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Stony Brook, New York
Stony Brook University, Stony Brook, New York
Graduation: Spring (May) 2020
Master of Science, Computer and Information Sciences
Courses Computer Vision, Big Data Analytics, Natural Language Processing,
Database Systems, Analysis of Algorithms, Probability and Statistics
Mahindra Ecole Centrale, Hyderabad, India
August 2014 - August 2018
Bachelor of Technology (B.Tech), Computer Science and Engineering
GPA - 8.80/10.0
Dept. of Bio-Medical Informatics, Stony Brook University
January 2019 - Present
Graduate Research Assistant
• Developed a gradient-based adaptive sampling prediction scheme for precise discovery of tumor
regions in tissue images (WSI).
• Currently, integrating this prediction scheme with data pipelines based on InceptionV3 and
UNICEF - Office of Innovation, New York
June 2019 - September 2019
Machine Learning Intern - Satellite Imagery Analysis
• Land Cover Mapping - Developed a U-Net based segmentation analysis pipeline to identify
land resource usage from satellite imagery. Recorded validation f1-score of 88.53%.
• Poverty mapping - Developed a transfer learning pipeline using VGG-16 to assess poverty
distribution from satellite imagery. Recorded Spearman Correlation of 0.47.
ISRO, National Remote Sensing Center, India
September 2017 - May 2018
Research Assistant - Predicting Primary Crop Footprint from Satellite Images.
• Developed a ResNet (Convolutional Neural Network) based feature extractor and recorded a
prediction accuracy of 97.43%. This model can also be adapted to novel satellite scenes.
Kohli Center on Intelligent Systems, India
May 2017 - July 2017
Research Intern - Dynamic Winner Prediction in Twenty20 cricket
• Investigated this problem using supervised learning techniques (KNN, SVM, RF, XGBoost).
• Random Forest Classification yielded the highest prediction accuracy of 75.68%.
Programming/ Scripting Languages
Tensorflow, PyTorch, Spark, MySQL, AWS, Hadoop, D3.js
Data Visualization Dashboard: Visual Analysis of Security Incidents
Data visualization, Time Series analysis - (D3.js, Flask)
• Built a web framework to analyze and visualize various attributes of security incidents.
• ARMA based time-series forecasting also informs the possible trend of future incidents.
Crop Yield Prediction - Using Deep Learning
Big Data Analytics, Machine Learning - (Spark, Tensorflow)
• Developed a data pipeline to estimate future crop yield from satellite data (dataset size: 62 GB).
• Data pre-processing to extract histogram features from satellite data was performed using Spark.
• A stacked-two layer LSTM network was used for predicting crop yield from the histogram features.
1. Sasank Viswanadha, Kaustubh Sivalenka, Madan Gopal Jhawar, Vikram Pudi. ”Dynamic Winner
Prediction in Twenty20 Cricket: Based on Relative Team Strengths.” Workshop of Machine Learning in
Sports Analytics 2017 at the European Conference for Machine Learning.
• Recipient: Platinum and Team Leader Award - Apollo AI and IEEE Scholarship for Machine Learning