Arvid Gollwitzer

Additional information

Short Bio

Arvid E. Gollwitzer is a young scholar and entrepreneur. His current research interests are in bioinformatics, clinical genomics, computer architecture for medical applications, drug delivery, acoustic robotics for life sciences, and the early detection of cancer. Throughout his graduate studies in Electrical Engineering and Information Technology at ETH Zurich, he specialized in clinical (meta)genomics, drug delivery techniques, and early-stage cancer detection. Arvid also co-founded NextGuidecall_made, where he develops AI assistance technology for visually impaired individuals. His professional experience, teaching, and graduate studies include roles at CERN and the SAFARI Research Group of ETH and CMU. Arvid has published several works on bioinformatics, metagenomics, and clinical genomics. He also holds an excellence scholarship from the Swiss Study Foundation, an organization dedicated to promoting the top 3% of students based on their exceptional academic impact, creativity, and character. 

At ETH Zurich, Arvid teaches a project- and research-driven course on Clinical Genomics, offered every semester for up to 12 students.

Research Interests

• Bioinformatics
• Computational Genomics
• Clinical Genomics & Metagenomics
• Early Detection of Cancer
• Human Microbiome
• Targeted Drug Delivery
• Acoustic Robotics
• Biomedical Engineering
• Health Sciences and Technology

Selected Papers

Arvid E. Gollwitzer, Mohammed Alser, Joel Bergtholdt, Joel Lindegger, Maximilian-David Rumpf, Can Firtina, Serghei Mangul, Onur Mutlu. MetaTrinity: Enabling Fast Metagenomic Classification via Seed Counting and Edit Distance Approximation. arXiv:2311.02029call_made

Maximilian-David Rumpf*, Mohammed Alser*, Arvid E. Gollwitzer*, Joel Lindegger, Nour Almadhoun, Can Firtina, Serghei Mangul, Onur Mutlu. SequenceLab: A Comprehensive Benchmark of Computational Methods for Comparing Genomic Sequences. arXiv:2310.16908call_made

Nika Mansouri Ghiasi, Jisung Park, Harun Mustafa, Jeremie Kim, Ataberk Olgun, Arvid E. Gollwitzer, Damla Senol Cali, Can Firtina, Haiyu Mao, Nour Almadhoun Alserr, Rachata Ausavarungnirun, Nandita Vijaykumar, Mohammed Alser, Onur Mutlu. (2022). GenStore: a high-performance in-storage processing system for genome sequence analysis. In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '22). DOI:10.1145/3503222.3507702call_made.

All Publications

Google Scholar - Arvid E. Gollwitzercall_made

Entrepreneurship 

Social Media

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