Data Science

Experienced Data Scientist and an associate member of the Chartered Institute for IT with strong background in Machine Learning, Big Data Analysis, Process System Engineering, Automation and Advanced Process Control, Fault Tolerant Control Systems, Business Administration and Finance. An experienced University teacher in Chemical Engineering and a Fellow of the Higher Education Academy (FHEA).

I am also a professional member of IEEE with memberships of Control System, Instrumentation and Measurement, Robotics and Automation Societies. My most recent Data Scientist role was as a Research Fellow in Pharmaceutical Process Characterisation and Data Analysis at the School of Chemical and Process Engineering, University of Leeds. The research focus was to resolve issues of sticking in the manufacture of pharmaceutical tablet through Big Data Analysis using several machine learning algorithms. It was a collaboration between the University of Leeds and Pfizer Global Research Sandwich, and part of Advanced Digital Design of Pharmaceutical Therapeutics (ADDoPT) project involving select UK universities, SMEs and the UK pharmaceutical industry.

I am a proactive individual with great team spirit, dynamic teaching and research capabilities and core technical competencies in data-based fault detection and diagnosis using multivariate statistical process monitoring (MSPM) techniques such as dynamic principal component analysis (DPCA) and dynamic partial least squares (DPLS), Process Control, Data Analytics and Fault Tolerant Control Systems.

Some of my skills and competencies are:

• Excellent application skills in Matlab, Simulink, Python, JavaScript, C++, SQL, Orange and Aspen Hysys.
• Expertise in multivariate statistical modelling and data analysis using various machine learning algorithms.
• Proficient in the applications of Spotfire, MS Project, SPSS, MS Words, Excel and Power Point.
• Great computational, problem-solving, peoples’ management, administrative and time-management skills.
• Excellent skills in development, calibration and simulation of steady state and dynamic models using both Aspen Hysys and Matlab.
• Excellent grasp of principles underpinning chemical process dynamics and control, and fault tolerant control.
• Expertise in advanced process automation and control systems technology.
• Skilled in the development of PFD, P&ID, material balance and energy balance for chemical processes.
• Excellent understanding of industrial chemical and manufacturing operations and management.
• Excellent written and verbal communication skills.

Professional Data Science Roles

Research Associate in Deep Learning Web Based Portal for Medical Data Analysis (Since Sept. 2020): Newcastle University, UK

Working on the development of algorithms for determining medical markers based on movement data accumulated through stroke rehabilitation interventions. The role focuses on medical software development and associated research activities that will enable extraction of value, appropriate medical markers, from already gathered data. The role has also given me the opportunity to be involved in teaching and acting as Module Leader for CSC3221 – Programming for Games module, a C++ based programming module..

Research Fellow in Pharmaceutical Process Characterisation and Data Analysis (Feb – June 2019): University of Leeds, UK

Worked on resolving issues of sticking in the manufacture of pharmaceutical tablet through Big Data Analysis using several machine learning algorithms. It was a collaboration between the University of Leeds and Pfizer Global Research Sandwich, and part of Advanced Digital Design of Pharmaceutical Therapeutics (ADDoPT) project involving select UK universities, SMEs and the pharmaceutical industry.

PreScreen Software Update Consultant (Aug. – Nov. 2017)

Worked on PreScreen MATLAB-based software update to include Multivariate Parallel Coordinate Plot in the package for the Centre for Process Analytics and Control Technology (CPACT).

Chemometrics Calibration Model Consultant (June – Sept. 2016): Research & Knowledge Exchange Services, Univ. of Strathclyde, UK

Worked on Multi Sensor Technology (Muse-Tech) Project funded under the Seventh Framework Programme of the European Community for Research, Technological Development and Demonstration Activities to develop multi-block chemometric calibration models for multi-sensors suitable for use in the food processing industry.