Aakarsh Nadella
Data Engineer at Amazon
Data Engineer at Amazon
Experienced Research Assistant with a demonstrated history of working in the higher education industry. Skilled in Python, Java, C++, Apache Spark, HTML, Data Analysis, and R. Strong research professional with a Master of Science - MS focused in Computer and Information Sciences, General from Purdue University.
Amazon
https://www.linkedin.com/company/amazon
Greater Seattle Area
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Data Engineer
Branded Entertainment Network
https://www.linkedin.com/company/bengroup
Provo, Utah Area
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Data Engineer
Indiana University–Purdue University Indianapolis
https://www.linkedin.com/company/indiana-university%E2%80%93purdue-university-indianapolis
Indianapolis, Indiana Area
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Graduate Research Assistant
Indiana University–Purdue University Indianapolis
https://www.linkedin.com/company/indiana-university%E2%80%93purdue-university-indianapolis
•	Worked at the department of Center for Teaching and Learning.
•	Ensured effective migration of services from Adobe Connect to Zoom.
•	Synchronized accurately every slide of the power point presentation with the audio track (explanation of slide) and converted the entire presentation into a video format.
•	Performed editing of videos using Adobe Creative Suite and also captioned the videos
•	Worked on platforms such as Adobe Presenter, Adobe Captivate, Adobe, Office Mix, OBS etc.
Indianapolis, Indiana Area
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Media Technology Consultant
M3BI
https://www.linkedin.com/company/m3bi
•	Worked for government project "Mission Digitalization" as a Database Developer. The objective is to ensure transparency of information of digital(cable) operators/providers and the clients who subscribed to them for the government. Also, to create an interface for the digital (cable) operators to store information of their clients.
•	Part of the design team to ensure proper design of database ensuring consistency and no redundancies. 
•	Created and populated the data into tables using DDL and DML commands.
•	Performed querying using all the concepts such as Joins and Procedures to test the reliability.
•	Ensured proper backup strategies of the database and also implemented the concepts of packages and triggers.
Hyderabad Area, India
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Intern - Database Developer
Master of Science - MS
Computer and Information Sciences, General
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Indiana University–Purdue University Indianapolis
https://www.linkedin.com/school/indiana-university%E2%80%93purdue-university-indianapolis/
Bachelor of Engineering (B.E.)
Computer Science
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Velagapudi Ramakrishna Siddhartha Engineering College
https://www.linkedin.com/school/vrsec/
Algorithms Analysis, Design and Implementation
CSCI 58000
Big Data Analytics
CSCI 59000
Data Visualization
CSCI 55200
Database Systems
CSCI 54100
Intelligent Systems
CSCI 54900
Programming Languages
CSCI 56500
Data Mining
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Data Structures
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Object Oriented design and Programming
CSCI 50700
•	Designed and developed distributed priority-based job scheduler based on Model View Controller (MVC), Broker and Observer architectural patterns in Java using Executor Service with dynamic thread pool size
•	Ensured that program is consistent, concurrent and uses memory efficiently with high throughput and low latency
Priority-based Job Scheduler
•	Wrote a python program to download abstracts directly from PubMed database
•	Performed data cleaning and data preprocessing, by filtering the required sentences using Action Words
•	Trained MedPost Parts of Speech (POS) Tagger, followed by Named Entity Recognition (NER) and accessed UMLS database from Python which was hosted in a local server to identify the proteins and genes present in the data 
•	Word embeddings are done on the processed dataset using one-hot encoding 
•	Built 2 deep learning models one with Recurrent Neural Networks using LSTM and another with a combination of both Convolutional Neural Networks and Recurrent Neural Networks for the multi-class classification
•	Visualized the interaction between genes and their consequences using Cytoscape
•	Used several modules such as tensor-flow, keras, Scikit-learn, Matplotlib, NumPy, Pandas, nltk, ggplot2 etc.
Multi-class classification of Biomedical data using Deep Learning
https://github.com/aakarshnadella/Multi-class-classification-of-Biomedical-data-using-Deep-Learning
•	Carried out detailed functional dependency analysis and designed the database according to requirements of the client, achieving presumably the highest level of Normalization (Boyce–Codd Normal Form).
•	Security is ensured restricting user’s access, constrained data using triggers and views and sensitive data is protected using Dynamic Data Masking.
•	Database designed in ERwin and prototype generated using SQL Server 2016.
A Prototype of Relational Database Design for Rental Business
https://github.com/aakarshnadella/A-Prototype-of-Relational-Database-Design-for-Rental-Business
•	Implemented an XML Parser in Python to extract Amazon’s customer reviews into a CSV file 
•	Word embeddings are generated initially using Word2Vec tool on all the customer reviews
•	Deep learning framework is applied using Long Short-Term Memory (LSTM) architecture based Recurrent Neural Networks
•	Naïve Bayes Classifier using Bigrams is built on the same dataset after cleaning the reviews, eliminating stop words and performing stemming
•	Accuracy of both the models are observed and Area Under Curve is generated for comparing the performance
•	Used tensor-flow, nltk, matplotlib and ggplot packages in python
Sentiment Analysis of Reviews using Deep and Machine Learning algorithms on Textual data
https://github.com/aakarshnadella/Sentiment-Analysis-of-Reviews-using-Deep-and-Machine-Learning-algorithms-on-Textual-data
•	Feature selection is implemented using Recursive Feature Elimination(RFE).
•	Predictive models are built using machine learning algorithms such as Auto Regressive Integrated Moving Average(ARIMA), Recurrent Neural Networks(RNN) and Support Vector Machines(SVM). 
•	Performance analysis is tested by computing Confusion Matrix, Receiver Operating Characteristic Curve(ROC) and Normalized Root Mean Square Error(NRMSE). 
•	Used Python programming as environment.
Analyzing Performance of various Machine Learning Algorithms using Walmart    Stock Price Data
https://github.com/aakarshnadella/Analyzing-Performance-of-various-Machine-Learning-Algorithms-using-Walmart-Stock-Price-Data
•	Efficiently organized and stored nearly 75 GB data. 
•	The raw data in XML format is transformed to CSV file by XML Parser in Python.
•	Performed querying using Pig and PySpark. 
•	Some of the queries implemented are to find the technologies that have been growing in demand over the past few years, number of active users, most popular questions and tags etc.
•	Results to the queries are visualized using Tableau
Understanding and Implementing Big Data Concepts using Stack Overflow Data
https://github.com/aakarshnadella/Understanding-and-Implementing-Big-Data-Concepts-using-Stack-Overflow-Data
•	It is an application of fraud detection. 
•	The dataset is pre-processed, and predictive models are built using Random Forest, Gaussian process, Backup Propagation Neural Networks and Linear Regression.
•	Performance of models are analyzed using NRMSE and Coefficient of Determination(COD). 
•	Implemented using R programming
Predictive Analytics on Tax Evasion Using Feature Engineering Strategies.
https://github.com/aakarshnadella/Predictive-Analytics-on-Tax-Evasion-Using-Feature-Engineering-Strategies
https://www.linkedin.com/in/manjusha-kottala
Sunnyvale, CA
Mani Manjusha Kottala
Senior Software Engineer at Visa
https://www.linkedin.com/in/pavaniga
Itasca, IL
Prem chand Avanigadda
Software Engineer at Flexera
https://www.linkedin.com/in/schubert-carvalho-phd-6425ba4
Provo, UT
Schubert Carvalho, PhD
Director, AI Research
https://www.linkedin.com/in/sai-kiran-veera-3a0788111
Albuquerque, NM
Sai Kiran Veera
Software Engineer at Analog Devices Inc
https://www.linkedin.com/in/moniqueagonzalez
Los Angeles Metropolitan Area
Monique Gonzalez
Writer at heart, marketer by trade
https://www.linkedin.com/in/lydia-estes-9822a5195
Provo, UT
Lydia Estes
Campain Manager at Branded Entertainment Network
https://www.linkedin.com/in/chaitanya-potluri
Seattle, WA
Chaitanya Potluri
Software Engineer II at Microsoft
https://www.linkedin.com/in/bryanbecker92
Los Angeles, CA
Bryan Becker
Influencer Marketing
https://in.linkedin.com/in/anil-majeti-b8a27b1a6
Greater Chennai Area
Anil Majeti
Bachelor of Technology - BTech at Velagapudi Ramakrishna Siddhartha Engineering College
https://www.linkedin.com/in/joshua-wilkins-308172ba
Provo, UT
Joshua Wilkins
Account Executive at Branded Entertainment Network
https://www.linkedin.com/in/william-damin-244539129
Los Angeles, CA
William Damin
Digital Marketing and Community Specialist
https://www.linkedin.com/in/nicholas-johnson-7a8b3a11b
Seattle, WA
Nicholas Johnson
Data Engineer Lead at Branded Entertainment Network
https://www.linkedin.com/in/samlichtenwalter
Salt Lake City, UT
Sam Lichtenwalter
Influencer Marketing Expert | Retired YouTuber | Leading Performance Marketing and Special Projects @ BEN
https://www.linkedin.com/in/blakearrington
Provo, UT
Blake Arrington
Campaign Manager at BEN
https://www.linkedin.com/in/ginalobasso
New York City Metropolitan Area
Gina Lobasso
Account Manager, Client Services at BEN
https://www.linkedin.com/in/summerswigart
Kapaa, HI
Summer Swigart
Director, Product Development at Branded Entertainment Network
https://uk.linkedin.com/in/erinlarnder
London
Erin Larnder
Executive Director, Global Content & Integration at BEN
https://www.linkedin.com/in/maerodriguez
Los Angeles, CA
Mae R.
Director, Brand Integration at BEN
https://www.linkedin.com/in/saheli-saha
Portland, Oregon Metropolitan Area
Saheli Saha
Data Science || Data Analyst Engineer at Nike
https://www.linkedin.com/in/nishikachopra
Bellevue, WA
Nishika Chopra
Data Engineer at Amazon
Kael Kanczuzewski
      
          



            
              
        
              
  

    
        Aakarsh was an incredibly valued employee for the Center for Teaching and Learning (CTL) at IUPUI. As the university underwent a major migration from one service to another, Aakarsh provided critical support helping to manage the data needs between the two services. Aakarsh is a self starter and needed minimal day-to-day directions to complete the tasks in a timely fashion. He is dedicated, organized, and efficient. He was a joy to work with and he'd be an asset to any department or company.
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Aakarsh Nadella
Trader | Entrepreneur | Co-Founder AlphaBulls