Khushboo Agarwal

Research Scholar

Industrial Engineering and Operations Research                                   
Indian Institute of Technology Bombay   

Curriculum Vitae 


Prof. Veeraruna Kavitha 

Research Interests

Branching Processes, Probability Theory, Stochastic Approximation, Behavioral aspects in game theory

Academic Background

  • M.Sc-Ph.D. in Operations Research (2017- present), IE&OR, IIT Bombay, Mumbai
  • B.Sc (Hons.) Mathematics (2014-2017), Miranda House, University of Delhi, Delhi

Academic achievements

  • Awarded with Prime Minister's Research Fellowship (PMRF) : May 2020
  • Awarded Charpak Lab Scholarship (2019) for working as a research intern at Dionysos, INRIA, France under the supervision of Prof. Bruno Tuffin

Accepted Publications

  • Kapsikar, Suyog, et al. "Controlling Fake News by Collective Tagging: A Branching Process Analysis." IEEE Control Systems Letters 5.6 (2020): 2108-2113. Link 
  • Agarwal, Khushboo, Patrick Maillé, and Bruno Tuffin. "Impact of Heterogeneous Neutrality Rules with Competitive Content Providers." 2021 IFIP IM. IEEE, 2021. Link 
  • Agarwal, Khushboo, and Veeraruna Kavitha. "Co-Virality of Competing Content over OSNs?." 2021 IFIP Networking Conference (IFIP Networking). IEEE, 2021. Link 
  • Singh, Vartika, Khushboo Agarwal, Shubham, and Veeraruna Kavitha. "Evolutionary Vaccination Games with premature vaccines to combat ongoing deadly pandemic." EAI VALUETOOLS, 2021. Link
  • Agarwal, Khushboo, and Veeraruna Kavitha. "Saturated total-population dependent branching process and viral markets." Link (manuscript submitted to CDC 2022)

Publications under Review/Preparation

  • Agarwal, Khushboo, and Veeraruna Kavitha. "New results in branching processes using stochastic approximation." (Manuscript under preparation)


  • Presented the paper titled "Co-Virality of Competing Content over OSNs?" at IFIP Networking conference, 2021 Slides Video


  • Core: Optimization Models; Operations Analysis; Computer Programming and Algorithms; Engineering Statistics, ​Probabilistic Models; Service and Infrastructure Systems; Linear Systems; Decision Analysis and Game Theory; Optimization Techniques; Introduction to Stochastic Models
  • Electives: Discrete Event System Simulation; Quantitative Models for Supply Chain Management; Random Graphs: Theory and Applications; Systems Dynamics Modeling & Analysis; Online Learning; Integer Programming: Theory and Computations; ​Advanced Stochastic Processes for Operations Research;  Networks, Games and Algorithms; Advanced Stochastic Processes for Operations Research II; Applied Mathematical Analysis in Engineering; Optimal Control Systems; Introduction to Stochastic Optimization, Markov decision processes

Teaching Assistantship

  • Topics in Industrial Engineering and Operations Research (IE 802) : Autumn 2021
  • Decision Analysis and Game Theory (IE 616) : Spring 2021, 2022
  • Probability & Stochastic Processes I (IE 621) : Autumn 2020
  • Decision Analysis and Game Theory (IE 616) : Spring 2020
  • Introduction to Stochastic Processes (NPTEL project) : November- March (2020, 2021)
  • Introduction to Stochastic Models (IE 611) : Autumn 2019


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