Pranav Sriram

Hello! My name is Pranav and I'm currently working as a Software Engineer at Stripe. I recently graduated with MS degree (specializing in computer vision) in Computer Engineering at UIUC, advised by Prof. Yuxiong Wang. My research interests focus in the area of computer vision, few-shot learning and meta-learning. During my undergraduate years, I worked on multiple research projects in the Human-Centered Autonomy Lab advised by Prof. Katherine Driggs-Campbell, focusing on predictive modeling and computer vision in autonomous driving. I am passionate about learning and especially fascinated by the high-impact of deep learning in solving real-world problems! I completed my Bachelor's degree with honors at UIUC, majoring in Computer Engineering.

E-Mail | Github | LinkedIn

Updates

Oct 2023	Started as a Software Engineer at Stripe!
Aug 2023	Our paper, "YouTubePD: A Multimodal Benchmark for Parkinson’s Disease Analysis", is accepted at NeurIPS 2023!
Aug 2023	Graduated with my Master's degree in Computer Engineering.
Apr 2022	Our paper, "CoCAtt: A Cognitive-Conditioned Driver Attention Dataset", is accepted at ITSC 2022!
Jan 2022	Our paper, "Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory Prediction", is accepted at ICRA 2022!
Aug 2021	Started my Master’s degree in Computer Engineer at University of Illinois at Urbana-Champaign with a focus on artificial intelligence and machine learning.
May 2021	Graduated with honors with a Bachelor’s in Computer Engineering from the University of Illinois at Urbana-Champaign.
May 2021	Started my internship at Arm, working as a software engineer intern to automate IP deliverables review process for continuous delivery.
Apr 2021	Started working on a research project for driver attention prediction with Yuan Shen and Niviru Wijayaratne, adapting state-of-the-art deep learning attention frameworks to incorporate driver intention and distraction as inputs.
Jan 2021	Started working on a research project for pedestrian trajectory prediction with Aamir Hasan, proposing a novel meta-path enhanced structural RNN that incorporates meta-paths in spatio-temporal graphs of pedestrian scenes.
Aug 2020	Started working as an undergraduate teaching assistant in ECE 391 (course on operating systems and x86).
Jan 2020	Started my internship at J.P. Morgan, working as a software engineer intern to create full-stack web application to visualize trading data.
Jan 2020	Started the City Scholars program, a selective work-study program for students which enables them to work part-time for a company and take a full courseload while living in Chicago.
Aug 2019	Started working as an undergraduate teaching assistant in ECE 385 (course on digital design and FPGAs).
May 2019	Started my internship at Select Portfolio Servicing, creating a user-intuitive data visualization application for non-technical users to create their own dashboards in a facile manner.

Publications

	YouTubePD: A Multimodal Benchmark for Parkinson’s Disease Analysis Andy Zhou, Samuel Li, Pranav Sriram, Xiang Li, Jiahua Dong, Ansh Sharma, Yuanyi Zhong, Shirui Luo, Maria Jaromin, Volodymyr Kindratenko, George Heintz, Christopher Zallek, Yu-Xiong Wang NeurIPS Datasets and Benchmarks Track, 2023. (NeurIPS 2023) denotes equal contribution paper project
	CoCAtt: A Cognitive-Conditioned Driver Attention Dataset Yuan Shen, Niviru Wijayaratne, Pranav Sriram, Aamir Hasan, Peter Du and Katherine Driggs-Campbell The 25th IEEE International Conference on Intelligent Transportation Systems. (ITSC 2022) * denotes equal contribution paper project
	Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory Prediction Aamir Hasan, Pranav Sriram, and Katherine Driggs-Campbell International Conference on Robotics & Automation (ICRA). (ICRA 2022) paper project

Experience

	Software Engineer @ Stripe Working on the Money Controls team to ensure transaction level compliance across Stripe!
	Software Engineer Intern @ Meta Developed an internal tool for verifying integrity and recommendations in Instagram using Hack. Developed a privacy-safe migration tool using Hack, React, and GraphQL to facilitate rollout of new Facebook Business features. Enhanced security and addressed privacy concerns to enable cross-functional usage of internal tools.
	Software Engineer Intern @ Arm Developed a library of Python modules to automate manual review of soft IP deliverables before delivery, to ensure that IP integration deliverables and directory structure conform to specified standards. Automated 15% of the manual review and collaborated with senior engineers to develop the library infrastructure. Created and modified CI pipelines in Jenkins to enable automatic code validation, linting and testing. Collaborated with team members to demonstrate viability of review automation with an end-to-end review pipeline.
	Software Engineer Intern @ J.P. Morgan & Chase Developed a full-stack web application using Java and Angular for time series visualizations. Implemented the back-end with Spring Boot, Apache Kafka, and MongoDB to consume and store financial data from multiple vendors and built a REST API to query the data. Demonstrated utility of a centralized financial database for internal applications to executive management.
	Software Engineer Intern @ Select Portfolio Servicing Developed a data visualization application that allows nontechnical users to create interactive dashboards with a quick and intuitive workflow. Implemented the front-end and back-end components of the web application with Angular 7, d3.js, and JavaScript. Created and modified SQL queries in SQL Server Management Studio to retrieve financial data metrics. Collaborated with team on UI/UX design and presented a minimum viable product with an intuitive workflow.

Teaching Assistant

Template credits: Saurabh and Yuan