Kunal Singh Email & Phone Number

Santa Clara, CA, US

Santa Clara, CA, US

Santa Clara, CA, US

Berkeley, CA, US

Reader for Data 100 - Principles and Techniques of Data Science

San Francisco, CA, US

- Designed, implemented, optimized, and productionized NLP-based algorithm for computational storytelling from news events- Built web-based application to visualize storylines of events - Tools: Python, TensorFlow, Django, D3.js, AWS, Postgres, Kubernetes, HTML/CSS

Berkeley, US

Berkeley, US

Intuit (Spring 2018)- Built a latent space of financial terms using natural language processing to build a self-learned financial ontology for Intuit- Created visualization in D3.js to visualize latent spaceWish (Fall 2017)- Constructed model to automatically determine image quality for product images on Wish marketplace- Built data pipeline with Amazon.

Berkeley, CA, US

- Created deep learning models to predict future network traffic across Energy Sciences Network, part of an end-to-end system for a self-learning network connecting all Department of Energy research labs- RNN/LSTM, seq2seq learning, online learning- Tools: Python, Tensorflow, Keras, AWS, SageMaker, Docker, Google Cloud Platform (GCP) BigQuery, BigTable

Berkeley, CA, US

- Reasoning Group under Prof. Michael Ranney- Translated explanations of transcripts on http://www.howglobalwarmingworks.org/, the site designed by the Reasoning Group dedicated to educating people on global warming

Los Angeles, CA, US

- Under Prof. Eran Halperin- Developed microbial source tracking model to predict proportions of contamination from a given set of sources in different samples - Multiple mixture models, Expectation-Maximization (EM), Markov Chains- Tools: Python, R

- Developed an interactive data model with MEDLINE publication database using Python and D3.js. Utilizing a force-directed graph with nodes and links, the model served as a basic visualization of research credibility for authors. - Transformed inSilicoDB microarray gene expression data and BioChain gene sequence variant data to aid in target discovery and.

Stony Brook, NY, US

- Simons Summer Research Program, under guidance of Prof. Dimitris Samaras - Developed a machine learning based framework for the automatic classification of shapes and multiple attributes for individual nuclei in brain tumor tissue slides- Isolated stains, extracted sets of visual features, and trained multiple Support Vector Machine (SVM) models.

New Brunswick, NJ, US

- Under guidance of Prof. Vladimir Pavolvic- Designed an autonomous program in Python for an airborne drone to detect a target face in a room and accurately position itself to take an optimal photograph of the face. - Utilized Face++ detection and recognition software and developed an algorithm to compute the required time the drone needs to travel to.

Bachelor'S Degree, Computer Science

Education record