Biswajit Sahoo

Biswajit Sahoo

Machine Learning Engineer

HP Inc. R&D, Bengaluru, India


Professional with 7+ years of experience in data-driven fault diagnosis and prognosis of rotating machinery. I got introduced to these fields during my PhD research at IIT Kharagpur, where I was advised by Prof. A. R. Mohanty. I am a trained Mechanical Engineer with proficiency in machine learning and programming. Always eager to leverage my domain knowledge and machine learning experience to tackle emerging problems in condition-based maintenance and Industry 4.0. An open source contributor aiming to demystify technical jargons through expository writing and code that would contribute towards understanding of digital transformation happening in mechanical/manufacturing industry. My open source contributions can be found here and my blogs can be found here. Beyond research, I like literature and music.

  • Machine Learning
  • 3D Printing
  • Anomaly Detection
  • Time Series Analysis
  • Natural Language Processing
  • Signal Processing
  • Condition-Based Maintenance
  • Industrial Internet of Things
  • PhD in Mechanical Engineering, 2024

    Indian Institute of Technology, Kharagpur, India

  • MTech in Mechanical Engineering, 2015

    National Institute of Technology, Rourkela, India

  • BTech in Mechanical Engineering, 2013

    Odisha University of Technology and Research (Formerly College of Engineering and Technology), Bhubaneswar, India


Machine Learning Engineer
April 2023 – Present Bengaluru, India
Machine Learning Engineer
November 2021 – March 2023 Bengaluru, India
Project Manager (Condition Based Maintenance)
October 2020 – October 2021 Kolkata, India
Senior Data Science Consultant
June 2020 – September 2020 Kolkata, India

Recent Posts

All blog posts can be found here.


Browse all publications with code here.
(2022). Multiclass bearing fault classification using features learned by a deep neural network. In International Congress and Workshop on Industrial AI 2021.

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(2021). Machine Learning, Regression, and Optimization. In Data Science and SDGs.

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(2020). Feature Subset Selection Using Sparse Principal Component Analysis and Multiclass Fault Classification Using Selected Features. In Advances in Asset Management and Condition Monitoring. Smart Innovation, Systems and Technologies.

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