Summary
Alvan Arulandu is a versatile researcher-engineer with six years of experience bridging applied machine learning, mathematics, and systems engineering across academia, government labs, and startups. He has worked on quantum algorithms and robust estimation at the University of Washington while contributing to Neuralink and teaching advanced math and CS at Harvard, demonstrating a mix of deep theory and practical implementation. Past projects include physics-informed neural networks, generative U-Nets for automating CFD, optimal vaccine allocation models, and end-to-end product work from prototyping to production at a YC-backed startup. Comfortable leading small engineering teams and mentoring students, he also has hands-on experience in propulsion and DevOps, showing an appetite for cross-domain problem solving. Alvan favors fast, weekend-sized iterations and values conversations as a way to navigate long-term goals, so he’s as likely to build a quick prototype as he is to dive into a research proof. Based in Herndon, VA, he combines academic rigor with entrepreneurial grit and an unusual breadth that spans quantum learning to rocket plumbing.
6 years of coding experience
5 years of employment as a software developer
Bachelor of Arts - BA, Mathematics and Computer Science, Bachelor of Arts - BA, Mathematics and Computer Science at Harvard University
Advanced High School Diploma, N/A, Advanced High School Diploma, N/A at Thomas Jefferson High School for Science and Technology
Certificate of Quantum Excellence, Quantum Computing, Quantum Machine Learning, Certificate of Quantum Excellence, Quantum Computing, Quantum Machine Learning at 2021 Qiskit Global Summer School on Quantum Machine Learning
English, Spanish, Tamil