Dilip Mathew Thomas, Machine Learning Developer in Kochi, Kerala, India
Dilip Mathew Thomas

Machine Learning Developer in Kochi, Kerala, India

Member since March 5, 2019
Along with having earned a PhD in computer science and engineering, Dilip has over a decade of experience in the industry. Since 2015, he’s been focusing on projects related to machine learning and deep learning for computer vision. Dilip has an eye for detail which helps in identifying data biases and developing models for image classification of fine-grained data, object detection, text recognition, image translation, and face recognition.
Dilip is now available for hire

Portfolio

Experience

  • Machine Learning, 5 years
  • Data Science, 5 years
  • Scikit-learn, 4 years
  • Deep Learning, 4 years
  • Computer Vision, 4 years
  • Artificial Intelligence (AI), 4 years
  • Keras, 4 years
  • PyTorch, 1 year

Location

Kochi, Kerala, India

Availability

Part-time

Preferred Environment

Ubuntu, Keras, Pytorch, Scikit-learn, Git

The most amazing...

...project I've worked on was the partial automation of a factory using an array of cameras and computer vision techniques.

Employment

  • AI and Data Science Engineer

    2015 - PRESENT
    Independent Consultancy
    • Built fine-grained visual classification models.
    • Created image translation models for Sketch in order to help with image generation and style transfer.
    • Implemented text recognition from images using convolutional recurrent neural networks.
    • Developed an object-detection model for apparel detection.
    • Created prototypes for anomaly detection in a surveillance camera video feed using unsupervised techniques.
    Technologies: Keras, Pytorch, Scikit-learn
  • Computer Scientist

    2015 - 2015
    Adobe
    • Investigated the use of topological methods for data analysis.
    • Explored research use cases for Adobe's digital marketing portfolio.
    • Designed a topic modeling system to understand user behavior and engagement from their mobile phone usage.
    Technologies: Python
  • Member of Technical Staff

    2006 - 2007
    Netapp
    • Designed and implemented a data deduplication module for a virtual tape library.
    • Developed a proof of concept to show the effectiveness of data deduplication.
    • Maintained the back-end code for a content management module.
    Technologies: C, C++
  • Senior Software Engineer

    2002 - 2006
    Philips
    • Designed and implemented enhancements for workflow management of cardiovascular intervention software.
    • Built and designed a memory management module for efficient image storage and retrieval.
    • Created an import-and-export module of a patient database.
    • Performed the onsite system integration and testing at Philips Medical Systems, Netherlands.
    • Designed test cases and tested different modules before the release of the software.
    Technologies: C, C++

Experience

  • Anomaly Detection in a Surveillance Video Feed (Development)
    https://beedotkiran.github.io/VideoAnomaly.html

    This project reviewed different techniques for detecting anomalies in videos using unsupervised machine learning techniques. We explored the use of reconstruction models, predictive models, and deep-learning-based generative models for this project.

    These reconstruction-based models build representations that minimize the reconstruction error of training samples from the normal distribution. Spatiotemporal predictive models take into account the spatiotemporal correlation by viewing videos as a spatiotemporal time series and learn representations that minimize the prediction error on spatiotemporal sequences. The generative models learn to generate samples from the training distribution while minimizing the reconstruction error as well as the distance between generated and training distribution. Each of these methods focuses on learning certain prior information that is useful for constructing the representation for the video anomaly detection task.

Skills

  • Libraries/APIs

    Keras, Scikit-learn, PyTorch, TensorFlow, VTK
  • Paradigms

    Data Science, Agile
  • Other

    Machine Learning, Deep Learning, Computer Vision, Artificial Intelligence (AI), Algorithms, Pytorch, DevOps Engineer, Computational Topology, Scientific Data Analysis, Computational Geometry
  • Languages

    Python 3, Python 2, C++, C
  • Platforms

    Linux
  • Frameworks

    Caffe
  • Tools

    Git

Education

  • PhD degree in Computer Science and Engineering
    2009 - 2015
    Indian Institute of Science - Bangalore, India
  • Master of Engineering degree in Computer Science and Engineering
    2007 - 2009
    Indian Institute of Science - Bangalore, India
  • Bachelor of Technology degree in Computer Science and Engineering
    1998 - 2002
    National Institute of Technology - Calicut, India

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