Mikhail Soutchanski, ProfessorPhD in Artificial Intelligence, University of Toronto, Canada
Email: Thank you for not sending me email!
245 Church Street, room ENG275 (NE corner, the 2nd floor)
A long-term mission of Soutchanski's Advanced Aritificial Intelligence (AI) Lab:
Theory is when you know everything but nothing works. Practice is when everything works but no one knows why. In our Advanced AI lab theory and practice are combined: computer programs that we develop have to work and we must know why. (Acknowledgement: this is an improvement of a well-known quote.)
Some of my
New KR-2022 Tutorial: Hybrid Temporal Situation Calculus for Planning with Continuous Processes @ the Federated Logic Conference (FLoC-2022).
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, feel free to reach out if you're interested in discussing research opportunities in my group. I would strongly 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 yourself, inform me.
Artificial Intelligence 1 , an undergraduate course (Fall 2021).
CP8314 (Advanced AI): Dynamic Systems in AI, a graduate course (Fall 2021)
CPS822 Artificial Intelligence 2: advanced undergraduate course (Winter 2022).
CPS 824 / CP8319:
Reinforcement Learning (Winter 2019).
A graduate / advanced undergraduate course.
CPS 815 / CP8201: Topics in Algorithms , an undergraduate course (Fall 2019).
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 (Winter 2017), an undergraduate course.
"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"
"The truth is simple. If it was complicated, everyone would understand it."
"There is nothing more practical than good theory"
"No more causes of natural things should be admitted than are both true and sufficient to explain their phenomena." (Rule 1)
"Therefore, the causes assigned to natural effects of the same kind must be, so far as possible, the same." (Rule 2)
"We learn more and more about less and less, and less and less about more, until we know everything about nothing and nothing about everything."
"If there occurs some change in nature, the amount of action necessary for this change must be as small as possible."