Close

Vivek Bhave

Download Resume

About Me

I am experienced in the areas of Machine Learning (Computer Vision, NLP, Information Retrieval) and Software Engineering (Distributed and Secure Systems).

Apart from my coursework, I have worked on two major research projects in the areas of Machine Learning & Computer Vision. Currently, I am working in the Information Fusion Lab at UMass Amherst directed by Prof. Madalina Fiterau where I am working on applying Computer Vision techniques to identify chronic diseases at an early stage through MRI images. I have initially worked with Prof. Brian Levine to build scalable ML systems to spot child harassment over social media.

I wish to use my knowledge and skills to contribute in two areas. I wish to work on applications of Machine Learning in solving real world problems in various domains like Healthcare, Finance, Education or Security. I am interested in building high performance software systems impacting millions of users everyday.

I would like to connect with Engineering Managers, Tech recruiters and students if we share any common interests.

Outside of technology, I like to play sports especially field hockey and football. I also like to read about history, philosophy and psychology.

Education

University of Massachusetts, Amherst

Sept 2019 - May 2021

MS, Computer Science (4.0/4.0)

College of Engineering, Pune (India)

July 2015 - May 2019

BTech, Information Technology (8.65/10)

Experience

Qualcomm

Interim Engineering Intern

Multimedia Visual Technology - Research & Development Division

  • Qualcomm's internal chipset design tool did not include core wise power projections
  • I implemented power projection models built in Excel and VB into Python.
  • I modified the 200k line code base of the internal tool and integrated the power models into the tool
  • New update of the tool extremely helpful for early stage chipset design, quickly estimating power projections with change in configurations among other advantages.

Schlumberger

Software Engineering Intern

Mobility Solutions - Cross Platform Application Development

  • Developed an Android application that enabled employees to record feedback during team meetings
  • Backend server logic implemented in C# on the Azure Cloud Stack
  • Anonymized data stored in Couchbase instance for time series analysis and to generate aggregated reports

Projects

Neural Text Simplification

  • Explored a novel technique to finetune pretrained models like T5, mBART, and Attention based Transformers on text simplification datasets
  • Developed a novel loss function in Tensorflow to combine results from neural and statistical models
  • Achieved a SARI score of 0.325 against the current state-of-the-art SARI score of 0.356
View Project

Image Classification using Convolutional Neural Networks and NLP

  • Performed object detection with the current state-of-the-art unified parsing model in PyTorch
  • Experimented with different neural network models to perform scene classification
  • Achieved an accuracy of 81.2% when tested over 5000 images of 10 different classes
View Project

Web Search Engine with Hadoop and Spark

  • Used a single node cluster of HDFS to store webpages and Spark for the creation of an inverted index
  • Stored and queried the inverted index to handle queries using RocksDB
View Project

Skills

Get in Touch