Hasnain Ali Arain

🏠 Orlando, Florida 32816

Hello, I'm Hasnain 👋

I am a Computer Science PhD student at the University of Central Florida and a Machine Learning Engineer dedicated to pushing the boundaries of artificial intelligence. My goal is to connect research with real-world applications, building AI systems that are both efficient and scalable.

I love creating technology that solves real problems and makes a positive impact. With a passion for innovation and entrepreneurship, I believe that well-designed AI has the power to transform industries and improve lives.

News

Aug 18, 2025	Commenced PhD Studies in Computer Science at the University of Central Florida
Jun 01, 2025	Our work on “On the Limitations of Vision-Language Models in Understanding Image Transforms” has been accepted at CVPR 2025w: Computer Vision in the Wild View
Oct 06, 2024	Delivered a workshop on Generative AI at Pak Angels: Essential Generative AI Training Program. View
Jul 14, 2024	Scored 145/160 in Duolingo English Test
Mar 07, 2024	Achieved a GRE score of 318: Quant 164, Verbal 154, AWA 4.0.

Latest Blog Posts

Aug 03, 2024	Building a Data Science Assistant with Llama 3 and Streamlit
Jun 28, 2024	Traditional Machine Learning Approaches: Machine Learning apart from Deep Learning
May 12, 2024	AI/ML Everywhere: A Beginner’s Guide

Checkout More

Selected Publications

On the Limitations of Vision Language Models in Understanding Image Transforms

Ahmad Mustafa Anis, Hasnain Ali Arain, and Saquib Sarfraz

Jun 2025

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Vision Language Models (VLMs) have demonstrated significant potential in various downstream tasks, including Image/Video Generation, Visual Question Answering, Multimodal Chatbots, and Video Understanding. However, these models often struggle with basic image transformations. This paper investigates the image-level understanding of VLMs, specifically CLIP by OpenAI and SigLIP by Google. Our findings reveal that these models lack comprehension of multiple image-level augmentations. To facilitate this study, we created an augmented version of the Flickr8k dataset, pairing each image with a detailed description of the applied transformation. We further explore how this deficiency impacts downstream tasks, particularly in image editing, and evaluate the performance of state-of-the-art Image2Image models on simple transformations

Engaged in exciting research projects with upcoming publications in the pipeline.