Shervin Teymouri

Shervin Teymouri, M.Eng., P. Eng.




Education

The University of British Columbia UBC, 2005, BASc, Geological Engineering
The University of British Columbia UBC, 2008, MEng, Mining Engineering

Biography

An entrepreneur at heart, Mr. Teymouri has experience as a consultant, lead design mining engineer, and also an operations specialist as a mining engineer for base, precious, and industrial metals projects. His combined financial and mining engineering experience has strengthened his credibility to interpret, evaluate, and comment on the feasibility of mining projects, whether underground or open pit. He had several leadership roles with projects in BC and Yukon Territories focused on heading the teams responsible for environmental, engineering, reclamation, tailings management, and mine development.

His involvement in mining finance and strategic mine planning has focused on the maximization of mine returns and aligning mine planning with project financial objectives. He has performed numerous mining project valuations and has been part of numerous feasibility studies and project due-diligence reviews globally.

Mr. Teymouri is an Adjunct Professor of mining engineering and lecturer at the University of British Columbia, Faculty of Applied Science, Norman B. Keevil Institute of Mining since 2013. He has held advisory roles with Yukon First Nations Chamber of Commerce (YFNCC) as mining advisor and speaker. He also seats on the board of several private and public mining companies.

Research Interests

Underground Rock Mechanics – Artificial Intelligence and Rock Mechanics
Capital Cost and Operating Cost Estimation, Economic assessments and Artificial Intelligence

Contact Information

Email: Shervin.teymouri@ubc.ca

Interests

Feasibility Studies, Rock Mechanics, Artificial Intelligence, Neural Networks, Cost Estimation, Financial Models and Economic Analysis, Mining Ventures, Mining Finance, Venture Capital

Teaching

Mine 302 and Mine 506 – Underground Mining and Design
Mine 304 and 504 – Rock Fragmentation

Awards

Mineral Economics and Management Society, 2008: Commodity Price Prediction Using AI and Neural Networks

Selected Publications