معرفی
Farzad Farnoud is an Assistant Professor in the Electrical and Computer Engineering and Computer Science Departments at the University of Virginia. His research focuses on information theory, coding theory, computational biology, and machine learning, with applications in DNA storage and genomic data analysis. He holds a Ph.D. in Electrical and Computer Engineering from the University of Illinois (2013) and postdoctoral experience at Caltech.
- Education:
- B.S. in Electrical Engineering (Sharif University of Technology, 2006)
- M.S. in ECE (University of Toronto, 2008)
- M.S. in Mathematics (UIUC, 2012)
- Ph.D. in ECE (UIUC, 2013)
- Postdoc at Caltech (2013–2016)
His research interests span information-theoretic analysis of biological datasets, coding for DNA storage, stochastic modeling of genomic mutations, and rank aggregation algorithms. Notable contributions include error-correcting codes for duplication channels and frameworks for metagenomic data analysis.
Recent work includes studies on short-duplication error correction (2023), active ranking algorithms (2022), and heterogeneous rank aggregation (2020). He has received the Robert T. Chien Memorial Award (2013) and the IEEE Data Storage Best Student Paper Award (2014).
Teaching includes courses on computational biology, statistical learning, and graphical models. He leads the Information Processing + Storage Lab, focusing on interdisciplinary challenges in data storage and analysis.
