Scientific Computing
Python pipelines for imaging data, experiment metadata, and X-ray analysis workflows.
Divyanshu Tandon
Most software engineers never have to think about whether a stream of liquid, thinner than a human hair, is stable enough to survive an X-ray beam. I do. I am Divyanshu Tandon, a Computer Science student at Arizona State University and an undergraduate researcher with CXFEL and ASU Biodesign, where my code lives close to the experiment: detector frames, h5 files, microjet videos, calibration details, and the strange failure modes that only show up when hardware and software meet.
My work centers on scientific software for X-ray free-electron laser imaging and biomolecular experiments. I build Python tools with NumPy, h5py, PyQt/PySide, and visualization workflows that help researchers inspect detector data, process high-speed imagery, and quantify microjet behavior, including velocity, diameter, breakup, and stability. At SLAC's LCLS beamline, I saw how small software decisions affect real data collection, not just a demo dataset.
Outside the lab, I build product-style software too: React interfaces, FastAPI services, backend APIs, and full-stack applications. I like problems where the interface has to stay usable, the computation has to be correct, and the system has to earn trust from people doing difficult work.
- 2027
- BS Computer Science, ASU
- LCLS
- SLAC beamline and sample-delivery research
- 2025
- Lab on a Chip publication
Open to internships, research roles, and software engineering opportunities.
Research Software
In XFEL sample-delivery work, I write software that measures liquid microjet velocity, diameter, angle, and breakup behavior from high-speed imaging data. My day-to-day stack includes NumPy, pandas, h5py, PyQt/PySide, and image-processing workflows tied to real experimental constraints.
I have supported beamline and lab work across ASU Biodesign, CXFEL, and LCLS at SLAC, from detector visualization and data collection support to documentation that helps a research team understand what the code is doing and why it matters.
Core Areas
Visualization Interfaces
Qt tools for detector views, interactive annotations, and research-facing data inspection.
Product Engineering
React and FastAPI systems that make technical information searchable and usable.
Selected Projects
Scientific Software
2025 - Present
Reborn Visualization Framework
Contributed to an open-source Python framework used for processing, visualizing, and analyzing X-ray diffraction detector data from XFEL experiments.
- Improved Qt PADView detector ring annotation and interactive labels.
- Resolved PyQt/PySide rendering and dependency issues across Linux environments.
Full Stack
May 2026
CoverMyPharma
Built a healthcare policy platform with React and FastAPI for searching insurer policy documents, analyzing coverage rules, and retrieving relevant policy evidence.
- Integrated Auth0 authentication and protected REST APIs.
- Added AI-powered PDF analysis for medical policy extraction.
Research Computing
2026
Microjet Image Analysis
Developed Python tools for liquid microjet characterization in XFEL sample-delivery experiments.
- Computed jet velocity, diameter, breakup behavior, and angle.
- Automated preprocessing, metadata extraction, and visualization workflows.
Algorithms
2025
Graph Pathfinding Engine
Built a graph-based routing engine for shortest-path computation using Dijkstra's algorithm, adjacency lists, and min-heap optimization.
- Built CLI workflows for loading graph data and reconstructing traversals.
- Focused on scalable path computation and clear algorithmic design.
Experience
Research Assistant, ASU Biodesign
Process liquid microjet imaging datasets, support instrumentation setup and calibration, and help coordinate data collection across active structural biology experiments.
Undergraduate Researcher, CXFEL
Build Python tools with NumPy and PyQt for biomolecular imaging, data analysis, automation, and X-ray diffractive imaging workflows.
Summer Researcher, SLAC LCLS
Operated and optimized ultra-thin sheet-jet injectors for in-solution single-particle imaging and assisted with detector configuration and data acquisition.
Data Analyst, MaRTy Fieldwork
Collected and validated MaRTy temperature data for shade analysis, transforming field data into insights for sustainable urban heat resilience.
Lab on a Chip
Ansari, A. et al. including Divyanshu Tandon. Lab on a Chip, Advance Article, 2025. DOI: 10.1039/D5LC00063G.
Read DOI
Gallery
Technical Stack
Languages
Python, Java, C, C++, JavaScript, TypeScript, SQL, HTML, CSS
Frameworks
React, FastAPI, REST APIs, PyQt, PySide, JUnit, Auth0
Scientific Tools
NumPy, pandas, h5py, image processing, detector visualization, cross-correlation analysis
Systems
Linux, Bash, Git, GitHub, GitLab, MySQL, CLI workflows
Get in Touch
Open to software engineering internships, research software roles, and collaborations around scientific computing, data workflows, and full-stack tools.