Mobile Application
Mobile application research currently centers on enhancing user experience, improving development processes, and addressing privacy concerns. Key focus areas include optimizing large language models (LLMs) and other deep learning architectures (like CNNs and Vision Transformers) for on-device performance, leveraging LLMs for tasks such as user review analysis and feature suggestion, and developing privacy-preserving techniques like federated learning. This research is significant because it drives innovation in mobile technology, improves app development efficiency, and enables the creation of more user-friendly and secure applications across diverse domains, from healthcare to agriculture.
Papers
An Annexure to the Paper "Driving the Technology Value Stream by Analyzing App Reviews"
Souvick Das, Novarun Deb, Agostino Cortesi, Nabendu Chaki
QuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster Inference on Mobile Platforms
Guillaume Berger, Manik Dhingra, Antoine Mercier, Yashesh Savani, Sunny Panchal, Fatih Porikli