About

I am a Master’s student in Computer Science at the University of Massachusetts Amherst, focusing on innovative solutions in Computer Vision and Natural Language Processing. I specialize in enhancing image captioning, integrating visual question answering (VQA) models, and improving text-to-image generation using deep learning. I am seeking Fall 2024 internships, co-op opportunities, and full-time positions starting in 2025 to apply my expertise.

I am always open to building meaningful connections with professionals who share similar interests and ambitions, as well as with recruiters who value collaborative relationships. I am eager to contribute to your team’s success and would be delighted to connect on LinkedIn. Feel free to reach out to me at rahulsaxena@umass.edu.

My work and research

My work primarily revolves around applying deep learning to solve complex problems in Computer Vision and Natural Language Processing. I have specialized in projects that enhance the performance and accuracy of image captioning systems, integrate Visual Question Answering (VQA) models, and improve the text-to-image generation process.

With over four years of software development experience in the healthcare and fintech sectors, I have had the privilege of working with industry giants like Philips and PayPal. During my tenure at Philips, I deployed machine learning models for automated customer complaints classification, leading a team to develop and implement medical imaging pipelines that significantly improved diagnosis speed and accuracy. I also built predictive models that prevented system downtimes and optimized resource allocation, resulting in substantial cost savings.

At PayPal, I developed an auto-remediation framework that reduced downtime and operational costs, alongside creating a full-stack web application for monitoring and resolving failures in critical data processing systems. My work has consistently demonstrated my ability to apply cutting-edge technology to solve complex, real-world problems.

In my research, I have worked on advanced camouflaged object detection in limited data settings, improving segmentation mask accuracy through innovative data augmentation techniques. My other significant project involved developing a prompt scoring system to evaluate the specificity of prompts used with Large Language Models (LLMs), which led to improved performance metrics and more accurate prompt evaluations.

My background and history

I am a Master’s student in Computer Science at the University of Massachusetts Amherst, where I maintain a 4.0 GPA. My focus lies in pioneering solutions in Computer Vision and Natural Language Processing (NLP). My academic journey has been shaped by a strong foundation in deep learning, neural networks, and machine learning, which I have applied to enhance image captioning, integrate Visual Question Answering (VQA) models, and improve text-to-image generation systems.

Prior to my master’s, I completed my Bachelor of Engineering (Hons.) in Electrical Engineering from Birla Institute of Technology and Science, Pilani (BITS Pilani), where I was a recipient of the BITS MCN Scholarship and the I.J Nagrath Project Grant for the NASA Radio Jove Project. My educational background has equipped me with a diverse skill set that spans multiple domains of computer science and engineering.

My other pursuits

Outside of my academic and professional life, I am an avid runner and cyclist. I have participated in numerous Half Marathons and Marathons in cities like Bangalore and Delhi, and have competed in elite trail running events across India, including the Malnad Ultra and the SRT Ultra Marathon. These activities not only help me stay physically fit but also provide a mental reset from the demands of my work.

I am also passionate about photography, where I blend art with science. I enjoy experimenting with tools like Adobe Photoshop and Lightroom, as well as leveraging AI-driven solutions like photo-realistic GPT to enhance my images. Photography allows me to capture the beauty of the world around me and express my creative side.