▶ Identified relationships between biochemical reactions in clot lysis, allowing the industrial partner to adjust the experimental procedure to meet their specific needs.▶ Suggested optimal dosages for lysis drugs across various scenarios, including flow conditions that the industrial partner was unable to replicate experimentally.▶ Sparked interest in additional investment by presenting results to a variety of academic and industry stakeholders at 4 conferences and high-level director meetings.▶ Created digital twins of industrial bioreactors, offering valuable insights while avoiding substantial experimental expenses, saving up to $14k per experiment, with experiments typically conducted once a month.▶ Identified performance limitations in mid-scale bioreactors and proposed a new design, improving performance by up to 30%.▶ Created numerical models of clot lysis under static and flow conditions in different setups. The static models replicate CSL Ltd experiments, while the flow models represent more realistic blood flow scenarios.▶ Analysed data on biochemical reactions in clot lysis, involving more than 20 variables and their sensitivity to drug dosages, using machine learning techniques in Python.▶ Gathered and analysed bioreactor scaling data, focusing on experimental costs for trials.▶ Developed digital twins of bioreactors at 2 scales, simulated multiple scenarios and utilised the university's HPC system, Spartan.▶ Utilised in-house Python codes and visualization tools (including Power BI) to explore performance discrepancies between mid- and small-scale bioreactors, in relation to flow behaviour across 16 settings.▶ Identified performance limitations in bioreactors and refined the model using experimental data from an industrial partner (CSL).

▶ Achieved a low failure rate among master students, with only 5% of students not passing the course.▶ Designed structured and user-friendly educational materials that are currently used by tutors.▶ Created an interactive platform with animations and quizzes, used by over 1k bachelor’s students and other platform users, increasing remote students to help address the student housing crisis.▶ Improved student engagement with the subject indicating their desire to continue their education at the university, with an indicative total course fee of over $140k for the master’s program.▶ Prepared and delivered teaching materials for the Fluid Dynamics course (MCEN90008) for second-year master's students, both as part of a teaching team and independently.▶ Conducted coding workshops using MATLAB, training 30+ students on techniques and best practices.▶ Assessed and graded assignments, providing analyses of student performance using Power BI and Excel.▶ Designed course materials for the Fluid Mechanics course (ENGR30002) for remote bachelor's students, ensuring accessibility and clarity for over 100 learners.▶ Prepared educational videos for the university’s online learning platform, Canvas.

▶ Provided tutoring services in mathematics and computer science to students of various academic levels.▶ Developed personalised lesson plans to meet individual student needs and learning objectives.▶ Assisted students in preparing for exams and improving their understanding of complex concepts.▶ Monitored student progress and adjusted teaching strategies accordingly.

▶ Developed an analytical model for ice formation on transmission lines, reducing prediction errors by 10%.▶ Enhanced the start-up company's organisational performance by up to 35%, allowing it to achieve residency status at the Skolkovo Foundation. This status provides the company with tax and customs benefits. In 2019, residents of the foundation collectively earned over US$1.5b.▶ Published 2 papers in engineering journals, leading to an increase in the start-up's market value and reliability at the Skolkovo Institute and helped advance my group leader’s career, leading to their promotion to associate professor a year later.▶ Conducted a literature review on transmission line coatings, analysed multiple studies to identify best practices and innovative solutions, and prepared a substantial data frame in Excel.▶ Improved the analytical model of ice formation on transmission lines using in-house Python codes.▶ Assisted in preparing facilities for wind tunnel experiments. Prepared transmission line coating samples for experiments, handling 5 samples to maintain integrity.▶ Assisted with documentation and management at the start-up company, handling over 10 administrative tasks aimed at enhancing company credibility.▶ Prepared reports and engineering papers, creating documents to communicate findings and solutions.

▶ Performed numerical modelling of multiphase flow to replicate wind tunnel experiments. These experiments were designed to investigate water droplets in clouds before they freeze on aircraft surfaces.▶ Assisted with the experiments by controlling the flow velocity in the tunnel, water injection and analysing images of the droplet distribution using MATLAB.▶ Wrote a report and presented findings at 5 scientific and industrial conferences.▶ Established collaborations with researchers from 2 scientific institutes to foster collaborative efforts.▶ Increased team morale through organising weekly after-work activities and team-building events.▶ Developed a mathematical model of the wind tunnel that enables nozzle position adjustments without incurring the high costs of experiments saving approx. $5k under challenging conditions, such as a cold temperature room with an operational wind tunnel.▶ Improved understanding of aircraft icing mechanisms, providing broader perspectives on the project development, including enhancing de-icing technologies and ensuring safer aircraft operation in adverse weather conditions.▶ Facilitated interest from industrial, scientific, and media sources in the project, resulting in a grant application in collaboration with 2 other research groups and an article published in a local newspaper.▶ Enhanced team dynamics, fostering positive interactions among members of various ages and increasing support from senior team members toward younger colleagues.