I am passionate about bridging AI, cloud, and software development to drive digital innovation.
About Me
Designing Scalable AI for a Smarter Future
A results-driven consultant with 5+ years of experience in cloud strategy, software development, and artificial intelligence. I specialize in designing scalable cloud architectures, optimizing costs, and developing AI-driven solutions. Key achievements include:
- Advised 15+ clients across banking, government, and enterprise sectors on cloud transformation and optimization.
- Certified in major cloud platforms (AWS, GCP, OCI) and led as a Learning Coordinator for AWS certification initiatives.
- Designed and deployed secure, high-performance cloud infrastructures, enhancing scalability and compliance.
- Good understanding of AI and ML models with expertise in Python, PyTorch, and deep learning frameworks.
- Built web-based applications and enterprise solutions, integrating cloud-native capabilities.
Currently pursuing an MSc in Advanced Computer Science (Artificial Intelligence) at The University of Manchester, I am passionate about bridging AI, cloud, and software development to drive digital innovation.
Education
Master of Science in Advanced Computer Science
The University of Manchester
Specialized in Artificial Intelligence. Expecting Distinction
Bachelor of Engineering (Hons.) in Computer Engineering
BITS Pilani Dubai Campus
Specialized in Computer Science. Graduated with First Division
All India Senior School Certificate (High School)
The Indian High School
Specialized in Computer Science. Graduated with 91% percentile
Work Experience
Skills
Machine Learning & AI
Programming Languages
Data Science
Databases & Tools
Frameworks
Cloud
Projects
ReNewTrade
An innovative decentralized platform that enables individuals generating surplus solar energy at home to trade their excess energy with factories and companies, while also earning carbon credits and monetary rewards.
Multi-Model Approach to Relation Extraction
This project focuses on Relation Extraction, comparing two major approaches: a traditional machine learning model and a graph-based neural network. We implement XGBoost as our traditional model and Graph Convolutional Networks (GCN) as our graph-based approach, utilizing the re-DOCRED dataset. For both models, the input data is pre-processed and converted into BERT embeddings to capture rich contextual features.
Industry Project - AI Strategy
WindÅ, a platform connecting Gen Z talent with purpose-driven employers, tasked us with addressing their manual data scraping challenges and scaling needs to support employers globally. Their mission is to empower young professionals with transparent CSR, sustainability, and DEI data, and our team developed an AI strategy report detailing their pain points, key AI trends and use cases within the sector, what tools could be utilized to extract them, several AI opportunities that can be leveraged and finally an implementation roadmap.
Certifications
Contact Me
Get In Touch
I'm currently available for graduate and full-time positions. If you're looking to hire, feel free to reach out.