software, hardware, and field validation, turning technical ideas into practical and measurable engineering outcomes.
Clients
- Boeing Co
- Bill & Melinda Gates Foundation
- Jaguar Land Rover Ltd
- European Space Agency
- Vodafone Group PLC