Sharath TS

AI Researcher

Santa Cruz, California, United States11 yrs 5 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in deep learning algorithms and neural networks.
Strong background in machine learning applications.
Proven track record in AI research and development.

Stackforce AI infers this person is a Machine Learning and AI specialist with a focus on deep learning and neural networks.

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Skills

Core Skills

Machine LearningNeural NetworksNatural Language ProcessingDeep LearningCComputer Vision

Other Skills

Reinforcement LearningZero Shot LearningData AugmentationSeq2Seq FrameworksSequence LabelingRecurrent Neural NetworksCRFsRegular ExpressionsRecursionSVMFeature ExtractionProgrammingJavaArtificial IntelligenceAlgorithms

About

Learning Algorithms. Master's in CS from University of California, Santa Cruz. Deep roots in, and fascinated by Machine learning and it's applications.

Experience

11 yrs 5 mos

Total Experience

2 yrs 11 mos

Average Tenure

8 yrs 1 mo

Current Experience

Nvidia

2 roles

Senior Deep Learning Algorithms Engineer

Promoted

Feb 2020 – Present · 6 yrs 4 mos · Santa Clara, California, United States

Deep Learning Algorithms Engineer

May 2018 – Feb 2020 · 1 yr 9 mos · Santa Clara, California, United States

Research and development on state of the art neural networks in domains such as CV, NLP, RL and optimizing training and inference for GPUs.

Natural language and dialogue systems lab

Researcher

Sep 2017 – Mar 2018 · 6 mos · Santa Barbara County, California, United States

Focus on end-end neural language generation with stylistic variation and personality like Open, Agreeable, Shy, etc., with zero shot learning and statistical features.
Worked on a team from the NLDS lab on two independent submissions for the E2E NLG challenge.
Built systems with data augmentation, seq2seq frameworks and contribution to TGEN repository.
Implemented convolutional and recurrent networks for extraction of arguments for the Gun-control corpus.

Sap

Machine Learning Intern

Jun 2017 – Aug 2017 · 2 mos · San Francisco Bay Area

Deep Learning for product attribute extraction with sequence labeling on product descriptions using recurrent neural networks and CRFs.
Implemented Time distributed convolutions and recurrent networks with LSTMs for modelling a time series of financial transactions of a retailer to predict FICO like credit scores.

University of california, santa cruz

2 roles

Graduate Teaching Assistant

Apr 2017 – Mar 2018 · 11 mos

Teaching assistant, CMPS 109: Advanced Programming, CMPS 104: Fundamentals of Compiler Design I.

Graduate Teaching Assistant

Oct 2016 – Mar 2017 · 5 mos

Teaching Assistant for the course CMPS 109: Advanced programming

Pathsolutions

Internship

Nov 2014 – Jan 2015 · 2 mos · United Kingdom(Virtual)

Built a complete posix standards regular expression parser
in C, which was then incorporated into a library. The approach here involved recursion to get a simple and extremely fast solution rather than the conventional approach of using finite automatons. The parser was built to replace the use of Lex, the standard pattern matching library which could not be used because of it's copyright restrictions. This parser was the backbone of the mainstream library.

L&t infotech

Machine learning and Computer Vision Intern

Jul 2014 – Aug 2014 · 1 mo · Mysore

Built a ML pipeline with canny edge detectors, sobel filter for feature extraction and classification using SVM and Neural networks for Hand gesture recognition. Evaluated their performance using ROC curves.

Getacoder

Freelancer

Aug 2013 – Aug 2015 · 2 yrs

I worked on 28 projects as a freelancer where I got the opportunity to work with people all around the globe, getting acquainted with the latest tools and technologies.