University of Toronto St. George Campus - Civil Engineering
CoFounder, OasisCode Swiftender
Construction
Shayan
Nahrvar
Toronto, Ontario, Canada
Shayan Nahrvar is a Toronto-based Engineer, Entrepreneur and Business Strategist. He's the CoFounder of OasisCode Swiftender. Previously, Shayan was also the co-founder of Raise5, an award-winning fundraising platform endorsed by Sir Richard Branson.
Digital Document Manager
The flow of information in a large scale $350M design/build hospital project can often be overwhelming. As a tech-savvy Jr. Engineer, I was responsible for maintaining the document management systems and looking into Web-based Technologies that could be acquired for solidifying and streamlining the information flow in the project.
Head Instructor
My passion and drive for teaching (along with a bit of luck) gave me the opportunity to become one of U of T's youngest instructors (at age 23). I was the head instructor for a first year Engineering Physics course as well as a Linear Algebra course.
In spite of my lack of experience as an instructor, the students in my section performed well above average.
Co-founder
As any entrepreneur knows, there are countless roles involved with being an early-stage founder of a start-up. As the co-founder, one of my primarily roles was to ensure to the technical functionality and usability of the platform, along with on-going updates and changes. Aside from the technical perspective, I was responsible for recruitment and fundraising.
CoFounder, CTO
Architecting -> Building -> Testing -> Publishing -> Monitoring -> Iterating.
Doing all the good stuff that startup CTOs do (+ business strategy & leadership)
CoFounder and Product Strategist
Shayan worked at Oasiscode Swiftender as a CoFounder and Product Strategist
Master of Applied Science (MASc)
Civil Engineering
Created a virtual simulation technique in the field of mega-project construct management. This discrete event virtual simulation is capable of taking into account the possible realm of outcomes and producing a probability distribution with respect to the cost and duration of a project.
A case study was conducted in collaboration with Waterfront Toronto, where this technique was successfully executed.
Bachelor of Applied Science (B.A.Sc.)
Civil Engineering
Engineering
University of Toronto Engineering Faculty
The methodology of discrete-event simulation provides a promising alternative to solving complicated constructions systems. Given the level of uncertainty that exists in the early estimation phase of mega-projects regarding cost and risk, project simulations have become a central part of the decision-making and planning. This thesis compares discrete-event simulation to the traditional Monte-Carlo method through a case study.
University of Toronto Engineering Faculty
The methodology of discrete-event simulation provides a promising alternative to solving complicated constructions systems. Given the level of uncertainty that exists in the early estimation phase of mega-projects regarding cost and risk, project simulations have become a central part of the decision-making and planning. This thesis compares discrete-event simulation to the traditional Monte-Carlo method through a case study.
University of Toronto Engineering Faculty
The methodology of discrete-event simulation provides a promising alternative to solving complicated constructions systems. Given the level of uncertainty that exists in the early estimation phase of mega-projects regarding cost and risk, project simulations have become a central part of the decision-making and planning. This thesis compares discrete-event simulation to the traditional Monte-Carlo method through a case study.
University of Toronto Engineering Faculty
The methodology of discrete-event simulation provides a promising alternative to solving complicated constructions systems. Given the level of uncertainty that exists in the early estimation phase of mega-projects regarding cost and risk, project simulations have become a central part of the decision-making and planning. This thesis compares discrete-event simulation to the traditional Monte-Carlo method through a case study.