- MSCS @ UC Riverside | Focus: Machine Learning & AI
- Passionate about intelligent systems, model optimization, and scalable ML infrastructure
- Currently developing tools for bias detection in VLMs and predictive autoscaling for AI workloads
- Strong interest in generative modeling, semantic search, and AI deployment on cloud-native platforms
- GSoC 2025 Contributor @ Unicode Consortium — building an LLM-based validator for global locale data quality (CLDR)
- Highly interested in both Software Engineering and Machine Learning roles that solve real-world problems at scale
- Always open to meaningful ML collaborations and open-source AI work
Programming Languages
Python, C++, SQL, Bash
Machine Learning & AI
Diffusion Models, Transformers, VLLMs, Supervised Learning, Semantic Search, Bias Analysis, Retrieval-Augmented Generation
Computer Vision
OpenCV, ResNet, DenseNet, MobileNet, ViT, DeconvNets, DeepLabv3, Semantic Segmentation, Person Re-ID
Cloud & DevOps
AWS, Kubernetes (EKS), Docker, CloudLab, HPA, CI/CD
Frameworks & Libraries
PyTorch, TensorFlow, HuggingFace, Scikit-learn, LangChain, FastAPI, Gradio
Databases
MongoDB, MySQL, PostgreSQL
- Gravitational Lensing Generator using DDPM – Realistic image synthesis for astrophysics using diffusion models
- Semantic Search Engine for Medicine – Scalable web-crawler and semantic retriever for online pharmacies
- Smart Autoscaler for Kubernetes – ML-driven horizontal autoscaler for optimizing AI workloads
- Vision-Language Bias Analyzer – Bias detection pipeline for societal fairness in vision-language models
- GSoC 2025: CLDR LLM Validator – AI tool to validate multilingual locale data at scale using LLMs
Turning complex ML models into accessible real-world solutions.