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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 École Polytechnique of Montreal
MSc University of Alberta
BSc University of Thessaloniki

Link(s): 
COSMO Laboratory
CRC Program
NSERC
GERAD
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 (http://cosmo.mcgill.ca/). 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: 

Publications

Courses: 

MIME 413. Strategic Mine Planning With Uncertainty.

Credits: 3
Offered by: Mining & Materials Engineering (Faculty of Engineering)
This course is not offered this catalogue year.

Description

Strategic decision-making for mine planning given uncertain metal supply from orebodies and commodity demand. Stochastic optimization techniques in mine design and production scheduling. Uncertainty quantification and orebody representation. Stochastic mine optimization in applications from open pit and underground metal mines. Introduction to sustainable development and utilization of mineral resources.
  • 3-3-3
  • Prerequisites: MIME 325, MIME 419, MIME 425
  • Restriction(s): Not open to students who have taken MIME 513.

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MIME 425. Applied Stochastic Orebody Modelling.

Credits: 3
Offered by: Mining & Materials Engineering (Faculty of Engineering)
This course is not offered this catalogue year.

Description

Representing uncertainty in orebody models and shortcomings of conventional methods including reserve reporting and mine planning. Stochastic spatial sequential simulation methods. Joint simulation of multiple correlated elements. Simulation material types. Introduction to geometallurgical modelling. Additional drilling, reserve classification, grade control and mine planning optimization. Risk quantification in life-of-mine production schedules.
  • 3-3-3
  • Prerequisite(s): (MPMC 326 or CIVE 208) and (MPMC 329 or MIME 329)
  • Restriction(s): Not open to students who have taken MIME 525.

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MIME 513. Mine Planning Optimization Under Uncertainty.

Credits: 3
Offered by: Mining & Materials Engineering (Faculty of Engineering)
This course is not offered this catalogue year.

Description

Strategic mine planning and optimization under uncertain demand and supply. Modern optimization techniques in mine design and production scheduling. Metal supply and orebody modelling. Market forecasting and planning with flexibility. Valuing information. Stochastic mine optimization and applications in open pit and underground metal mines.
  • This course in the Faculty of Engineering is open only to McGill students.
  • This course in the Faculty of Engineering is open only to McGill students.
  • 3-3-3
  • Prerequisite: Permission of instructor.
  • Restriction: Not open to students who have taken MIME 413.

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MIME 522. Mineral Reserve Assessment Techniques.

Credits: 3
Offered by: Mining & Materials Engineering (Faculty of Engineering)
This course is not offered this catalogue year.

Description

Techniques in mineral reserve assessment.
  • (3-3-3)
  • Prerequisites: COMP 208 or equivalent, MIME 209 or equivalent

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MIME 525. Stochastic Orebody Modelling.

Credits: 3
Offered by: Mining & Materials Engineering (Faculty of Engineering)
This course is not offered this catalogue year.

Description

Uncertainty in modelling orebodies. Conventional modelling methods. Ore reserve estimation and risk. Geostatistical basics. Sequential simulation methods. Fast and efficient simulation of large orebodies. Simulation of multi-element deposits. Simulation of geology. Geometallurgical modelling. Integration and effects on mine planning and financial evaluation. Drilling optimization; reserve classification; grade control. Practical applications.
  • (3-3-3)
  • Prerequisite: Permission of instructor
  • Not open to students who have taken MIME 425.

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MIME 626. Applied Geostatistics.

Credits: 3
Offered by: Mining & Materials Engineering (Graduate Studies)
This course is not offered this catalogue year.

Description

Review of applied geostatistics.

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MIME 631. Advanced Stochastic Optimization in Mine Planning.

Credits: 4
Offered by: Mining & Materials Engineering (Graduate Studies)
This course is not offered this catalogue year.

Description

Uncertainty and risk in mine design and production scheduling. Conventional mine optimization methods and flaws. Mine planning and sustainable mining under uncertainty. Combinatorial optimization and algorithmic methods in mine production scheduling. Real options and decision making in mine planning. Mine waste deferment methods. Global and local optimization of mining processes.
  • Prerequisite: Permission of instructor.
  • (3-3-6)
  • Prerequisite: Permission of instructor.

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