Course Staff


Alexei (Alyosha) Efros
Office: 724 Sutardja Dai Hall
Office Hours: Thu 5-6pm


Isabelle Guyon
Office: 329 Soda 
Office Hours: Wed 2:30-4:30p

Bio: Isabelle Guyon is an independent consultant, specialized in statistical data analysis, pattern recognition and machine learning. Her areas of expertise include computer vision and and bioinformatics. Her recent interest is in applications of machine learning to the discovery of causal relationships. Prior to starting her consulting practice in 1996, Isabelle Guyon was a researcher at AT&T Bell Laboratories, where she pioneered applications of neural networks to pen computer interfaces and co-invented Support Vector Machines (SVM), a machine learning technique, which has become a textbook method. She is also the primary inventor of SVM-RFE, a variable selection technique based on SVM. The SVM-RFE paper has thousands of citations and is often used as a reference method against which new feature selection methods are benchmarked. She also authored a seminal paper on feature selection that received thousands of citations. She organized many challenges in Machine Learning over the past few years supported by the EU network Pascal2, NSF, and DARPA, with prizes sponsored by Microsoft, Google, and Texas Instrument. Isabelle Guyon holds a Ph.D. degree in Physical Sciences of the University Pierre and Marie Curie, Paris, France. She is president of Chalearn, a non-profit dedicated to organizing challenges, vice-president of the Unipen foundation, adjunct professor at New-York University, action editor of the Journal of Machine Learning Research, and editor of the Challenges in Machine Learning book series of Microtome.



Nihar Shah

As head GSI, Nihar will be your first point of contact for any logistical issues.
Nihar B. Shah
Office Hours: Fri 2:30-3:30p (Soda Alcove 411) 
Discussion: Fri 12-1p (105 Latimer)
Bio: Nihar is a fifth year PhD student working in the areas of statistical learning theory and game theory with applications to crwodsourcing. Outside of work, Nihar likes playing football (soccer) and ultimate frisbee, and his favourite sport is kite fighting.

Brian Chu
Office Hours: Mon 6-7p in 246 Cory (in the lounge outside 246) 
Discussion: Fri 11-12p (3105 Etcheverry), 12-1p (3 Evans)
Bio: Brian is a 3rd year undergrad in Computer Science. He is TAing because CS 189 has been his favorite CS class so far. Last summer Brian interned at Twitter (so follow him @brrrianchu). When he isn't studying in Cory, you might find him playing ping pong in Cory, reading Hacker News, admiring his personal website, or coding.

Weicheng Kuo 
Office Hours: Thurs 2-3p (Soda 283H)  
Discussion: 1-2p (247 Dwinelle)
Bio: Weicheng's work has been focused on computer vision and image processing, where modern approaches rely heavily on machine learning and optimization. Weicheng is excited about TAing this class to learn Machine Learning together with you all.

Deepak Pathak 
Office Hours: Tues 6-7p (Soda 411) 
Discussion: Fri 9-10a (102 Latimer), 1-2p (70 Evans)
Bio: Deepak is a second-year graduate student in EECS, working with Prof. Trevor Darrell. He is interested in computer vision and machine learning, in particular learning large-scale visual models with fewer/weaker annotations using constraint based methods.

Shaun Singh 
Office Hours: Thurs 5-6p (651 Soda) 
Discussion: 11-12p (3113 Etcheverry)
Bio: Shaun is in his final year in EECS, trying to develop a deeper knowledge of statistical learning--especially with regards to NLP. He worked on Topic Modeling at Facebook this summer. He's particularly interested in making fancy neural embedding techniques work together with traditional linguistic knowledge, but with so many intriguing areas out there, its hard to stick to just one, so he's dabbling in computational biology. Shaun loves basketball, so you might run into him at the RSF.

Faraz Tavakoli
Office Hours: Fri 8-9a, (751 Soda)
Discussion: Fri 10-11a (101 Wurster)
Bio: It might seem rather obvious; but what you see on the left is an artist depiction of an Allosaurus, not Faraz!