Mikhail Soutchanski  

Mikhail Soutchanski, Professor

PhD in Artificial Intelligence, University of Toronto, Canada
M.Sc. (Diploma with Honors), Moscow Institute of Physics and Technology ( Phys-Tech), State University

Email:   Thank you for not sending me email!

Office: 245 Church Street, room ENG275 (NE corner, the 2nd floor)
Computer Science is located in George Vari ENG building.
Phone: (416) 979 5000 ext 7954   (leave voicemail)
General enquiries:
        Ms. Lori Fortune (416) 979-5000 ext.7411
        or Mr. Alex Zheltov (416) 979-5000 ext.7410

Mailing address:
245 Church Street, ENG281
Department of Computer Science
Ryerson University
Toronto, Ontario, M5B 2K3, Canada

"In theory, theory and practice are the same. In practice, they are not."
"The proper method for inquiring after the properties of things is to deduce them from experiments."
"In questions of science, the authority of a thousand is not worth the humble reasoning of a single individual"
"An error does not become truth by reason of multiplied propagation, nor does truth become error because nobody sees it"
"The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge"

International students:
Unfortunately I am unable to respond to emails about graduate admission or possibility of working with me. Please contact the Ryerson School of Graduate Studies or the CS Graduate Program Assistant. If you have been admitted to Ryerson, please feel free to reach out if you're interested in discussing research opportunities in my group. I would strong recommend to browse my recent research papers before you contact me and write why do you think our research interests match well. If you have published research papers, inform me.

Recent Teaching    

CPS 815 / CP8309:   Topics in Algorithms ,   an undergraduate course (Fall 2017).
CPS 721:   Artificial Intelligence 1  , an undergraduate course (Fall 2018).
CP8314 (Advanced AI) / CPS822     Artificial Intelligence 2: Dynamic Systems in Artificial Intelligence.
A graduate / advanced undergraduate course (Winter 2018).
CPS 841 / CP8319 / CPS824:   Reinforcement Learning (Winter 2019).
A graduate / advanced undergraduate course.
CPS 40A/B:   Undergraduate Thesis  , a two-term research oriented course (Winter 2019).
CP8310:   Directed Studies in Computer Science   (Fall 2016), a graduate course.
CPS 616:   Analysis of algorithms ,   an undergraduate course (Winter 2014).
CP8201:   Algorithms and Computability,   (Fall 2013), a graduate course.
CPS603:   Foundations of Semantic Technologies   (Winter 2011), an undergraduate/graduate course.
CPS 125:   Digital Computation and Programming  , an undergraduate course.

Research interests

Some of my publications

WWW links

Web mail