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Eshika Aggarwal

Qualification
Assistant Professor, IT Systems & Analytics

Dr Eshika Aggarwal is a researcher in the field of Information Systems and Artificial Intelligence with her work published in many international journals including Soft Computing, Journal of Intelligent & Fuzzy Systems, and International Journal of Mathematics in Operational Research. She holds a Ph.D. and an MBA from the Indian Institute of Management Lucknow, and a bachelor’s degree from Punjab Technical University, along with professional certications such as Lean Six Sigma and SCJP. She has nine years of rich industry experience in IT with firms such as NIIT Technologies, IBM, and Tata Consultancy Services, and has consulted with global organizations such as Cisco, Airtel and Voya.

  • Ph.D, IIM Lucknow
  • MBA, IIM Lucknow
  • B.Tech (Information Technology), Punjab Technical University
  • Indian Institute of Management Jammu
  • Indian Institute of Management Lucknow
  • NIIT Technologies Pvt. Ltd
  • IBM India Pvt. Ltd
  • Tata Consultancy Services Pvt. Ltd.

 

  • Aggarwal, E. & Mohanty, B. (2023). Hesitant fuzzy sets with non-uniform linguistic terms: an application in multi-attribute decision making. International Journal of Mathematics in Operational Research, 24(1), 1-28. (ABS,SCI/SSCI/ESCI,Scopus)
  • Mohanty, B. K. & Aggarwal, E. (2022). A preference structure in Multi-Attribute Decision Making –An algorithmic approach based on Hesitant Fuzzy Sets. Soft Computing (Impact factor: 4.20), 26, 7259-7277. (SCI/SSCI/ESCI,Scopus), DOI : https://doi.org/10.1007/s00500-022-07112-w
  • Aggarwal, E. & Mohanty, B. K. (2022). An Algorithmic-based Multi-Attribute Decision Making Model under Intuitionistic Fuzzy Environment. Journal of Intelligent & Fuzzy Systems (Impact factor: 2.12), 42(6), 5537-5551. (SCI/SSCI/ESCI,Scopus), DOI : DOI: 10.3233/JIFS-212026
  • Sinha, N. (2024). Artificial Intelligence-based Decision-making in HRM: A Systematic Literature Review and Future Research Agenda. 9th INDAM conference, 2024 on Creating Impact Through Responsible Leadership & Sustainable Business Practices INDAM and Goa Institute of Management Goa, India:
  • Sinha, N. (2024). AI-based Decision-making in HRM. Seventh Emerging Research Paradigms in Business and Social Sciences (ERPBSS 2024) conference Middlesex University Dubai Campus in Knowledge Park, Dubai, United Arab Emirates:
  • Aggarwal, E. (2021). A recommender system that reacts to buyers’ feedbacks - A new TOPSIS model with hesitant fuzzy data. The 22nd Conference of the International Federation of Operational Research Societies Hanyang University in Seoul South Korea:
  • Aggarwal, E. (2017). Fuzzy Logic and TOPSIS: An integration approach for product recommendation in online business. Dec 2017: Proceedings of Fifth PAN IIM World Management Conference IIM Lucknow, (pp.183-192). Lucknow India:

Information Systems

IT Agile Product & Project Management

Research Interests:

Methodological developments for modelling and analysis in uncertain environment

Cognitive & fuzzy implications with Multi attribute decision making in online platforms

 

 


  


  • Conferred with prestigious "Outstanding Women Researcher in Information Systems & Analytics" award at 9th Venus International Women Awards. The award by Venus International Foundation was presented for achievement in the field of Management. 9th International Women awards, Chennai, India, March 2, 2024

  • Ignite Award 2015: Awarded for overall leading the project successfully in NIIT Technologies, Noida, India 
  • Outstanding Award 2010: Awarded for exceeding the expectations for the successful completion of the project by Tata Consultancy Services, Mumbai, India 
  • Customer Appreciation Award for making TCS proud 2009: Recommended by the onsite client for the exceptional work done in the consultancy project.
  • State level Chess Champion
  • All India level best Athlete

 


  • International Society of Multi-Criteria Decision Analysis
  • Reviewer to Soft Computing

  • Reviewer to Journal of Organizational Computing and Electronic Commerce