Third-year B.Tech Computer Science student
I, Aarya kabra am a third-year B.Tech Computer Science student at Vishwakarma University, Pune. With a Diploma in Computer Science Engineering and hands-on experience in Java, Python, C, C++, SQL, and software development projects. i have formed a strong foundation in data structures and algorithms, object-oriented programming, databases, operating systems, computer networks, and system design. My project experience includes building a Kafka-like distributed messaging system and a high-performance Deep Packet Inspection engine using distributed systems, networking, multithreading, concurrency, and client-server architecture. i am also currently developing my skills in AWS, DevOps, CI/CD, containerization, infrastructure as code, cloud architecture, and scalable systems. I am eager to apply my technical knowledge to practical engineering challenges and contribute to real-world software projects.
I am a third-year B.Tech Computer Science student at Vishwakarma University, Pune, pursuing my degree after completing a Diploma in Computer Science Engineering from Smt. Sharadchandrika Institute of Technology. I work with Java, Python, C, C++, and SQL, and have applied these languages in academic software development and systems-oriented projects. My core computer science knowledge includes data structures and algorithms, object-oriented programming, DBMS, operating systems, computer networks, and system design. I am particularly interested in distributed systems, networking, multithreaded programming, concurrency, message queues, REST APIs, and client-server architecture. My projects demonstrate practical experience in building a Kafka-like messaging system and a Deep Packet Inspection engine. I stand out through my interest in understanding systems from the ground up and my motivation to strengthen my skills in AWS, DevOps, CI/CD, containerization, infrastructure as code, and scalable software engineering.
To build reliable, scalable, and practical software systems while continuously strengthening my skills in computer science, distributed systems, networking, cloud computing, and software engineering.
To become a skilled software engineer capable of designing impactful, secure, and scalable technology solutions for real-world problems.
Academic Project
A high-performance Deep Packet Inspection engine developed in C++17 to analyze PCAP network captures and inspect traffic across Ethernet, IPv4, TCP, and UDP layers. The system tracks connections using five-tuples, identifies application and domain traffic through TLS SNI and HTTP Host extraction, and supports configurable traffic filtering.
Academic Project
A Kafka-like distributed messaging system built from scratch using Java, Maven, Apache ZooKeeper, and distributed-systems concepts. The project implements brokers, persistent storage, client libraries, producer and consumer APIs, topic partitioning, replication, broker coordination, and a client-broker binary communication protocol.
Academic Project
Architected and deployed a defense-only, event-driven return-abuse risk platform using FastAPI, Kafka, Redis, PostgreSQL, and React, designed for merchant fraud and return-operations teams.
Metrics derived from synthetic/demo data
Academic progress, technical projects, and continuous learning in computer science and software engineering.
Currently pursuing a Bachelor of Technology in Computer Science with a CGPA of 8.5 after the fourth semester. The academic journey focuses on computer science foundations, software development, systems, networking, and scalable technologies.
Completed a Diploma in Computer Science Engineering with 88.34% marks, establishing a strong foundation for further study in computer science and software engineering.
Designed and implemented a distributed messaging system from scratch with brokers, persistent storage, producer and consumer APIs, topic partitioning, replication, leader/follower mechanics, ZooKeeper coordination, and a client-broker binary protocol.
Created a C++17-based Deep Packet Inspection engine capable of parsing PCAP traffic, tracking connections, extracting application and domain information, filtering traffic, and processing packets through a multithreaded pipeline.
Helps e-commerce merchants identify and triage return/refund abuse.
It combines FastAPI, Apache Kafka, Redis, PostgreSQL, and React to ingest and process return events through synchronous rules and asynchronous worker pipelines.
