Kishore Ravisankar

Machine Learning Enthusiast.

Education

  • M.S. in Engineering Sciences (Data Science), University at Buffalo, February 2020
    • GPA: 3.76/4.00
    • Courses taken: Machine Learning, Data Intensive Computing, Statistical Data Mining, Probability Theory, Numerical Mathematics, Data Models and Query Languages, Programming and Database Fundamentals
  • B.E. in Electronics and Communication Engineering, Anna University, June 2018
    • GPA: 7.63/10.00
    • Selected Courses: Digital Image Processing, Digital Signal Processing, Object Oriented Programming and Data Structures, Computer Networks, Wireless Networking and Communication, VLSI Design, Embedded Systems, Optical Communication, Digital Electronics
    • Completed MOOCs in Signal Processing, Application Development from IIT
    • Organized events at the department’s tech fest Quintessence for 3 years
    • Member of IET (Institute of Engineering and Technology)

Work experience

  • Software Developer, Ford Motor Company (March 2020 - Present)
    • Developing solutions to enhance and maintain reporting processes that deliver bill of material (BOM) data to key business teams in an Agile environment. Conserved Java and Hadoop workflow runtimes by 30% and 8% respectively.
    • Co-leading the envisioning of Machine Learning use cases in the BOM team. Contributed to completion of multiple proof-of-concepts by working on data extraction, analysis, feature engineering and model training.
    • Overseeing tech refreshes in the team and managing code deployments in GitHub. Streamlined code deployment process for developers and optimized Gradle build runtimes by 36%.
    • Successfully deployed multiple webpages in a Java web app to present BOM data and other metrics by communicating with necessary APIs and SQL Server data. Reduced load time of under-performing pages by over 80%.
  • Machine Learning Intern, Buffalo Media Works LLC (September 2019 - December 2019)
    • Built a machine learning model using TensorFlow and OpenCV that crops scanned photos dynamically, to remove irrelevant features such as photo frames and color swatches. Achieved a baseline accuracy of 83%.
    • Additional Duties: Fixed critical bugs and improved code for inventory management.
  • Graduate Research Assistant, University at Buffalo (April 2019 - December 2019)
    • Predicted suitable conditions for occurrence of chemical reactions by developing a framework based on Bayesian Design of Experiments in Python, using NumPy and SciPy.
    • Analyzed and visualized results using matplotlib and seaborn, and documented results for journal publication.
  • Machine Learning Intern, GoToVerdict LLC (May 2019 - August 2019)
    • Delivered production ready code that performs semantic segmentation using TensorFlow and OpenCV on legal case summon documents, to automate extraction of case details. Achieved a baseline accuracy of 61%.
    • Implemented Named Entity Recognition using NLTK to recognize and differentiate the extracted attributes.
  • Machine Learning Intern, Tata Consultancy Services (June 2017 - July 2017)
    • Worked on creating a model to detect attributes in retail product images, such as nutritional information, product name, brand etc.

Freelance

  • Android Developer, electrophile (June 2017 - August 2018)
    • Worked on UI design and various functions of Mr Anna University, an app to calculate GPAs effortlessly
    • Tested apps for bugs

Skills

  • Programming Languages: Python, Java, R, C++, C, MATLAB, Bash, Verilog, VHDL
  • Databases: MySQL, SQL Server, Oracle SQL, SQLite
  • Packages: NumPy, SciPy, pandas, scikit-learn, NLTK, OpenCV
  • Visualization Tools: matplotlib, ggplot, RShiny, seaborn, Tableau, D3.js, PowerBI, QlikView
  • Frameworks: Tensorflow, Keras, Hadoop (Cloudera), Spark, Jekyll, Bootstrap
  • Web Development: HTML, CSS, JavaScript, JavaFX
  • Cloud services: Google Cloud Platform, Microsoft Azure, Amazon Web Services
  • Softwares: Android Studio, Arduino, OrCAD Capture, PSpice, PCB Editor, Simulink, Xilinx, Tanner Tools
  • Version Control: Git (GitHub, Gitlab, Bitbucket)
  • Software Containerization: Docker
  • Operating Systems: Windows, Ubuntu, macOS, Fedora, RHEL

Publications

  • Walker, Eric A., Kishore Ravisankar, and Aditya Savara. “CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics.” ChemCatChem 12.21 (2020): 5401-5410. Special Collection: Data Science in Catalysis.
  • Walker, Eric A., and Kishore Ravisankar. “Bayesian Design of Experiments: Implementation, Validation and Application to Chemical Kinetics.” arXiv preprint arXiv:1909.03861 (2019).
  • R. S. Selvi, R. Kishore, G. R. Suresh and S. K. S. Raja, “Embedding Data in Audio Signals using HSA-EMD algorithm”, 2017 Third International Conference on Science Technology Engineering & Management (ICONSTEM). Chennai, 2017, pp. 384-388.

Volunteer Experience

  • The Climber (March 2017 - August 2017)
  • Crossfire - The Helping Hand (March 2012 - May 2014)