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Roussos G Dimitrakopoulos

Title: 
Professor
Roussos G Dimitrakopoulos
Contact Information
Address: 

Frank Dawson Adams Bldg, Room 107
3450 University Street
Montreal, Qc, Canada H3A 0E8

Email address: 
roussos.dimitrakopoulos [at] mcgill.ca
Phone: 
514-398-4986
Degree(s): 

Canada Research Chair (Tier I) in Sustainable Mineral Resource Development
and Optimization Under Uncertainty

PhD 脡cole Polytechnique of Montreal
MSc University of Alberta
BSc University of Thessaloniki

Current research: 

Roussos Dimitrakopoulos holds a Canada Research Chair (Tier I) in Sustainable Mineral Resource Development and Optimization under Uncertainty since 2005, and is director of the COSMO - Stochastic Mine Planning Laboratory (). He works on stochastic simulation and optimization as well as artificial intelligence methods and applications in mine planning and production scheduling, along with the simultaneous optimization of industrial mining complexes and mineral value chains under uncertainty. He has published extensively, maintaining large competitive grants from the National Science and Engineering Research Council of Canada and a long-standing partnership with AngloGold Ashanti, BHP, AngloAmerican/De Beers, Agnico Eagle, IAMGOLD, Kinross Gold, Newmont, Vale SA and Vale Base Metals (COSMO Consortium) who support this research. He has taught and worked in Australia, North America, South America, Europe, the Middle East, South Africa and Japan. Specific current research topics include:

  • Simultaneous stochastic optimization of mineral value chains with new smart technologies, and dynamic planning options for strategic planning, including climate change related aspects
  • Self-learning decision support systems for mine production scheduling of mining complexes based on reinforcement learning and other AI based methods
  • Short-term production planning of mining complexes integrating new sensor and production information, and model updating capabilities
  • High-order, non-linear, non-Gaussian stochastic simulation models of geological risk
  • New statistical learning models, data analytics, and pattern recognition of geological information
  • New artificial intelligence framework for production planning and operations
  • Mine planning optimization integrating waste management and environmental risk and rehabilitation
  • Surface and underground mining methods in the context of the above
  • Exploring, modelling and integrating grinding and process ability characteristics for mine production optimization (geometallurgy)
  • Mineral value chain optimization with supply (mineral deposits) and demand (market) uncertainties
  • Real options and financial aspects of mine production and mine valuation
  • Advanced visualization
Selected publications: 

Courses: 

MIME 413 Strat Mine Plan W/Uncertainty 3 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer


MIME 425 Appl Stoch Orebody Modelling 3 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer


MIME 513 Mine Plan Optim Under Uncert 3 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer


MIME 522 Mineral Reserve Assess Techs 3 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer


MIME 525 Stochastic Orebody Modelling 3 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer


MIME 626 Applied Geostatistics 3 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer


MIME 631 Adv Stochastic Optim:Mine Plan 4 Credits
    Offered in the:
  • Fall
  • Winter
  • Summer

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