Shreyas Addamane Pallathadka

+1-716-***-**** adhl0b@r.postjobfree.com Buffalo, New York,14214 Github Linkedin Education

MS, Engineering Science (Data Science) August 2019 – January 2021 University at Buffalo (State University of New York) Courses: Introduction to Probability Theory, Introduction to Numerical Mathematics, Statistical Data Mining, Programming and Database Fundamentals, Data Intensive Computing, Data Model Query Language, Introduction to Machine Learning, Introduction to Deep Learning

Bachelor of Engineering, Information Technology August 2013 – May 2017 University of Mumbai

Relevant Courses: Database Management Systems, Big Data Analytics, Data Structure and Algorithm Analysis, Software Engineering, Object Oriented Programming Methodology, Intelligent Systems Skills

AI Platforms: Microsoft LUIS, QnAMaker, BotFramework, Kore.ai, IPSoft Amelia, RASA Platform (NLU & Core Libraries) Scripting Languages: Python, MATLAB, R, Node.js, Java, PHP, C Libraries: Spacy, Scikit-learn, TextBlob, RASA, NLTK, pandas, Numpy, seaborn, matplotlib, Tensorflow, paralleldots Databases: MySQL, PostgreSQL, MongoDB, OracleDB, SQLite Frameworks: Spark (PySpark), Hadoop, MapReduce, Flask Cloud Platforms: Azure Cognitive Services (Text Analytics, Translator, Speech Service, Bing Search API) Work Experience

Accenture Technology Application Development Associate October 2017 – July 2019

Worked in Accenture Artificial Intelligence Capability as Virtual Agents (Chat-bot Developer) and Cognitive Services Developer.

Worked for a Pharmaceutical Client (Pfizer) for Modelling of Conversation and FAQs and Productionizing as a Chatbot for their internal team which acts as a one stop solution for frequent queries for newly onboarded employees.

Worked on various Virtual Agents (Conversational AI) Platform like Microsoft LUIS, QnAMaker, MS BotFramework, Kore.ai, IPSoft Amelia, RASA Platform (RASA NLU & RASA CORE) & Microsoft Cognitive Services (Speech to Text, Text to Speech).

Implemented an End to End Chatbot in Hindi using RASA NLU as well as RASA Core and Fasttext Word Vectors.

Defect Triage for a Virtual Agent (Conversational AI) Asset using Applause Crowd Testing Platform.

Implemented NERs, Sentiment Analysis Model and Text Similarity model in Chatbot using RASA NLU Pipeline. University at Buffalo Graduate Research Assistant May 2020 – Ongoing Advisor: Eric A. Walker (Research Assistant Professor, School of Engineering and Applied Sciences)

The objective of the project is to solve CO Oxidation microkinetic model by Quantum Algorithm.

This project will in the end help to solve system of linear equations through Quantum approach instead of traditional Gradient Descent Approach for faster computation.

The following algorithms are used to solve the equations derived by microkinetic model: 1. Quantum Fourier Algorithm

2. Quantum Phase Estimation to derive eigen values of matrix 3. Harrow, Hassidim and Lloyd Algorithm to solve linear system of equations

The project tries to implement 8 qubit system to solve three equations using Google Cirq Framework. Academic Projects

Glass Type Prediction from Properties (Glass Type Prediction) September 2019 – December 2019

In this project various classification algorithms like SVM, Decision Tree, Random Forest, K-NN algorithm were used in R to find out the best algorithm which can be used to predict the glass type based on its properties

The dataset contained 10 properties of glass based on that we need to predict to which type of glass the particular feature belongs to.

Analysing the crime pattern in San Francisco Area (SF Crime Pattern) September 2019 – December 2019

The objective of project to find the like relationship between the area and category of crime, Time and the category of crime, Day of the week to find out the least and the most frequently crime affected areas and days using visualization libraries like matplotlib and seaborn.

Also Dynamically mapped the Geolocation of the crime spot to find the pattern in landmarks of the crime affected area using GMPlot Library.

Machine Reading Comprehension System & Summarization (Machine Reading Comprehension) April 2020 - May 2020

Developed a Question Answering System using AllenNLP Pretrained Model which can process any paragraphs and user can ask questions on WhatsApp UI by creating a Flask endpoint which is integrated with Twilio Framework Movie Genre Prediction (Movie Genre Prediction) May 2020

The goal of the project was to build multi-label classifier based on the plot of the movie using PySpark & SparkNLP

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