Arjhun Swaminathan

- Authored 6 peer-reviewed publications (e.g. Nature Communications, ICML 2026, SaTML 2026, TMLR) - Designed and implemented machine learning algorithms using privacy enhancing technologies - Maintained the research group's website by updating project pages, onboarding new members, and posting news on publications and events - Supervised a master's student on a secure Quantum Federated Learning thesis

Courses: - Privacy-preserving Methods in Biomedical Studies [Seminar] (WS22) - Introduction to Cryptography (SS23) - Secure Processing of Medical Data: Privacy-Enhancing Technologies in Practice - Anonymization Techniques [Practical Course] (WS23)

- Researched and pitched themes for short-form science explainer videos - Wrote scripts and collaborated with animators to clarify complex concepts - Assisted in SEO optimization

- Drafted scripts and infographics for web articles and video content

Research on Privacy-preserving Machine Learning with the MDPPML Research Group. Funded by the Federal Ministry of Education and Research, Germany (BMBF).

Grade: 91% (1.53) Master's Thesis | Supersingular Isogeny Diffie-Hellman Key Exchange Talks Given: - Riemann Surfaces and Elliptic Curve Cryptography | A ninety minute oberseminar talk | 25 May 2022 - Isogeny Based Cryptography | A ninety minute colloquium talk | 03 June 2022 - Shor's Algorithm | A ninety minute seminar talk | 24 June 2022

Grade: 91.9% (9.19) Graduated: First Class with Distinction Bachelor's Thesis | Resolution of Plane Curve Singularities: Blowing Up