Ankush Kumar RathourComputer Vision Engineer
SUMMARY

I am a skilled Computer Vision Engineer with experience in developing, implementing, and optimizing computer vision models for real-time applications. I have expertise in deep learning frameworks such as TensorFlow, PyTorch, and OpenCV, and a proven ability to handle various tasks including object detection, image classification, video analytics, and multi-camera setups. I am adept at deploying models on edge devices and working with camera systems (Basler, PoE, CCTV) for industrial automation, particularly in the automotive sector. I have a strong understanding of YOLO and classification models, with a focus on delivering end-to-end solutions for anomaly detection and quality control in manufacturing.

Previously, I worked as a Research and Development Engineer specializing in Data Science and physics-based modeling, with a focus on industrial applications. My professional experience in the oil and gas industry includes pressure forecasting, anomaly detection, predicting gas component percentages, diagnosing failures in ultrasonic meters, and detecting anomalies in sensor data using a combination of statistical, machine learning, and deep learning techniques.

PROFESSIONAL EXPERIENCE

Computer Vision Engineer

(Eternal Robotics Private Limited)
06/2024 – present | Remote, India

Project 1: IP Cluster Inspection

Description: The IP Cluster Inspection project involves detecting child parts and classifying them to ensure that the correct part is installed in a particular vehicle model.

Responsibility:-

  • •Collect vehicle model image data.
  • •Train the YOLO AI model.
  • •Analyze the results and fine-tune the YOLO AI model.
  • •Build the software pipeline.

    • Research and Development Engineer

    (Alethe Lab India Private Limited)
    01/2022 – 05/2024Gurgaon, Haryana

    Project 1:(M.A.S.S.) Industrial Applications

    Description: M.A.S.S. Industrial Applications provide comprehensive support throughout the industrial process, from data aggregation and processing to trend identification, anomaly detection, and control functions for actions, leveraging machine learning and industrial models for enhanced operational insights and efficiency.

    Responsibility:-

  • •Write SQL queries to retrieve pressure and temperature data from the gas pipeline database.
  • •Analyze the retrieved pressure and temperature data to understand trends and patterns in the gas pipeline.
  • •Find and analyze the correlation between multiple pressure and temperature devices to identify any relationships or dependencies.
  • •Develop predictive machine learning models to forecast the pressure and temperature along the gas pipeline.

    • Project 2:(M.A.S.S) – ILI Pigging

    Description: Intelligent or smart pigging allows the pipeline operators to inspect the pipeline for anomalies like corrosion, metal loss, dent etc. without stopping the flow. Intelligent or smart PIG (Pipeline Inspection Gauge) uses sensors like Magnetic Flux Leakage or Ultrasonic to identify the anomalies. In case of long pipelines intelligent pigging is the only viable method to efficiently operate the pipeline.

    Responsibility:

  • •Preprocess and Clean Sensor Data.
  • •Analyze and Understand Features in the Sensor Data.
  • •Apply Wavelet Filter to Reduce Noise.
  • •Converting the sensor data into a gray-scale image which can help visualize the features more clearly
  • •Apply Machine Learning (ML) & Deep Learning (DL) Models to identify and classify the feature like corrosion, weld etc.
    • TECHNICAL SKILLS
  • •Python/ML Packages- NumPy, Pandas, Sci-Py, Scikit learn, Seaborn, Matplotlib, Flask, Django, Open CV.

  • •Machine Learning- Supervised Learning, Unsupervised Learning, Deep Learning, Decision Trees, Random Forests, Support Vector Machines, K - Nearest Neighbors, Gradient Boosting, Ensemble Learning, Model Selection, Hyperparameter Tuning, Cross - Validation, Feature Selection, Feature Extraction, Data wrangling.

  • •Deep Learning- Neural Network, Deep Learning, ANN, CNN, DNN, Transfer Learning, Back propagation, Optimizer, Activation Function, Loss Function, TensorFlow, Yolo.
  • •
  • •Evaluation- Cross- Validation, Precision, Recall, F1 -Score.

  • •Statistical Analysis- Hypothesis Testing, Regression Analysis, Time Series Analysis.
    • EDUCATION

    M.Sc. (Tech.) Applied Geophysics

    Kurukshetra University, Kurukshetra
    2018 – 2021

    B.Sc. (Physics, Chemistry, Maths)

    Ramdoot Collage of Education Randevi Nakur, Saharanpur (Ccs University Meerut)
    2015 – 2018
    CERTIFICATES
  • •Natural Language Processing and Text Mining - https://simpli-web.app.link/e/o7watLw4CCb

  • •Python 101 for Data Science - https://courses.cognitiveclass.ai/certificates/da77388d91794ad6a12f990f972173b1

  • •Python Assessment - https://www.hackerrank.com/certificates/f29cc91203e3

  • •SQL Assessment(Basic) - https://www.hackerrank.com/certificates/fc617f7abe1f

  • •SQL Assessment(Intermediate) - https://www.hackerrank.com/certificates/iframe/0d93e1a0fddc