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

Quotes
"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

Commonsense Knowledge Representation and Reasoning. More specifically, I'm interested in Reasoning about Actions and Change. I'm exploring several computational tasks such as lifted planning and causal reasoning about hybrid systems with application to diagnosis.
Multi-disciplinary research: I'm interested in solving the organic chemistry synthesis problem using a variety of techniques from AI planning. More generally, I'm interested in developing AI techniques to facilitate discovery in health and natural sciences.
Reasoning about actions and events with applications to problem solving. I was developing modular and taxonomic representations that can facilitate implementing large-scale logical theories for reasoning about effects of actions/events.

Some of my publications

WWW links

Cognitive Robotics Group at the University of Toronto.
A Prolog interface to Sony's AIBO robots.
Graduate Program in Computer Science and Engineering, York University, Toronto, Ontario, Canada. I'm an Adjunct Professor supervising graduate students. This brief brochure provides some details about this graduate program.
Mathematical logic around the world
The Open Logic Project supported by the University of Calgary Faculty of Arts and the Campus Alberta OER Initiative.
The Openproof Project at the Center for the Study of Language and Information (CSLI), Stanford University.

Web mail