Tushar Saini, MS in CS

Tushar Saini, MS in CS

Application Engineer

Oracle India

Biography

I am currently working as an Application Engineer at Health Science Global Business Unit (HSGBU) of Oracle. My work at Oracle revolves around NLP problems, where we are trying to simplify the AE reporting in Argus Safety.

Apart from work, I am also interested in IoT devices and Environmental Sciences.

Download my resumé.

Interests
  • Artificial Intelligence
  • Machine Learning
  • Computational Modelling
Education
  • MS in Computer Science, 2021

    Indian Institute of Technology, Mandi

  • B.Tech in Computer Science, 2017

    GGSIPU

Recent Publications

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(2021). Modelling Particulate Matter Using Multivariate and Multistep Recurrent Neural Networks. Front. Environ. Sci.

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(2021). Forecasting of Air Pollution via a Low-Cost IoT-Based Monitoring System. IoT and Cloud Computing for Societal Good.

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(2021). A Weighted Ensemble Approach to Real-Time Prediction of Suspended Particulate Matter. In: IACC 2020.

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(2019). An Online Low-Cost System for Air Quality Monitoring, Prediction, and Warning. In: ICDCIT 2020.

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Experience

 
 
 
 
 
Application Engineer
Oracle India Private Limited
Feb 2022 – Present Noida, India
  • ML Engineer working on Entity-Linking tasks.
  • Developed unbalanced task assignment solver based on Hungarian Algorithm.
 
 
 
 
 
Associate Data Scientist
Cogneau Systems Private Limited
Apr 2021 – Jan 2022 Gurugram, India
  • Developed mixed integer programming solver to solve inventory replenishment where there were around of 200 inputs.
  • Developed sales forecasting models for two-wheeler manufacturer via ensemble of facebook prophets and recurrent neural network.
  • Developed monte-carlo based warehouse simulator which outputs major KPIs revolving around number of workers required at what stage via simulating various inputs.
 
 
 
 
 
Project Associate
Indian Institute of Technology Mandi
Jul 2019 – Mar 2021 Mandi, India
  • Research and developed a Low-cost Air-pollution Sensing and Warning technology, which could be deployed at hilly terrains of Himalayas for 24x7 monitoring of air-pollution.
  • Developed short- and long-term machine learning and state-of-the-art deep learning forecasting model which can forecast pollution concentration ahead in time.
  • Evaluated public perception of people residing at polluted location in India and their eagerness to adopt technology to mitigate the impact of air pollution.
 
 
 
 
 
Research Intern
Center for Road Research Institute, CSIR
Apr 2019 – Jun 2019 Delhi, India
  • Worked briefly on formulating a CNN based machine learning model to identify vehicular traffic on road via CCTV footage.
  • Evaluated vehicular traffic at urban city of Ghaziabad, U.P., India, to devise a modification plan of road intersection to smooth out long traffic jams.