activity
20202026
most citedNeural ODEs for Informative Missingness in Multivariate Time Series

3 citations · 5 across the 9 of their papers we have counts for

collaborators

10 papers

cs.HC2026

From Product-Centred Retrieval to Experience-Led Commerce:Twelve Candidate Design Principles for Fashion E-Commerce User Experience

Nafiul I. Khan, Mansura Habiba, Rafflesia Khan

This paper proposes twelve candidate Experience-Led Commerce design principles for high-constraint, relational fashion e-commerce, surfaced through design-led induction while build…

cs.MA2025

A Gossip-Enhanced Communication Substrate for Agentic AI: Toward Decentralized Coordination in Large-Scale Multi-Agent Systems

Nafiul I. Khan, Mansura Habiba, Rafflesia Khan

As agentic platforms scale, agents are moving beyond fixed roles and predefined toolchains, creating an urgent need for flexible and decentralized coordination. Current structured…

cs.MA20252 cited

AGENTSAFE: A Unified Framework for Ethical Assurance and Governance in Agentic AI

Rafflesia Khan, Declan Joyce, Mansura Habiba

The rapid deployment of large language model (LLM)-based agents introduces a new class of risks, driven by their capacity for autonomous planning, multi-step tool integration, and…

cs.MA2025

Revisiting Gossip Protocols: A Vision for Emergent Coordination in Agentic Multi-Agent Systems

Mansura Habiba, Nafiul I. Khan

As agentic platforms scale, agents are evolving beyond static roles and fixed toolchains, creating a growing need for flexible, decentralized coordination. Today's structured commu…

cs.LG2024

Recent Trends in Modelling the Continuous Time Series using Deep Learning: A Survey

Mansura Habiba, Barak A. Pearlmutter, Mehrdad Maleki

Continuous-time series is essential for different modern application areas, e.g. healthcare, automobile, energy, finance, Internet of things (IoT) and other related areas. Differen…

cs.LG2021

Continuous Convolutional Neural Networks: Coupled Neural PDE and ODE

Mansura Habiba, Barak A. Pearlmutter

Recent work in deep learning focuses on solving physical systems in the Ordinary Differential Equation or Partial Differential Equation. This current work proposed a variant of Con…