Ms. Anshita Shukla is an academician currently serving as an Assistant Professor in the School of Computer Science and Engineering at IILM University, Gurugram. She brings over five years of diverse experience spanning academia, industry, and research, with core expertise in Machine Learning and Artificial Intelligence.

A technology-driven professional, she has substantial hands-on experience in addressing complex system architectures, data-intensive challenges, and scalability issues within AI and ML ecosystems. She has contributed to several real-time AI projects, published research papers, filed patents, and authored books in her areas of specialization.

Committed to fostering innovation and academic excellence, she is passionate about mentoring students, advancing impactful research, and exploring emerging technologies to drive meaningful advancements in the field.

Educational Qualification

• Master of Technology, IET ,Dr. Ram Manohar Lohia Awadh University , 2019.
• Major : Artificial Intelligence and Machine learning ,Gold Medallist ,(First Division).
• Bachelor of Technology, Dr. A.P.J. Abdul Kalam Technical University,2014
• Computer Science & Engineering ,4 years programme ,(First Division).

Research and Scholarly Publication

BOOKS

• AI-Driven Wealth Planning: Harnessing Machine Learning and Large Language Models for Financial Innovation 2025,ISBN : 9789367886571.
• Optimizing Enterprise Security and Scalability: Advanced Techniques in AI- Driven Automation and Cloud Architecture 2025, ASIN ‏ : ‎ B0DTF71T4G
• A Systematic Approach of Blockchain Platform For Internet Of Things (book chapter)

PUBLICATIONS

• Analysing 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: Analysing 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.
• 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.
• Privacy preserving AI System For Time Detection And Prevention Of Online Harassment And Working Method Thereof (filed), July 2025