T S

• Conduct research on the application of autoencoders for image compression.
• Develop and optimize the entire AI pipeline, from model training to inference.
• Improve model efficiency through quantization, pruning, and architecture search.
• Study and implement state-of-the-art AI techniques in image compression, optimizing them for real-time performance.
• Train models that integrate computer vision tasks (such as segmentation or classification) with image compression.
• Design and develop an in-house, low-latency classical codec.
• Enhance the performance of classical codecs using AI-driven approaches.
• Collect, curate, and prepare datasets for model training and evaluation.
• Innovate and explore new AI applications for the company’s products.
• Present research findings and results regularly to stakeholders.

Keywords:

Python, Computer Vision, Video Processing, Artificial Intelligence, TensorFlow, PyTorch, Video Compression, AWS.

Keywords:

Computer Vision, Deep Learning, Python, PyTorch, C++.

My research focuses on applying Deep Learning in robotics, with a particular emphasis on Reinforcement Learning algorithms. I am also interested in autonomous robots and Computer Vision.

I lead a team dedicated to developing autonomous mobile robots and integrating Artificial Intelligence techniques into robotics.

Additionally, I teach courses on Artificial Intelligence, Deep Learning, autonomous robots, and embedded systems.