output
20112026
most citedDeep-learning based down-scaling of summer monsoon rainfall data over Indian region

99 citations

25 papers

quant-ph2026

Engineering a Phase-Noise-Based Quantum Random Number Generator for Real-Time Secure Applications: Design, Validation, and Scalability

Anurag K. S. V., Shubham Chouhan, K. Srinivasan +2

Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random…

cs.CY2026

A federated architecture for sector-led AI governance: lessons from India

Avinash Agarwal, Manisha J. Nene

Purpose: India has adopted a vertical, sector-led AI governance strategy. While promoting innovation, such a light-touch approach risks policy fragmentation. This paper aims to pro…

cs.CV2025

Real-Time Sign Language to text Translation using Deep Learning: A Comparative study of LSTM and 3D CNN

Madhumati Pol, Anvay Anturkar, Anushka Khot +4

This study investigates the performance of 3D Convolutional Neural Networks (3D CNNs) and Long Short-Term Memory (LSTM) networks for real-time American Sign Language (ASL) recognit…

cs.CY2025★ 1 cited

The AI Regulatory Readiness Index ARRI: Assessing Cross-Jurisdictional Legal Preparedness for AI in Telecommunications

Avinash Agarwal, Peeyush Agarwal, Manisha J. Nene

As Artificial Intelligence becomes increasingly embedded in critical telecommunications infrastructure, existing legal frameworks remain ill-equipped to address the distinct risks…

cs.CY2025★ 25 cited

A five-layer framework for AI governance: integrating regulation, standards, and certification

Avinash Agarwal, Manisha J. Nene

Purpose: The governance of artificial iintelligence (AI) systems requires a structured approach that connects high-level regulatory principles with practical implementation. Existi…

cs.CY2025★ 3 cited

Incorporating AI incident reporting into telecommunications law and policy: Insights from India

Avinash Agarwal, Manisha J. Nene

The integration of artificial intelligence (AI) into telecommunications infrastructure introduces novel risks, such as algorithmic bias and unpredictable system behavior, that fall…