
Software Engineer, passionate about Technology.
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ans-live-demo
October 3, 2025 – October 9, 2025
Agent Name Service (ANS): A DNS-like trust layer for secure, scalable AI-Agent Deployments on Kubernetes
View ProjectAI-Augmented-DevOps
August 20, 2025 – August 27, 2025
An original framework for integrating Predictive AI and Large Language Models (LLMs) into the DevOps lifecycle. This project introduces automated root-cause analysis (RCA), predictive scaling, and self-healing infrastructure to reduce MTTR (Mean Time to Recovery) and optimize cloud-native environments.
View ProjectRobotics-Internal-Developer-Platform-IDP
August 19, 2025 – December 10, 2025
Robotics-Internal-Developer-Platform-IDP — repository
View ProjectDomain-Focused-Sequence-Model-Experiment
August 19, 2025 – September 11, 2025
This repository contains the complete reproducibility code for the IEEE Cars conference paper "Domain Focused Sequence Model Architecture For Predicting Long Term User Interests" - an empirical validation of distilled sequence models for personalized recommendations in automotive and transportation domains.
View ProjectAI-Augmented-Cyber-Lab
August 10, 2025 – September 26, 2025
This repository contains the complete implementation of the AI-Augmented Cyber Lab system for enhancing cloud-native security education through adaptive feedback and threat simulation, as described in our research paper.
View ProjectSEDE-2025-Paper-Reproducibility-Code
August 9, 2025 – August 27, 2025
This repository contains all the experimental code and data needed to reproduce the results from our SEDE 2025 conference paper on vulnerability detection using RAG systems.
View Projectkserve-demo
April 22, 2025 – April 24, 2025
This repository demonstrates how to deploy, scale, and monitor machine learning models on Kubernetes using KServe and Kubeflow Lite components.
View ProjectCloudyBot-DevOps-AI
April 16, 2025 – July 11, 2025
Provide a conversational assistant that can answer DevOps-related questions. This helps demonstrate how large language models (LLMs) can be applied to real-world knowledge domains (in this case, cloud and DevOps topics). For students, it’s a fun, interactive example of AI services.
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards research, innovation, and open-source contributions, particularly in the AI/ML and DevOps domains. This aligns well with a culture that values continuous learning and technical exploration. However, the projects are predominantly personal and research-oriented, with limited evidence of collaborative team environments or large-scale production system experience, which might impact cultural fit in a fast-paced, product-focused backend engineering team. The experience level is listed as 0, which suggests a lack of professional experience.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and innovative approach to problem-solving, particularly in integrating AI with DevOps and cybersecurity. The focus on reproducibility and detailed project descriptions suggests good organizational skills. However, without psychometric test results or interview data, a comprehensive assessment of soft skills and operational fit is not possible.