Computer Vision
(Perception)
- Deep learning
- Convolutional neural networks (CNN)
- Generative adversarial networks (GAN)
- Image and video processing
- Temporal modelling for video activities
- Image & video segmentation
- Segmenting instance, semantics & multimodal info.
- Object detection and recognition
- Gesture & gait recognition
- Scene classification
- Microscopic image acquisition and processing
- Biomedical image processing
- Image restorations
- Super-resolution
- GAN based image transformations
- Object tracking
- Video activity analysis & prediction
- Video surveillance, traffic scene analysis
- Stereo vision and depth estimation
- 3D point cloud and multimodal image data analysis
Machine Learning
(Intelligence)
- Pattern recognition
- Mathematical optimization methods
- Theoretical aspects of ML
- Applications of ML
- Financial data analysis
- Medical domain
- Bioinformatics
- Design and modification of CNN architectures for speed and memory efficiency
- Optimization for end-to-end learning and one-shot learning
- Temporal data analysers, LSTM, GRU and Bayesian learning methods
- Stability analysis of ML models and convergence analysis of optimization based learning algorithms
- Data science, predictive & exploratory analysis
- ML with imbalanced data
- Portfolio optimization & quantitative analysis
- Algorithmic trading
- Bioinformatics, quantitative biology and genomics
- Data-driven healthcare
Robotics
(Learning and Sensing)
- Reinforcement learning
- Autonomous driving
- R&D for new sensors
- Human robot interaction
- Sensor development and integration of multi-sensory data for robotics & autonomous driving
- Low cost sensor development for healthcare, biosensors and sensory data enhancement
- Higher order sensing via fusion of multi-array and multi-modal sensors
- Integrating learning mechanism in sensing itself
- Human robot interaction, imitation learning and reinforcement learning
- Control, navigation & soft landing of drones
- Remote sensing
- Path planning in autonomous driving, simultaneous localization and mapping (SLAM)
Signal Processing & Communications
(Multimodal Multichannel Systems)
- ML for communication systems
- Optical, satellite, RADAR, mm-waves
- Medical image processing, audio, EEG
- Biosignals & cognitive systems
- Load-balancing and optimal resource allocation in multi-channel communication systems
- Machine learning for communications (optimal configuration and parameter estimation)
- Millimeter wave, radar, wifi and optical communication based pattern recognition
- Satellite imaging and remote sensing in static as well as dynamic environments
- Multimodal signal processing in all modalities: audio, multispectral, EEG, ECG, EMG
- Biosignals & cognitive systems: cognitive biomarkers in biosignals
- Our research lab is flexible and accommodative to work on any new topics in Signal Processing & Communications