Dipanwita Sinha Mukherjee

About

I’ve done my PhD in Electrical Engineering from Indian Institute of Science(IISc), Bangalore, India. My research interest is in Predictive Modelling, Machine Learning and Numerical Analysis. Other research interests include Computational Methods for Electromagnetic Fields and Software Development. Currently, I am working in Artificial Intelligence - Center of Excellence, Wells Fargo as ‘Applied AI research Scientist’ for last 2 years. I am a member of IEEE Computational Intelligence Society. I’ve a total 8 years of professional experience in Research & Development across various organizations.

Employment

• Wells Fargo Applied AI Research Scientist
  2020 - Present
• Lexmark Software Engineering Professional
  2010 - 2014
• Tata Motors Limited Manager-Development
  2008 - 2010

Education

• Indian Institute of Science Ph.D
  2014 - 2019
• Indian Institute of Science MSc-Engineering
  2006 - 2008
• Indian Institute of Engineering Science and Technology B.E.
  2001 - 2005

Projects & Funding

Projects & funding information is unavailable.

Publications (7)

• Detecting Distributional Shift Responsible for Predictive Model’s Failure*
  IEEE TechRxiv 2021 DOI: 10.36227/techrxiv.16656901.v2
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• Investigation of weight initialization using Fibonacci Sequence on the performance of neural networks*
  IEEE-TechRxiv 2021 DOI: 10.36227/techrxiv.14546022.v1
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• Prediction of variation of oxides of nitrogen in plasma-based diesel exhaust treatment using artificial neural network
  Springer-International Journal of Environmental Science and Technology 2019 DOI: 10.1007/s13762-019-02242-5
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• DBD plasma based ozone injection in a biodiesel exhaust and estimation of NO<inf>x</inf> reduction by dimensional analysis approach
  IEEE Transactions on Dielectrics and Electrical Insulation 2016 DOI: 10.1109/tdei.2016.005919
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• Discharge Plasma Assisted Adsorbents for Exhaust Treatment: A Comparative Analysis on Enhancing NOxRemoval
  Plasma Science and Technology 2008 DOI: 10.1088/1009-0630/10/3/08
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• Achieving Better NOxRemoval in Discharge Plasma Reactor by Field Enhancement
  Plasma Science and Technology 2008 DOI: 10.1088/1009-0630/10/2/12
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• Ozone estimation by ANN approach for indirect plasma based exhaust cleaning
  11th International Symposium on Non-Thermal/Thermal Plasma Pollution Control Technology and Sustainable Energy, ISNTP-11, Padova, Italy
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