Ms. Anshita Shukla is an academician, presently working as Assistant Professor in the Intelligent Cluster, School of Computer Science & Engineering, IILM University, Gurugram. She has nearly 6 years of broad-based experience spanning research, industry, and academia, having worked as a Data Scientist and Machine Learning practitioner before transitioning into teaching. Her primary research interests lie in Artificial Intelligence, Machine Learning, and AI Safety and Responsible AI. As a researcher & author, she has published in reputed journals ,conference proceedings, authored books, and holds patents. She actively engages in independent AI safety research, publishing open-source benchmarks and audits addressing jailbreak detection, agentic tool-use guardrails, educational fairness, and healthcare reliability of large language models.

Educational Qualification

• M.Tech, IET, Dr. Ram Manohar Lohia Avadh University (July 2017 – September 2019)
• B.Tech, Dr. A.P.J. Abdul Kalam Technical University (July 2010 – June 2014)

Research and Scholarly Publication

BOOKS

• AI-Driven Wealth Planning: Harnessing Machine Learning and Large Language Models for Financial Innovation
• Optimizing Enterprise Security and Scalability: Advanced Techniques in AI- Driven Automation and Cloud architecture

PUBLICATIONS

• “An Empirical Analysis of Regression and Ensemble Learning Models (LR, DTR, RFC, GBR) for Robust and Accurate House Price Prediction Using Structured Data”, IEEE ICADCS 2026, DOI: 10.1109/ICADCS70036.2026.11583665.
• “Analyzing the Impact of AI Adoption on Job Market Dynamics and Employment Trends Using a Synthetic Dataset”, IEEE SMART 2024, DOI: 10.1109/SMART63812.2024.10882256.
• “Comparative Analysis of Machine Learning Models for Diabetes Prediction”, IEEE SMART 2024, DOI: 10.1109/SMART63812.2024.10882506.
• “Machine Learning-Based Prediction of Gold Prices Using Economic Indicators”, IEEE SMART 2024, DOI: 10.1109/SMART63812.2024.10882507.
• “Comparative Analysis of IoT and Blockchain Technologies in Enhancing Security and Efficiency in Healthcare Systems”, IEEE ICTACS 2024, DOI: 10.1109/ICTACS62700.2024.10841246.
• “Predictive Analytics in Sports: Using Machine Learning to Forecast Outcomes and Medal Tally Trends at the 2024 Summer Olympics”, IEEE ICTACS 2024, DOI: 10.1109/ICTACS62700.2024.10840553.
• “Predicting Student Academic Performance using Machine Learning: Analyzing Socio-Economic and Personal Factors from Secondary Education in Portugal”, IEEE ICTACS 2024, DOI: 10.1109/ICTACS62700.2024.10841127.
• “Benchmark Dataset for Breast Cancer Associated Genes”, Science Direct – Elsevier, July 2021 – September 2022.
• “Blockchain Platform for IoT”, AEFICS 2024.
• “Comparative Study on Face Recognition Technique”, JETIR, June 2019.
• “Prototype of Emergency Blood Donation Using AI”, JETIR, June 2019.

PATENTS

• “Object Classification For Remotely Sensed Images By Using Enhanced CNN Model”, Patent Application No. 202411041144, June 2024.
• “An IoT Based System for Remote Patient Vital Sign Monitoring”, Patent Application No. 420611-001, July 2024.