P&S: Architectures & Algorithms for Health & Life Sciences - L1: Course Introduction (Spr 2026)
Why It Matters
Equipping engineers with architecture‑algorithm co‑design skills accelerates the translation of massive health data into scalable, energy‑efficient solutions, driving advances in precision medicine and related industries.
Key Takeaways
- •Rapid biotech advances generate massive health data requiring new computing.
- •Conventional systems struggle with performance, energy, and privacy constraints.
- •Course blends architecture, algorithms, and co‑design for bioinformatics challenges.
- •Hands‑on projects include profiling, optimization, and potential publication outcomes.
- •Prerequisites: C/C++ basics, Linux/SSH, and interest in efficiency.
Summary
Welcome to the first lecture of the ETH Zurich “Architectures & Algorithms for Health and Life Sciences” project‑seminar, presented by PhD candidate Nika Mansuriyasi. The session outlines the course’s scope, objectives, and its relevance amid accelerating biotechnological data generation.
Mansuriyasi explains that high‑throughput genome sequencing, medical imaging, and sensor streams are producing unprecedented volumes of biological data, but conventional computing faces performance, energy, privacy, and cost bottlenecks. The course aims to explore computational challenges across genomics, proteomics, neuroscience, and related domains, emphasizing computer‑architecture and algorithm co‑design.
The format combines optional weekly lectures, mentor‑guided hands‑on projects, and regular progress meetings. Students will profile and optimize algorithms on specialized hardware, document results in a Git repository, and present findings—potentially leading to publications. Prerequisites include basic C/C++ skills, Linux/SSH familiarity, and a drive to improve efficiency.
By equipping participants with interdisciplinary expertise, the course prepares the next generation of engineers to translate massive health data into scalable, energy‑efficient solutions, directly supporting precision medicine, agricultural monitoring, and broader life‑science innovations.
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