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ML Engineer at 7-Eleven Inc. • UC San Diego Alumnus • Turning data into decisions, one gradient descent at a time.
model.about()
Hi, I'm Param! I'm a Machine Learning Engineer at 7-Eleven Inc., where I build intelligent systems spanning Personalization, Recommender Systems, Computer Vision, Retrieval-Augmented Generation (RAG), and Generative AI — basically teaching machines to know what you want before you do. I hold a Master's degree from UC San Diego.
Driven by innovation, I love transforming bold ideas into tangible results and continuously pushing the frontiers of AI. My goal is simple yet ambitious: to create technology that not only excites but also makes a lasting, meaningful impact. When I'm not fine-tuning models, I'm probably fine-tuning my coffee-to-code ratio.
model.layers()
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AWS
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Git
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Jupyter
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Linux
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OpenCV
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Pandas
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Python
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PyTorch
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SKLearn
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TensorFlow
model.research()
The advent of high-throughput sequencing technologies and the availability of biological “big data” has accelerated the discovery of new protein sequences, making it challenging to keep pace with their functional…
bioRxiv
This work presents a technique developed by utilizing Generative Adversarial Networks (GANs) to generate Sign Language videos. Sign Language is the main mode of communication for people in the hearing impaired community...
(Optical Memory and Neural Networks, 2024/12, Volume 33, Issue 4)
model.predict()
Modified the patch embedding with Conv2D for efficient extraction, reducing overhead and speeding up training/inference. Unlike standard ViTs, this compact model is optimized for binary classification while maintaining strong performance.
Vision Transformer, PyTorch
Nebula-Nexus is a futuristic PDF question-answering assistant for research papers, powered by Retrieval-Augmented Generation (RAG). This tool allows users to upload any PDF and receive precise answers to their questions based on the content of the research paper.
Langchain, RAG, LLM, Transformers
Developed custom ensemble model combining pre-trained CNN for feature learning with a classification model on reduced features
VGG16, VGG19, ResNet, MobileNet, Boosting Algorithms, Flask, Python, TensorFlow
Build a Recommendation System using ML model (SVD) to provide recommendations to the users based on their interests and requirements, along with user login and authentication.
SVD, Python
Built a Flashcards WebApp that can be used similarly to traditional flashcards. Built using Flask, Python, Sqlite, etc. Please Note - The website may not be live anymore due to end of support from Replit for free app hosting.
Flask, Python, HTML, CSS, Sqlite
model.visualize()
