Social Media Data

ManiKanta Vankayala

www.linkedin.com/in/manikanta-vankayala ● Tempe AZ 85281 ● +1-480-***-**** ● *********.****@*****.*** SUMMARY Computer Science graduate student with deep understanding of Cloud technologies, Distributed Database Systems and Internals, looking for full-time positions in data engineering and software development roles. EDUCATION

M.S Computer Science (Big Data Spec.) Arizona State University, Tempe 4.20/ 4.0 May’21 M.Tech Information Security National Institute of Technology, India 8.10/10.0 May’18 B. Tech Computer Science and Engineering National Institute of Technology, India 7.95/10.0 May’17 RELEVANT COURSE-WORK

Cloud Computing Distributed Database Systems Distributed Systems Distributed S/W Development Statistical Machine Learning Artificial Intelligence Data Visualization Data Mining Algorithms & Data Structures SKILLS

Programming: Java, C++,C,C#,Python, Scala, TD SQL, PostgreSQL,MySQL,NoSQL,MongoDB, JDBC, ORM Technologies: Spark, Hadoop, AWS EC2, S3, SQS, GCP CDN, VPC, GAE, Redis, TaskQueues, HTTP, REST APIs, GIT PROFESSIONAL WORK EXPERIENCE

Software Engineer at Teradata Jun’18 - Dec’19

● Developed the Foreign Access Feature (FAF) Module that provides seamless and high-performing data processing between external cloud storages (AWS S3, AZURE, Google cloud storage) and teradata database to support to querying semi-structured and structured data such as JSON,CSV & Parquet to perform analytics on TD compute engine.

● Implemented the Bin-packing algorithm for load balancing among AMPs to lessen the execution time of SQL queries

● Designed and developed the Table Operator (read_nos) to read the Raw data and Metadata of files in the cloud storage and also implemented the access control for Table Operator (read_nos) for multi-tenancy.

● Created the stored procedures to help the Database Administrators to generate and execute the DDL queries to access the parquet data. Eliminated the messages passing overhead which reduced the data transfer time between Hash maps. Identification of key hackers in the hacker community via Twitter Social Media using Centrality Jun’ 16 - Dec’16

● Used REST and Streaming APIs of Twitter to collect hackers data and processed JSON objects to implement Mapping Degree Centrality and Mapping Betweenness Centrality algorithms to identify key hackers. ACADEMIC PROJECTS

AWS Machine Learning as a Service AWS EC2, S3, SQS Jan’20 - Jul’20

● Developed FullStack Application that provides object detection as a service using AWS cloud resources to autoscale depending on the input traffic. Configured SQS to queue the messages triggered by S3.

● Implemented load balancer from scratch to scale out/in the number of EC2 instances based on incoming traffic using multi-tier architecture. Used Boto3 and Paramiko libraries and darknet algorithms to accomplish the project. Developed SaaS application, PedalHire, using Google Cloud Services GoogleCloudResources Jan’20 - May’20

● Developed Google App Engine based Application, to rent and hire bikes in real-time, supported by Google Cloud SQL to store structured data, Google CDN for static data caching and Google Virtual Private Connector for private Redis cluster

● Used Google TaskQueues & MemoryStore for performance improvement & routed HTTPS API calls via Google EndPoint Spatial data processing using GeoSpark Scala, Apache Spark, HDFS, Map Reduce Jan’20 - Jul’20

● Utilized Spark capabilities to identify top 50 hotspots in the Manhattan area where top Taxi pickup spots in January 2015 by analyzing Geospatial data from New York Taxi database with five-node Spark cluster.

● Implemented a Map-Reduce program in Scala that considers the time series data to count the number of pickups in a location for every hour. Heap sorted all the spatial locations to find the places where most pickups happened. Image classification using machine learning models. Jan’20 - Jul’20

● Developed supervised machine learning models on MNIST dataset to classify the images using a feature set.Performed extensive exploratory data analysis and performed Naive bayes and logistic regression classification techniques

● Achieved the accuracies around 82% for logistic regression and 70% for Naive bayes. FindBestStore Jan’20 - Jul’20

● Developed the RESTful and Soap services like Authentication, Registration, OrderPlacing, Encryption and Decryption.

● Used Google Maps APIs to calculate the nearest and cheapest items in the grocery stores and recommended the same in the UI developed using ASP.NET.

Developed e-commerce console application using event driven multithreading programming Jan’20 - Jul’20

● Designed the client-server architecture and developed the e-commerce console application that allows retailers to create order events and allows producers to process those events.

● Used Multi-cell buffer and Semaphores to synchronize between retailers and producer threads. CERTIFICATIONS

Teradata Professional Coursera Cloud Computing

Contact this candidate