Course Staff

Instructors

Peter Bartlett
http://www.eecs.berkeley.edu/~bartlett
e-mail: bartlett@eecs.berkeley.edu 
Office:  723 Sutardja-Dai Hall
Office Hours: Monday 1:30-2:30pm

 

Alexei (Alyosha) Efros
http://www.eecs.berkeley.edu/~efros
e-mail: efros@eecs.berkeley.edu 
Office: 724 Sutardja Dai Hall
Office Hours: Tuesday 6-7pm

 

GSI's

Faraz Tavakoli
e-mail: ftavakoli@eecs.berkeley.edu 
Office Hours: Fri 4-6 (Location: 373 Soda)
Discussion: 1 pm, 24 Wheeler (Sec 112)
Bio: It might seem rather obvious; but what you see on the left is an artist depiction of an Allosaurus, not Faraz!

Peter Gao
e-mail: pgao@berkeley.edu 
Office Hours: Wed 7-9PM (258 Cory) 
Discussion: Monday 11AM (106 Wheeler) and 12 PM (24 Wheeler)
Bio: Some people are born to be a 189 TA, some people work hard to become a 189 TA, and some people have 189 TA-ship thrust upon them. With Peter, it had been all three. Peter is a 4.5th year EECS undergrad. Peter has interned most recently at Khan Academy and Pinterest. Peter will be working at Cruise after graduation to work on self-driving cars. Peter derives pleasure from tangerines, writing, coding, laughing maniacally whilst holding dangerous power tools, running, swimming, postmodernist aesthetics, bikes, sarcasm, artificial intelligence, natural stupidity, lockpicking, and long lists, among other things. Peter's preferred gender pronoun is "it."

Yun Park
e-mail: yunpark93@gmail.com 
Office Hours: Tues 4-6PM (611 Soda)
Discussion: 4-5PM (3 Evans), 5-6PM (9 Evans)
Bio: Yun is a 4th-year undergrad in EECS. He has previously worked at Google and Pinterest and after graduation, he will work at Databricks, a start-up founded out of UC Berkeley AMPLab that focuses on efficiently extracting useful information from big data. Outside of computer science, he is a huge fan of the Golden State Warriors often attending games and a fan of hip-hop and rap listening to artists such as J. Cole and Kendrick Lamar.

Kevin Tee
e-mail: kevintee@berkeley.edu 
Office Hours: TTh 10-11AM, 651 Soda 
Discussion: 1-2PM (123 Wheeler), 2-3PM (9 Evans)
Bio: Kevin is a Masters student in EECS, working with Laurent El Ghaoui on sparse models for textual data. He is also interested in Bayesian statistics. He enjoys running, eating, learning, and long walks on the beach.

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Pat Virtue
e-mail: virtue@eecs.berkeley.edu 
Office Hours: Tues 2-4 pm, 504 Cory 
Discussion: 12 pm, 3 Evans (Sec 103) 
Bio: Pat is a 5th year Ph.D. student in EECS. He is researching ways to make MRI faster using compressed sensing, convex optimization, computer vision, and machine learning. Pat loves movies, trail running, and coaching little kid soccer and football.

Christopher Xie 
e-mail: chrisdxie@berkeley.edu 
Office Hours: Wed 2-3pm (611 Soda), 3-4pm (411 Soda) 
Discussion: 2pm (246 Dwinelle), 3pm (251 Dwinelle)
Bio: Chris is a 4th year undergraduate student in EECS. He is a TA this year because he really enjoyed being a TA for CS189 last year. He previously researched in Stuart Russell's group, and is currently researching in Pieter Abbeel's lab using nonlinear optimal control techniques to solve different types of motion planning problems. Chris (was) a competitive Taekwondo athlete, and plays keyboard in a funk band.

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Daniel Xu
e-mail: xudaniel11@gmail.com 
Office Hours: Mon 7-9pm, Cory 258
Discussion: 10 am, 105 Latimer (Sec 101) and 11 am, 310 Hearst Mining (Sec 102)
Bio: Daniel is a 4th year undergraduate student in EECS. He is a TA this year because he really enjoyed taking CS189 with Peter Gao last year. He previously interned at Goldman Sachs, Microsoft, and will be working at Addepar full time next fall. Daniel is a gym rat (come to the RSF in the mornings and say hi!), sucks at League of Legends and Starcraft II, and is looking for a group of students to play tackle football on Saturday afternoons.

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Yuchen Zhang
e-mail: zhangyuc@gmail.com 
Office Hours: Tues 7-9pm, Soda 411
Discussion: 10 am, 106 Wheeler (Sec 109) and 3 pm, 289 Cory (Sec 106)
Bio: Yuchen is a 4th year Ph.D. student in computer science. His research lies in the intersection of machine learning, optimization and statistics. A major part of his work explores the theoretical foundation of machine learning in distributed systems. He enjoys eating, running, playing Civilization 5 and reading science fictions.