Viji Vennelakanti

Viji Vennelakanti

Bengaluru, Karnataka, India
Member since June 28, 2018
Viji was the director of IT in Chicago and worked there for 15 years leading a team of over 100 with a budget of $18 million. She led the Agile transformation of the organization and was the interim PMO for 18 months. More recently, she was the CTO and co-founder of a fintech startup in India. Viji is also a certified deep learning and machine learning practitioner and a deep learning mentor at Coursera.
Viji is now available for hire
Project Highlights
Expertise
  • Agile Transformation
  • Budgeting
  • Deep Learning
  • IT Strategy
  • Machine Learning
  • Program Management
  • Scrum
  • Technical Leadership
Education
Employment
  • Consultant - Machine Learning and Project Management
    2015 - PRESENT
    Self-employed
    • Completed several computer vision projects. Data cleansing, training, analysis of results using classification/object detection metrics. Submitted comprehensive reports to the client. One project’s goal was to democratize dental care. The successful completion of this proof of concept has led to the founders raising funds for a global solution.
    • Worked at a data science and machine learning startup where I built a neural network model in R for predictive analytics for chaotic time-series data from industrial IoT sensors with the goal of reducing downtime and maintenance costs. Contributed to business development opportunities. Introduced the concept of product release schedule and agile project management techniques to the team.
    • Investigated the reasons for perceived long distribution cycle times for an FMCG client. Data cleansing, exploratory data analysis, descriptive statistics, and data visualization techniques were used to suggest changes to the order entry, payment and distribution models resulting in a potential improvement of 50% in cycle time while reducing operational costs.
  • CTO and Co-founder
    2018 - 2019
    Lima Payments
    • Streamlined IT infrastructure, processes, and resources to get the most value for money.
    • Introduced Agile project management with a Kanban board on Trello and got the team into a rhythm of bi-weekly deployments.
    • Introduced best practices with respect to coding, code management, and deployments for our mobile and web app. Tech stack: Python, Android, AWS.
    • Developed a detailed 5-year budget forecast for IT resources, services, and infrastructure.
    • Helped create an investor's pitch and represented the company to various investors and accelerator programs.
  • Director/Division Manager, Information Technology
    2007 - 2013
    Rotary International
    • Led the Agile transformation of the organization along with associated restructuring. This resulted in a significant increase in the number and size of enterprise projects delivered with much-improved client satisfaction.
    • Led the establishment of an offshore captive development center in India in 2007 and successfully managed this relationship over the years. This resulted in a significant increase in the number of projects and support delivered within the same budget.
    • Managed a team of 11 project managers as the interim PMO, promoted the concept of product ownership, was responsible for the creation of and management of project portfolio budget and established a data-based project portfolio dashboard for the steering committee. These steps led to increased visibility and trust which allowed the establishment of an IT strategic plan to dovetail with the organization's strategic plan.
  • Enterprise Applications Division Manager, PeopleSoft Systems Division Manager, PeopleSoft Systems Engineer
    1999 - 2006
    Rotary International
    • Oversaw an organization restructuring.
    • Headed several large enterprise projects which were transformational in nature.
    • Implemented, supported, customized, and performed upgrades on all the major PeopleSoft financials applications.
Project History
  • Object Detection Using Computer Vision for Medical Images
    Successfully completed a proof of concept to democratize healthcare using computer vision.

    My client wanted a proof of concept to understand if computer vision using deep learning could identify medical problems from images. I used convolutional neural networks (deep learning) to deliver a successful proof of concept for object detection on medical images with a small sample training dataset of 2,500 annotated images.

    Tools used included Google Cloud Platform (GCP), Python, YOLO, and Jupyter notebook. Set up Ubuntu VM on GCP to use GPU, loaded necessary software, and trained the model using cleansed data. Analyzed results using object detection metrics. Ran another iteration with a larger training dataset and compared results to show improvement.

    The client was pleased with the improvements shown and plans to obtain funding to scale the model to accommodate a larger training dataset.

    A comprehensive report including an executive summary; approach; data cleansing procedure; GCP setup; training and testing procedure; object detection metrics and recommendations were submitted at the end of the PoC.

  • Computer Vision for Water Meter Images
    Used computer vision and deep learning to "read" water meter images and determine the reading with an accuracy of 85%.

    Planned and executed a project using computer vision and deep learning.

    Read in over 36,000 images, converted them into tensors, matched them against readings from a CSV file and cleansed the data. Ensured that the images were of the correct data type and size. Shuffled image and reading data. Split into train, cross-validation (CV), and test loaded the InceptionV3 model and used its weights on train, CV, and test data for transfer learning. Created separate hdf5 files with features, labels and batches datasets for train, CV, and test batches. Trained on a shallow CNN model and transformed the output into the right dimensions for comparison. Plotted the loss and per digit accuracy. Calculated the accuracy for train, CV, and test data.

    Iterated the above process with multiple hyper-parameters, sizes of network and also InceptionResNetV2 to improve the accuracy.

    Utilized Floydhub Cloud Platform, Keras on TensorFlow, Python 3.x, Jupyter Notebook, and Excel to work through this project. Utilized an Agile Methodology to keep the project on track and provide visibility.

  • Worldwide Loyalty Management Solution
    Let the implementation of a loyalty management solution in seven countries to reduce the cycle time from months to five days.

    This project was implemented in seven countries simultaneously to strip-out a decades-old mostly manual business process that had unpredictable cycle times and poor customer service to a simpler, consistent mostly automated business process that cut the cycle time to five business days.

Education
  • Master's degree in Business Administration, Finance
    1993 - 1995
    University of Bombay - Mumbai, India
  • Bachelor's degree in Engineering
    1988 - 1992
    University of Bombay - Mumbai, India
Certifications
  • Deep Learning Specialization
    FEBRUARY 2018 - PRESENT
    Coursera
  • Coursera Mentor Community and Training Course
    JANUARY 2018 - PRESENT
    Coursera
  • Machine Learning AtoZ
    JULY 2017 - PRESENT
    Udemy
  • Machine Learning
    APRIL 2017 - PRESENT
    Stanford University | via Coursera
  • R Programming
    DECEMBER 2014 - PRESENT
    Johns Hopkins University | via Coursera
  • Getting and Cleaning Data
    DECEMBER 2014 - PRESENT
    Johns Hopkins University | via Coursera
  • The Data Scientist’s Toolbox
    NOVEMBER 2014 - PRESENT
    Johns Hopkins University | via Coursera
  • Organization Change Management
    MAY 2012 - PRESENT
    Prosci, Chicago
  • DSDM Foundations Certificate - Agile Project Management & Development Methodology
    APRIL 2011 - PRESENT
    DSDM Consortium, UK
  • Business Process Reengineering
    NOVEMBER 2008 - PRESENT
    Northwestern University, Chicago
  • Art of Leadership
    MAY 2006 - PRESENT
    Northwestern University, Chicago

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