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Bikram Baruah

Research and Solutions Engineer at Opteran
Intro Book
Bikram Baruah, a seasoned Research and Solutions Engineer with extensive experience in AI, machine learning, and software development, holds a Bachelor of Engineering degree from the University of Sheffield.
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Location
Sheffield, England, United Kingdom, GB
Languages
  • English Full professional proficiency
  • Hindi Full professional proficiency
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Credentials

  • Introduction to Machine Learning in Production
    Coursera
    May, 2022
    - Apr, 2026
  • AI for Medical Diagnosis
    Coursera
    Oct, 2021
    - Apr, 2026
  • Sequences, Time Series and Prediction
    Coursera
    Sep, 2020
    - Apr, 2026
  • Convolutional Neural Networks
    Coursera
    Feb, 2018
    - Apr, 2026
  • Structuring Machine Learning Projects
    Coursera
    Nov, 2017
    - Apr, 2026
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
    Coursera
    Oct, 2017
    - Apr, 2026
  • Neural Networks and Deep Learning
    Coursera
    Oct, 2017
    - Apr, 2026
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms
    Coursera
    Aug, 2017
    - Apr, 2026

Experience

  • Opteran
    • Sheffield, England, United Kingdom
    • Research and Solutions Engineer
      • Nov 2022 - Present
      • Sheffield, England, United Kingdom

      • Led the development and deployment of a remote simulation-based development tool to accelerate the algorithm development lifecycle. • Blended technical expertise with strong communication skills to collaborate and provide customized solutions for clients, analyzing their data, and maintaining strong relationships to ensure client satisfaction and product optimization. • Set the foundation for analytical testing within the company, by implementing multiple large scale open-loop and closed-loop tests to help developers perform insight-driven algorithm iteration of the company’s autonomy software stack.• Developed Github Workflows to trigger automated tests to generate KPIs for various algorithms, and created Grafana dashboards to visualize the KPIs saved onto a MySQL database• Provided mentorship to interns to support their development and enhance job performance.

  • AMRC
    • United Kingdom
    • Research Services
    • 400 - 500 Employee
    • Technical Lead - AI
      • Aug 2021 - Oct 2022

      • Researching and developing multi-class classifiers to classify minute defects in turbine blades used for jet engines. Testing different methods and models such as Big Transfer, one-class classifier.• Developing image processing routines to classify between the different types of defects on composite samples. • Involved in scoping of AI projects and assessing feasibility of a project. Reviewed technical reports for projects related to AI.

    • Software Developer
      • Sep 2019 - Aug 2021

      • Researched and trained a multi-class object detection model to detect small items with an accuracy of 96% for a construction company. Involved in data collection, pre-processing, training and validating the model.• Developed a classifier with 98% accuracy to detect defective carbon composites using statistical properties of the image such as mean, variance, skewness and additional post processing of those statistical properties. Built a web interface using HTML/CSS and Flask to do real-time defect detection on a camera stream• Developed feature detection models for an aerospace partner using HALCON.• Delivered multiple projects for high-value clients as part of an agile project delivery system by continuously monitoring milestones.• Mentored a placement student by providing them technical guidance.

  • AMRC
    • Intern Machine Learning Developer
      • Jul 2018 - Sep 2018

      • Successfully designed and built a generic time-series segmentation algorithm in Python to segment different parts produced by a lathe. • Statistical features calculated from the individual segments were then fed into a machine learning classifier to detect anomalies during production in real-time with 92% accuracy.

  • The University of Sheffield
    • Sheffield, United Kingdom
    • Summer Research Intern
      • Jun 2018 - Jul 2018
      • Sheffield, United Kingdom

      • Built a machine learning model to predict the dose-response curve for anti-cancer drugs from the GDSC dataset with 97.5% accuracy. Tested different algorithms and evaluated them based on various performance metrics.

Education

  • 2016 - 2019
    The University of Sheffield
    Bachelor of Engineering (B.Eng.), Electronic and Communications Engineering
  • 2004 - 2015
    Don Bosco High School
    91.8% in CBSE AISSCE 2016

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Industry Focus. “Software Development”

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