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Sayani Gupta

PhD candidate

Monash University

Hello, folks! Welcome to my home page. I am doing PhD at the Econometrics and Business Statistics Department of Monash University under the supervision of Rob J Hyndman and Di Cook. My dissertation focuses on building visualization and statistical tools for analyzing spatially distributed big time series data.

I’m passionate about putting to use statistics to solve real world problems and I almost always use R to do that.

Apart from my research, I spend my time learning Indian classical music, travelling in and around Melbourne and exploring cafes near me.

Be kind, remember you are collaborating with your future self

Interests

  • Computational Statistics
  • Visualization
  • Time series analysis
  • Forecasting

Education

  • PhD in Computational Statistics, 2021

    Monash University

  • MStat in Statistics (QE specialization), 2011

    Indian Statistical Institute, India

  • BSc in Statistics (Honors), 2008

    St. Xavier's College, India

Recent & Upcoming Talks

Young Statisticians Conference

Exploring probability distributions for bivariate temporal granularities.

useR! 2018

An R package for international cricket data

Industry Experience

 
 
 
 
 

Senior Analyst

Payback

Jun 2016 – Jan 2018 Gurgaon
Responsibilities:

  • Customer segmentation, campaign management, predictive modelling, generating customer insights and developing customer engagement strategies at PAYBACK
  • Modelling wallet potential of customers
 
 
 
 
 

Consultant

KPMG

Aug 2014 – Jun 2016 Gurgaon
Responsibilities:

  • Development of Entry / Exit Transmission Pricing Mechanism for Southern African Power Pool (SAPP)
  • Load Forecasting and Power Procurement and Sale Optimization for Punjab State Power Corporation Limited (PSPCL)
  • Review of functioning of a power exchange of India - An audit of the Matching Engine/ Software Application used for price discovery and market splitting for various market segments
  • Techno-Economic study of Indian Power Sector - Assessment of demand (historical and projections), assessment of existing generation capacity & new builds (including identification of long term tie ups) and analysis of fuel availability and prices in future