About
Software Developer & AI Engineer
Hello! I'm Binaya Sharma, a passionate software developer and Master's student in Computer Science at Louisiana State University (LSU). With a Bachelor's in Computer Engineering from Tribhuvan University, Nepal, and professional experiences in big data, microservices, and AI, I strive to solve real-world problems through efficient software solutions. I have contributed to projects ranging from digital forensics LLM to pharmaceutical R&D tools. Outside of tech, I am an avid traveler who enjoys exploring new places and cultures, bringing a global perspective to my work.
Skills
My diverse skill set, which includes proficiency in various programming languages, frameworks, databases, machine learning and DevOps tools, allows me to tackle a wide range of challenges in the rapidly evolving tech landscape.
Resume
I have worked on projects that demonstrate my ability to apply my expertise to real-world problems, such as developing microservices for pharmaceutical R&D, implementing big data pipelines for the European Central Bank (ECB), building a specialized language model for digital forensics and predicting vehicle energy consumption for a road network using advanced machine learning techniques.
Education
Master's in Computer Science
2023 - 2024
Louisiana State University, Baton Rouge, LA
Relevant Courses: Artificial Intelligence, Algorithms Analysis and Design, Cloud Computing, Big Data, Advanced Operating Systems
Bachelor's in Computer Engineering
2015 - 2019
Tribhuvan University, Kathmandu, Nepal
Relevant Courses: Data Structures and Algorithms, Theory of Computation, C/C++, Database Systems, Enterprise Applications, Project Management
Current Position
Graduate Research Assistant
2023 - Present
LSU, Baton Rouge, LA
- Implemented Residual Vision Transformer (RVT) to predict energy consumption pattern for multiple vehicles across a city’s road network, achieving 20% improvement to Convolution Vision Transformer (CVT).
- Migrated web app and data for Artifact Genome Project from public (DigitalOcean) to private server, reducing operational costs and increasing data security.
- Developed one of the first local Large Language Model (LLM) for digital forensics by fine-tuning LLaMA-3-8B using the Retrieval Augmented Fine-tuning (RAFT) approach on a corpus of digital forensics research papers and curated digital artifacts, achieving 4.06% improvement in BERTSCORE F1, 15.79% improvement in G-Eval (using GPT-4o) and 86.6% source citation accuracy.
- Conducted user survey to evaluate practical applicability of ForensicLLM by developing a survey web app using Flask and deployed on Azure.
- Deployed multiple model configurations (base, fine-tuned, RAG) and managed concurrency using vllm to prevent memory crashes on an NVIDIA RTX 4090 handling over 80 participants.
- Performed Kruskal-Wallis tests to assess statistical significance of the user ratings across categories such as participant’s digital forensics experience and familiarity with LLMs.
Past Professional Experiences
Big Data Developer
2022 - 2023
Ultra Tendency, Kathmandu, Nepal
- Collaborated with international teams remotely to refactor big data pipeline for European Central Bank (ECB) using Cloudera Distributed Hadoop platform (Kafka, HBase, Spark) and Spring Boot.
- Improved code coverage by over 20% by resolving critical bugs and implementing test cases.
- Managed microservices deployments with Ansible and Kubernetes.
Software Developer
2019 - 2021
Leapfrog Technology Inc, Kathmandu, Nepal
- Developed microservices for pharmaceutical R&D utilizing AWS cloud infrastructure (EC2, RDS, S3).
- Developed RESTful APIs using Micronaut and Hibernate, with Oracle backend and lit-html frontend.
- Integrated and optimized BLAST search algorithm using multi-processing, reducing comparison time by 50%.
- Implemented secure authentication using JWT and dynamic role-based authorization across microservices.
- Automated data migration processes from multiple sources streamlining transitions and minimizing manual labor.
- Contributed to API’s documentation of different microservices used using Swagger API tools.
business Intelligence (bi) intern
2019 - 2019
LIS Nepal, Lalitpur, Nepal
- Understand the ETL process being used for a chain retail company.
- Write Python and SQL scripts to carry out ETL processes.
- Generate BI reports using MicroStrategy.
Portfolio
- All
- Project
- Research Paper
ForensicLLM
A local Large Language Model (LLM) for digital forensics developed by fine-tuning LLaMA-3-8B using the Retrieval Augmented Fine-tuning (RAFT) approach on a corpus of digital forensics research papers and curated digital artifacts, achieving 6.9% improvement in BERTSCORE F1 and enabling the model to accurately cite sources 84.6% of the time. 2024
DeepTran
DeepTran leverages deep learning techniques to accurately forecast energy consumption for various vehicle types across a city's road network, incorporating real-time traffic conditions. It integrates a Residual Neural Network (ResNet) into the Vision Transformer architecture to capture spatial patterns and temporal dependencies. 2023
Backward Pattern Matching using FM-Index
The FM index is a specialized index that combines the Burrows-Wheeler Transform (BWT) with a compressed data structure, making it useful for locating specific patterns and determining the frequency of pattern occurrences in large string sequences. This indexing strategy is very effective when searching for a specific pattern, such as locating a certain gene in a DNA sequence. 2023