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Academic Experts

Umar Farooq

Biography

Mr. Umar Farooq is currently working as an Assistant Professor (Grade I) at Jaypee Institute of 
Information Technology (JIIT), Noida. He completed his B.Tech. in Computer Science and 
Engineering from Graphic Era Hill University and his M.Tech. in Computer Science and Engineering 
with specialization in Data Science/Data Analysis from JIIT, Noida, securing a CGPA of 8.8/10. He is 
currently pursuing a part-time Ph.D. in Computer Science and Engineering at JIIT under the 
supervision of Dr. Niyati Aggrawal and Prof. Anuja Arora. His research interests include Large 
Language Models (LLMs), Natural Language Processing (NLP), Artificial Intelligence, Machine 
Learning, Generative AI, and Agentic AI. He has hands-on experience in Java, C, Python, Data 
Structures, DBMS, Operating Systems, Machine Learning, NLP, Transformer models, GPT, BERT, 
HTML, CSS, and JavaScript. As a faculty member, he is committed to delivering quality education, 
mentoring students, and contributing to research in intelligent AI systems.

Research Highlights

His research primarily focuses on Artificial Intelligence, Large Language Models (LLMs), Agentic 
AI, Natural Language Processing, and Intelligent Decision Support Systems. His work explores the 
application of advanced AI techniques for modelling complex human behaviour, developing adaptive 
intelligent systems, and designing scalable AI-driven solutions for real-world challenges. 

His master's research proposed a novel framework for predicting users' future social media behaviour 
by analysing historical posts using transformer-based Large Language Models. The study involved a 
comparative evaluation of multiple LLMs, including Flan-T5, Phi-2, Gemma-2B, and Falcon-7B, 
under persona-aware prompting strategies and temporal context modelling. The framework was 
evaluated using semantic similarity and standard NLP metrics, demonstrating the effectiveness of 
incorporating user persona and contextual information into behavioural prediction. 

Building upon this foundation, his current research is directed towards Agentic Artificial Intelligence 
with emphasis on autonomous reasoning, long-term memory architectures, multi-agent collaboration, 
planning, and trustworthy AI systems. He is actively developing a systematic research framework that 
investigates core Agentic AI capabilities through comprehensive benchmarking, dataset analysis, 
model comparison, and capability taxonomy. His long-term vision is to develop intelligent, memory
aware, and adaptive AI agents that can be applied to complex domains such as healthcare and decision 
support while maintaining scalability, explainability, and reliability. 

His research philosophy emphasizes solving fundamental AI capability challenges before domain
specific deployment, thereby contributing reproducible, experimentally validated, and practically 
deployable intelligent systems. 

Areas of Interest
  • Large Language Models (LLMs)
  • Agentic AI
  • Natural Language Processing
  • Machine Learning & Deep Learning
  • Artificial Intelligence
Achievements

Qualified UGC-NET (December 2025) under Category III. 

Runner-up in Hackathon organized by Graphic Era Hill University. 

Participated in multiple AWS workshops organized by Graphic Era University. 

Completed M.Tech. in CSE (Data Science/Data Analysis) with CGPA 8.8/10. 

Currently pursuing Ph.D. in Computer Science and Engineering at JIIT.