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Built a AI Cyborg (Aegis) which aims to operate at client's site to prevent location privacy breach.
Conceptualized and programmed a novel obfuscation privacy model such that adversary confidence is reduced by 59.7%.
Tested and optimized the model for 6.86 million tweets and 360 user's profile.
Advanced cloud computing
Implemented 5 private + public clouds to solve a computationally intensive problem by doing automatic job scheduling and job slicing.
Architected an overlay on 50+ commodity instances to make maintanence and control easy and flexible by using terminal multiplexing software.
Analysed the following research paper:
Technology Stack
Ruby on Rails, Tsung , Git, Travis CI
• Boomerang is an application that connects people together. People would love and appreciate real, safe and simple communications in person with the help of our application which matches people based on thier mood.
• Identified bottlenecks for scalability in load balancing and SQL statement using Tsung load testing.
• Re-designed the system using pagination, caching and scaling (horizontal & vertical) techniques to improve performance by 33.3%.
Global Data Management
Developed a ride sharing application on top of a private blockchain to create a trusted but decentralized system such that we de ne a contract between the provider and the consumer without any middle-man.
Data dissemination protocol optimized blockchain network performance and scalability by splitting workload across all nodes by 30%
Operating System
Developed and Coded my own version of malloc() for dynamic memory allocaion. Handled memory fragmentation.
Wrote 8 system calls (like fork, wait, sbrk) and constructed the memory management system
Designed a online ticket system for 5 kiosks such that mutual exclusion is ensured.
Implemented multithreading and heartbeat system to execute PAXOS consensus algorithms.
Rebuilt app to tolerate site failures and network partitioning by collaborating a global snapshot algorithm.
Simulated state machines in Python by establishing reliable TCP/IP connections.
Constructed an application for advertising a local event deciding who all to give information about the event so that they cover maximum people in a community.
Engineered problem into a wider problem of choosing a committee in a multi-attributed network which ensures maximum diversification as well as coverage.
Quntified the problem with an algorithm built on greedy algorithm leading to improving the runtime by 60%.
Piloted the model on a social network data set in Python. Reached 30% coverage in the data set.
Technology Stack
Python , SQL , Git