High bandwidth transimpedance amplifier using FGMOS for low voltage operation. - Urvashi Bansal; Maneesha Gupta (Integr., 2018)

Frequency-Compensated Bulk-Driven TIA Suitable for Low-Voltage Low-Power Applications. - Urvashi Bansal; Maneesha Gupta; Niranjan Raj (J. Circuits Syst. Comput., 2021)

Modified SIMON Approach towards Lightweight Cryptography Scheme for Multi Data Key Pair Combination. - Aniket Kadukar; Urvashi Bansal (ACI@ISIC, 2022)

A QFGMOS-Based gm-Boosted and Adaptively Biased Two-Stage Amplifier Offering Very High Gain and High Bandwidth. - Urvashi Bansal; Abhilasha Bakre; Prem Kumar; Devansh Yadav; Mohit Kumar; Niranjan Raj (J. Circuits Syst. Comput., 2022)

A compensation scheme for three-stage OTAs with no Miller capacitors. - Urvashi Bansal; Alfio Dario Grasso (NEWCAS, 2023)

A Review on Recently Reported Grounded CMOS Active Inductors. - Urvashi Bansal; Aashutosh Garg; D. Shalini (Wirel. Pers. Commun., 2023)

A systematic literature review of Internet of Video Things: Trends, techniques, datasets, and framework. - Nisha; Urvashi (Internet Things, 2023)

Quantitative Evaluation of Extensive Vulnerability Set Using Cost Benefit Analysis. - Urvashi Bansal; Geeta Sikka; Lalit Kumar Awasthi; Bharat K. Bhargava (IEEE Trans. Dependable Secur. Comput., 2024)

Explainable AI: To Reveal the Logic of Black-Box Models. - Chinu; Urvashi Bansal (New Gener. Comput., 2024)

Fair XIDS: Ensuring fairness and transparency in intrusion detection models. - Chinu; Urvashi Bansal (Concurr. Comput. Pract. Exp., 2024)

How to Defend and Secure Deep Learning Models Against Adversarial Attacks in Computer Vision: A Systematic Review. - Lovi Dhamija; Urvashi Bansal (New Gener. Comput., 2024)

AFLF: a defensive framework to defeat multi-faceted adversarial attacks via attention feature fusion. - Lovi Dhamija; Urvashi Bansal (Evol. Syst., 2025)

Deadline-aware and energy efficient IoT task scheduling using fuzzy logic in fog computing. - Rahul Thakur; Geeta Sikka; Urvashi Bansal; Jayant P. Giri; Saurav Mallik (Multim. Tools Appl., 2025)

Correction: AFLF: a defensive framework to defeat multi-faceted adversarial attacks via attention feature fusion. - Lovi Dhamija; Urvashi Bansal (Evol. Syst., 2025)