Current students

Area of Research:

Information Systems

Committee Chair:

Stan Potapenko, Civil & Environmental Engineering

Examining Committee:

Stanko Dimitrov, Management Sciences (supervisor)

Fatih Erenay, Management Sciences

James Bookbinder, Management Sciences

Liping Fu, Civil & Environmental Engineering

Area of Research

Management of Technology

Committee Chair

Sagar Naik, Electrical & Computer Engineering

Examining Committee

Frank Safayeni, Management Sciences

Elizabeth Jewkes, Management Sciences

Robert Duimering, Management Sciences

Nada Basir, Conrad Centre - CBET
 

The University wide competition starts with our department-level heat. We want Management Sciences to be well represented on the university stage!

The 3MT is a university-wide competition for research-based master’s thesis and doctoral students.  Competitors will have 1 slide and 3 minutes to explain their research to a non-specialist audience.

This year we will be running our own department-level heat on February 27, 2018 at 2:00 pm in CPH 4335 with prizes and a winner moving on to the university-wide competition.

In recent years, long wait times for healthcare services have become a challenge in most healthcare delivery systems in Canada.

Existing leadership theories tend to explain that leaders induce others to follow as a function of one or more of the following:

i) A specific set of traits possessed by the leader (e.g., charisma);

ii) Different types of behaviours the leader exhibits depending on the situation (e.g., a focus on tasks or a focus on relationships);

iii) Specifics relating to the structure and dynamics of the leader-follower relationship (e.g., economic, social, or psychological exchange, or a 'customized' focus on the 'follower').

Supervisor(s):

Fatih Erenay, Management Sciences

Osman Yalin Ozaltin (remote), Management Sciences

Pallets are the most common form of packaging in the retail industry. Their building involves the solution of a three-dimensional packing problem with side practical constraints such as item support and pallet stability, leading to what is known as the mixed-case palletization problem. Motivated by the fact that solving industry-size instances is still very challenging for current methods, we propose a new solution methodology that combines data analysis at the instance level and optimization to build pallets.