About Me

AI/ML engineer with a passion for building intelligent systems

I'm an AI/ML engineer focused on building intelligent applications that bridge the gap between research and real-world impact. My work spans voice AI systems, machine learning pipelines, and LLM-powered applications.

Graduated in Bachelor of Engineering in Computer Science from Chandigarh University alongside a Major in Artificial Intelligence from IIT Ropar, I combine strong theoretical foundations with hands-on engineering experience. From building real-time voice AI receptionists to developing ML-based career recommendation systems, I focus on creating end-to-end solutions that work.

As a published researcher, open-source contributor, and active participant in the tech community, I'm constantly exploring the intersection of AI capabilities and practical engineering.

Education

B.Tech in Computer Science

Chandigarh University

CGPA: 7.24

Focused on software engineering, algorithms, and data structures

Minor in AI/ML

IIT Ropar

CGPA: 7.0

Machine Learning, Deep Learning, NLP, and Computer Vision

Work Experience

Jan 2026 — Present

Part-Time STEM Educator (Robotics)

BrightChamps

Providing hands-on robotics training to students using industry-aligned kits, enabling practical understanding of core STEM and emerging tech concepts. Fostering critical thinking, problem-solving, and a strong technical mindset through real-world project-based robotics builds.

Ongoing

AI/ML Engineer — Independent Projects

Self-directed

Building end-to-end AI applications including voice AI systems with speech-to-LLM pipelines, semantic matching systems using RAG patterns, and ML-based recommendation engines. Contributing to open-source projects.

Leadership & Activities

Class Representative

2021 — 2024 | Chandigarh University

CodeChef University Coordinator

Campus programming community lead

2nd Place — Discus Throw

CU Athletic Meet 2023

Research Publication

An Overview of Vulnerabilities and Mitigation Strategies in Facial Recognition Systems

Peer-reviewed research paper published in an academic journal (DOI: 10.1063/5.0262020), exploring security vulnerabilities in facial recognition systems and their mitigation strategies.

View Publication