Personal profile

Approach to teaching

As Lecturer in Mechanical Engineering at University of Brighton, I contributed to delivery of Energy Systems (ME410, level 4, 140 students), Engineering Mathematics (XE420, level 4, 40 student tutorials), Engineering Mathematics In-Year Retrieval (XE420, level 4) and Advances and Applications in Fluid Dynamics for Automotive and Mechanical Engineering (ME648/ME646, level 6, 12 and 45 students respectively) modules. In the Energy Systems module I was responsible for the design and delivery of the part introducing students to the fundamental concepts of fluid dynamic and aerodynamics of an aerofoil in particular. I delivered lectures and practical sessions, prepared the lecture notes and presentations, designed exam questions and solutions, assessed coursework and exams.

I aim to supplement each lecture by a short automated test to provide students with a feedback on their progress through the whole module. Additionally, I am looking to support self-study by developing interactive demonstrations using web-based dynamic mathematics software GeoGebra.

Research interests

My research interest are in mathematical and numerical modeling of multi-phase flows.

My research career started at Kazan Federal University, where I focusing on the mathematical and numerical modelling of gas-particle flows in porous structures between 2008 and 2015. During this period I developed high-performance numerical codes for Lagrangian particle tracking, using CUDA technology for parallel computing on graphics cards. As a result, performance of the calculations increased for up to 70 times comparing to single-threaded CPU version of the code.

As a Research Fellow at Advanced Engineering Centre at University of Brighton I developed a new method for calculating droplet number densities in gasoline engines and applied it to the analysis of experimental observations of sprays produced by high-pressure outwardly opening pintle injector. I developed a new model for heating and evaporation of a monocomponent droplet cloud based on the Fully Lagrangian Approach and implemented it into CFD code ANSYS Fluent. My ongoing work is focused on a two-way coupled model of gas-droplet flow based on Fully Lagrangian Approach.

Supervisory Interests

I am interested in supervising research students in mathematical and numerical modelling of fluid dynamics, with focus on multiphase flows with mass and heat transfer. I am particularly interested in novel applications of Machine Learning (neural networks) complementary to the traditional Computational Fluid Dynamics methods.

Education/Academic qualification

PhD, Kazan Federal University

Award Date: 27 Nov 2014


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