•             
background Name

Bio.

Manmeet Singh

Manmeet Singh is Scientist at the Centre for Climate Change Research, Indian Institute of Tropical Meteorology, Pune and an Associate at Jackson School of Geosciences, The University of Texas at Austin, Austin, USA. He was a Fulbright-Kalam fellow at the Jackson School of Geosciences, The University of Texas at Austin in 2021. His research interests include climate solutions to the problems on land, ocean and atmosphere using mathematical models, particularly numerical weather prediction systems. He is especially interested in AI/ML techniques, causal approaches, recurrence plots, complex networks and non-linear time series analysis for solving grand challenges in Earth System Science. He is an experienced climate modeller having contributed to the IITM Earth System Model simulations towards the IPCC AR6 report. Together with his PhD co-advisor, he developed and coupled the aerosol module of the IITM Earth System Model. He is active in teaching and has given invited talks at venues such as the NASA/UAH Seminar series, Microsoft India podcast among others. His PhD focussed on the impacts of the proposals suggesting volcanic eruptions as an analogue of solar geoengineering to halt climate change. Recently, his work has shown substantial improvements in high-impact short-range numerical weather predictions using deep learning.


University Education


Doctor of Philosophy, Climate Studies

2017 - 2022

Indian Institute of Technology Bombay, Bombay, India

CGPA: 9.0/10.0

Six months coursework, PhD topic “Role of volcanic and anthropogenic aerosols on the tropical ocean-atmosphere-land coupled system and the South Asian Monsoon”


Bachelor in Engineering, Civil Engineering

2009 - 2013

Thapar University Patiala, Panjab, India

CGPA: 8.85/10.0, WES report:


MOOCs


Natural Language Processing Specialization

2021

Deeplearning.ai (coursera)

Certificate:


Probabilistic Graphical Models Specialization

2021

Stanford University (coursera)

Certificate:


A Crash Course in Causality: Inferring Causal Effects from Observational Data

2021

University of Pennsylvania (coursera)

Certificate:


Deep Learning Specialization

2018

deeplearning.ai (coursera)

Certificate:


Machine Learning

2016

Stanford University (coursera)

Certificate:


Computational Investing

2016

Georgia Institute of Technology (coursera)

Certificate:


Professional Experience


Scientist D

January 2023 - - Present

Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Government of India, Pune, India

  • AI for climate science, tabular deep learning, computer vision, NLP in climate
  • Working on projects such as cloudburst prediction system, development of urban dynamic emission inventory, improving climate models, fire forecasting, atmospheric chemistry
  • Downscaling, bias correction, GLOBUS building height at high spatial resolution, Flood forecasting, NDUI, Crop yield prediction


Associate

November 2021 - - Present

Jackson School of Geosciences, The University of Texas at Austin, Austin, Texas, USA

  • Deep learning augmented numerical weather prediction
  • Causality in climate science
  • Climate Data Science
  • Global building height for urban studies


Scientist C

January 2019 - - December 2022

Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Government of India, Pune, India

  • CMIP6 simulations, Earth System Modelling, Aerosol Module in IITM-ESM, CMOR and ESMValTool setup
  • National committee on virtual center for AI/ML in weather and climate science
  • New technologies and climate science, Google Earth Engine, Microsoft Planetary Computer
  • GPU benchmarking for biggest HPC in India, designing problem, codes and data for deep learning WeatherBench


Fulbright-Kalam Fellow

February 2021 - - October 2021

Jackson School of Geosciences, The University of Texas at Austin, Austin, Texas, USA

  • Aerosols-induced land-atmosphere interactions in South Asian Monsoon
  • Urban climate change assessment
  • High-resolution urban downscaling using deep learning
  • Global numerical weather predictions enhanced by deep learning


Scientist B

September 2015 - - December 2018

Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Government of India, Pune, India

  • ENSO-Indian Monsoon coupling using phase synchronization analysis.
  • Deep Learning for seasonal Indian Monsoon prediction


Project Scientist B

June 2015 - - August 2015

Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Government of India, Pune, India

  • Introducing direct aerosol effects in IITM-ESM using MAC data.


Trainee Scientist

August 2013 - - May 2015

Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Government of India, Pune, India

  • One year coursework in Earth System Sciences and Climate followed by a six month project on development of Direct Numerical Simulation code for Navier Stokes equations.


Test Scores


International English Language Testing System (IELTS)

Score: 8.0/9.0 · Jan 2021

Score report:


Test of English as Foreign Language (TOEFL)

Score: 106/120 · Oct 2019

Appointment:


Common Admission Test (CAT)

Score: 97.25%ile · 2015

Score card:


Graduate Aptitude Test in Engineering (GATE)

Score: 98.25%ile · 2013

Score card: