Teaching

Courses

• 2023, Term 1: CPSC 536M: Convex Analysis and Optimization
• 2023, Term 2: CPSC 406: Computational Optimization
• 2021, Term 2: CPSC 406: Computational Optimization
• 2020, Term 1: CPSC 536M: Optimization Theory
• 2019, Term 2: CPSC 406: Computational Optimization
• 2018, Term 1: CPSC 524F / MATH 604: Convex Analysis and Optimization

Current students

• Naomi Graham, PhD
• Jonas Jager, PhD
• Yao Kuang, MSc
• Nicholas Richardson, PhD

Former students and post-docs

• Zhenan Fan, PhD (2022). Duality in Structured and Federated Optimization: Theory and Applications
• Mia Kramer, MSc (2022). AtomicSets.jl: The calculus of support functions in Julia
• Huang Fang, PhD (2021). First-order methods for structured optimization, Baidu Research
• Bahbru Joshi, post-doc (2019-2021)
• Halyun Jeong, post-doc (2021), Adjunt Assistant Professor, UCLA
• Casie Bao, MSc (2019)
• Liran Li, MSc (2019)
• Yifan Sun post-doc (2019). Assistant Professor, Stony Brook University
• Gabriel Goh, PhD (2017). Optimization with costly subgradients, Scientist, OpenAI
• Ives Macedo, PhD (2015). Gauge duality and low-rank spectral optimization, Scientist, Amazon
• Ernie Esser, post-doc (2014)
• Ting Kei Pong, post-doc (2014). Associate Professor, Hong Kong Polytechnic University
• Nathan Krislock, post-doc (2013). Associate Professor, Northern Illinois University
• Alexandr (Sasha) Aravkin, post-doc (2012). Associate Professor, University of Washington
• Hassan Mansour, post-doc (2012). Research Staff, Mitsubishi Electric Research Laboratories
• Mark Schmidt, post-doc (2010). Associate Professor, University of British Columbia
• Mitch Crowe, MSc (2010)
• Ewout van den Berg, PhD (2009). Convex optimization for generalized sparse recovery, Scientist, IBM Research
• Marisol Garrido, MSc (2008)
• Shidong Shan, MSc (2008)
• Jelena Sirovljevic, MSc (2007)