activity
20182026
most citedBenchmarking the performance of portfolio optimization with QAOA

106 citations · 168 across the 17 of their papers we have counts for

collaborators

17 papers

q-bio.GN2026

Quantum AI for Cancer Diagnostic Biomarker Discovery

Mandeep Kaur Saggi, Amandeep Singh Bhatia, Humaira Gowher +1

Quantum machine learning offers a promising new paradigm for computational biology by leveraging quantum mechanical principles to enhance cancer classification, biomarker discovery…

quant-ph2026

Quantum Machine Learning for Complex Systems

Vinit Singh, Amandeep Singh Bhatia, Mandeep Kaur Saggi +2

Quantum machine learning (QML) is rapidly transitioning from theoretical promise to practical relevance across data-intensive scientific domains. In this Review, we provide a struc…

quant-ph2026

Quantum Computing for Electronic Circular Dichroism Spectrum Prediction of Chiral Molecules

Amandeep Singh Bhatia, Sabre Kais

Electronic circular dichroism (ECD) spectroscopy captures the chiroptical response of molecules, enabling absolute configuration assignment that is vital for enantioselective synth…

cs.LG2025

Enhancing Quantum Federated Learning with Fisher Information-Based Optimization

Amandeep Singh Bhatia, Sabre Kais

Federated Learning (FL) has become increasingly popular across different sectors, offering a way for clients to work together to train a global model without sharing sensitive data…

cs.LG2024★ 1 cited

Multi-Omic and Quantum Machine Learning Integration for Lung Subtypes Classification

Mandeep Kaur Saggi, Amandeep Singh Bhatia, Mensah Isaiah +2

Quantum Machine Learning (QML) is a red-hot field that brings novel discoveries and exciting opportunities to resolve, speed up, or refine the analysis of a wide range of computati…

quant-ph2024★ 2 cited

Federated Hierarchical Tensor Networks: a Collaborative Learning Quantum AI-Driven Framework for Healthcare

Amandeep Singh Bhatia, David E. Bernal Neira

Healthcare industries frequently handle sensitive and proprietary data, and due to strict privacy regulations, they are often reluctant to share data directly. In today's context,…