Software Engineer

RISHABH RANJAN

510-***-**** **************@*****.*** https://www.linkedin.com/in/rishabh-ranjan-1113841b6/ https://github.com/RisHub1

EDUCATION

University of Michigan,

Ann Arbor

B.S. Computer Science,

B.S. Physics

Graduated Dec 2024

GPA: 3.7/4.0

TECHNICAL SKILLS

Languages: Python, Java, C++, HTML/CSS, Javascript, SQL, Ruby, bash scripting.

Frameworks/Libraries: Next.js, React, sklearn, Pytorch, scipy, CUDA

Developer Tools/Services: Git, CI/CD, Docker, Grafana, PostgreSQL, Tableau,

SELECTED COURSEWORK

Computer Science: Data Structures, Algorithms, Machine Learning, SW Eng

Physics and Math: Linear Algebra, Computational Physics, Numerical Methods

PUBLICATIONS

R. Ranjan, “Kβ XES Analysis using Bayesian Optimization”, APS User Conference, May ‘25.

R. Ranjan et. al “Kβ X-Ray Emission Spectra Analysis using Bayesian Optimization”, Journal of American Chemistry (under review)

WORK EXPERIENCE

Machine Learning Engineer Argonne National Laboratory Jan 2025 – Present

Working at a DOE national lab to simulate interactions between X-rays and metals using computational models

Trained a dense neural network using Pytorch to simulate absorption of X-rays by different metals, achieving same level of accuracy as state-of-the-art models with up to 90% runtime reduction

Used Bayesian optimization to determine critical structural properties of metals from their emissions

Machine Learning Researcher UM Galactic Dynamics Lab May 2023 – Present

Developed and implemented machine learning models for analyzing galaxy dynamics.

Classified growth rate of different structures in galaxies using unsupervised clustering techniques

Trained a neural network to determine mass of black holes in galaxies based on observational brightness data

Software Engineering Intern Synopsys May 2022 – Aug 2022

Addressed scaling limitations impacting the internal lookup application by restructuring its architecture

Build containerized versions of all services in its stack with Docker, linking them together to streamline deployment

Used Kubernetes to create new containers as needed, handling 10x the usage load of the original app

Deployed load balancing with Nodeport to control traffic between containers

Software Engineering Intern Synopsys May 2021 – Aug 2021

Engineered a logging service to standardize data formats and route large number of events (100,000+) from diverse internal systems to centralized storage.

Built a front-end user interface with React to track and analyze trends in error logs by querying events from MySQL database, catching internal use errors as fast as possible.

PROJECTS

Vision-Language Model Pipeline Aug 2024 – Present

Developed a pipeline in Python to highlight only image data that was important to the question being asked before passing into a VLM, enabling it to ignore unnecessary background information

Parallelized VLM using CUDA, dramatically reducing time needed to fine tune model

PROFILE

Computer scientist with multiple years of experience applying computational and machine learning techniques to a wide variety of problems. Designed and implemented AI models, optimization techniques, and physics-based simulations to solve complex, real-world issues. Proven ability to both lead independent projects and contribute to larger team-based programs in both research and industry settings.

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