Sustainable IoT

In an era marked by unprecedented technological advancements, the proliferation of Internet of Things (IoT) devices has become ubiquitous, revolutionizing the way we interact with the world. However, this surge in connectivity raises critical concerns about sustainability. Our research delves into the realm of Sustainable IoT, aiming to develop innovative solutions that reconcile the growing demand for interconnected devices with environmental responsibility. By integrating energy-efficient designs, renewable power sources, and eco-friendly materials, we strive to pave the way for a more sustainable and ecologically conscious IoT ecosystem.

Efficient Learning Algorithms

The rapid evolution of machine learning has empowered us to extract meaningful insights from vast datasets, propelling industries forward. Yet, the efficiency challenges posed by resource-intensive algorithms and energy consumption cannot be ignored. Our research focuses on Efficient Machine Learning, exploring novel techniques to optimize algorithms, reduce computational complexity, and streamline model architectures. By pushing the boundaries of efficiency, we aim to unlock the full potential of machine learning while mitigating its environmental impact and making these powerful tools more accessible across diverse applications.

Processing-in-Memory

As the demand for faster and more energy-efficient computing systems intensifies, the traditional von Neumann architecture faces limitations in terms of data transfer speeds and power consumption. Enter Processing in Memory (PIM), a paradigm-shifting approach that seeks to blur the lines between computation and memory. Our research in Processing in Memory explores cutting-edge technologies and architectures that enable computations to be performed directly within memory modules. By bypassing traditional bottlenecks, we aim to revolutionize the landscape of computing, ushering in a new era of high-performance, energy-efficient processing that can meet the demands of the modern digital age.