R Sambasivam

Lead the development of quantitative, data science, and AI-driven solutions for trading across commodities and derivatives, covering pricing, optimization, execution, portfolio construction, and risk analytics, with a focus on value delivery at scale Design and grow a high-performing analytics organization, including talent development, practice building, and the establishment of robust model governance, engineering standards, and controls Translate state-of-the-art AI and quantitative advances, including machine learning, reinforcement learning, and generative AI, into production-grade decision intelligence, embedding domain knowledge and institutional expertise Drive the transition from exploratory analytics to scalable, product-centric solutions, deeply integrated with trading, risk, and technology platforms to improve decision quality, speed, and consistency, enabling a strategic shift from models as tools to analytics as embedded capabilities.

I lead the ambitious initiative of building advanced analytics practice at Petronas group which aims to usher in transformation and deliver value across the group. Leading the AI Centre of Excellence of the group to drive value delivery and business transformation.

- Developed Analytics Centre of Excellence - Helped to frame and delivered two large analytics transformation programs in two integrated steel plants - Worked with business units to identify opportunities, developed solutions and implemented them to achieve business value

(i) Process Modelling using CFD, Fluid mechanics (including turbulence modeling and multiphase flows, Boiling and phase-change) and Heat Transfer. (ii) Advanced analytics - Develop, deliver and implement data science projects related to process optimisation, Supply Chain, process safety and productivity, using Optimisation techniques, machine learning, system simulation and statistical techniques. (iii) Data Visualisation - Real time process data analysis to help in trouble-shooting, productivity and quality improvements.

- Computational Fluid Dynamics (single and multi-phase flows and turbulence modeling) and Heat Transfer analysis - Process and quality improvement projects combining first principle analysis and probability/statistical analysis/Evolutionary optimisation

(i) Operation and maintenance of boilers and a small steam turbine (ii) Maintenance of chemical plant equipment and utilities

Done under the guidance of Prof. Franz Durst Though the classical Navier-Stokes equations are considered to be complete, there are problems, of practical importance, such as gas flows through microchannels, shock-waves, Thermophoresis etc., which need special treatments. In this work, it has been shown that it is important to consider self-diffusion mass transport and the associated momentum and energy transports in the governing equations to obtain good predictions to the above mentioned flows. The resulting equations are called the ‘Extended Navier-Stokes equations’ and the path-breaking results obtained with these equations have pointed out the lacunae in the current understanding of flow physics of these problems. You may get the copy of my thesis from the link given below.