ManukarBapathi_Resume

MANUKAR REDDY BAPATHI

**** * **** *****, *******, Illinois, 60616 +1-312-***-**** addag4@r.postjobfree.com

• linkedin.com/in/manukarreddy • github.com/manukarreddy • leetcode.com/manukar_reddy EDUCATIONAL QUALIFICATIONS:

Masters in Computer Science May 2020

Illinois Institute of Technology, Chicago, IL

Bachelors in Computer Science May 2018

Osmania University, Hyderabad, TS

RELEVANT COURSEWORK:

Algorithms and Data Structures, Computer Vision, Artificial Intelligence, Machine Learning, Deep Learning, Software Project Management, Data Privacy and Security, Cryptography, Information Security, Application Designing TECHNICAL SKILLS:

Programming Languages: Python (3 years) (past experience in JAVA, C++, C), SQL Machine Learning and Deep Learning Libraries: scikit-learn, TensorFlow, NumPy, Scipy, Pandas, Matplotlib Software: Microsoft Azure, AWS, Jupyter, Anaconda, Git Operating Systems: Mac OS, Microsoft Windows, Linux Web Frameworks: HTML, Django, JavaScript, DOTNET

Efficient Modeling with data structures and algorithms. PROJECTS EXPERIENCE:

Deep Neural Network for classification of cat and non-cat images. (Spring 2020)

• Built an L-layer Neural Network from scratch that differentiates cats with non-cats

• Implemented a four layer Neural Network which distinguishes cats with non-cats with an accuracy of 80% American Sign Language (ASL) recognition using edge detection (Fall 2018)

• Created an application using deep convolutional networks to classify images of both the letters and digits in American Sign Language.

• Implemented segmentation to extract images and train the data using neural model that predicts the letter of the sign displayed with an accuracy of 92%

• Dynamically the sign is displayed in front of the camera using hands and the corresponding letter is viewed on the screen. Social Network Analysis using BigData Approach (Fall 2019)

• Implemented a system that would suggest the user with the most similar members who are within n hops from him.

• Performed special technique called LDA(Latent Dirichlet Allocation) analysis on documents to get topic distribution.

• Built a regression model in pyspark which predicts the 2nd degree user of the main user with mostly matched topics.

• Used tweets/retweets/likes from twitter as data source in this project. Machine Learning with Differential Privacy (Spring 2019)

• Designed machine learning algorithm using convolutional neural networks to achieve privacy guarantee resulting in differential privacy.

• Built model that trains with differential privacy on private data with an accuracy of 78%

• Differentially private model relies on Differentially Private Stochastic Gradient Descent (DP-SGD). Implementing and Attacking Prefix Preserving Encryption for Traffic Traces (Spring 2020)

• Developed a cryptography-based, prefix-preserving anonymization algorithm.

• Implemented an attack on this cryptographic scheme and proved that the scheme is robust than any other schemes for preserving prefix of IP addresses in a trace.

Cloud Based Student Information Chatbot Project using python (Spring 2018)

• Artificial intelligence will be used to answer the students queries.

• The student will get the appropriate answers to their queries.

• The answers will be given using the built in artificial intelligence algorithms incorporated with python modules. Breaking Vignere Cipher (Spring 2020)

• Designed a tool that breaks any vignere cipher.

• Alphanumeric statistics have been used to implement a logic that brute forces every key and returns the most sensible key and decoded version of the vignere cipher.

Application based Placement Management System (Spring 2017)

• Stores the information of a student regarding placements where recruiter can view the student profile straightaway from the phone.

• Implemented application on android studio that can be accessed and effectively used throughout the organization with proper login enabled.

• Student login should be able to upload their personal and educational information in the form of a resume. Web Based Data Management System (Fall 2016)

• To insert, delete, update database using GUI components.

• Designed and Developed Database interface tool to test the database Connectivity features of JDBC drivers and their supported databases.

• The DBI tool covers all methods defined in the JDBC specification and provides facility for processing queries.

• The tool provides an abstract format and interface to submit an SQL statement and view the results. CERTIFICATIONS:

• Neural Networks and Deep Learning by Deeplearning.ai founded by Stanford University on Coursera. Course Certificate earned on February 7, 2020

• Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by Deeplearning.ai founded by Stanford University on Coursera. Course Certificate earned on February 28, 2020

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