Hello! I’m Nicolette, a passionate Data Scientist with a robust background in Engineering and Computer Science, and a PhD in Intelligent Transportation Systems. Originally from the sunny island of Malta, I’ve always been driven by the desire to solve real-world challenges through data. Throughout my career, I've developed innovative systems and have applied my expertise across various projects in data analytics, AI, machine learning, and deep learning. My approach is rooted in the belief that understanding and leveraging data can solve almost any problem, from optimising transportation systems to driving business decisions.
Supervisors: Professor Mohammed Quddus, Professor Stephen Ison , Dr Andrew Timmis
Dissertation: Developing Vehicle-Based Traffic Conflict Prediction Algorithms Using Deep Learning
Dissertation: Spatio-Temporal Modelling Applied to Marine Pollution Data
Research Project: Modelling and Analysis of the Interactions between Air Pollution and Traffic Flow
As a Lead Data Scientist, I create scalable data pipelines and optimise big data workflows on platforms like Databricks and Azure. Leveraging Python, machine learning, and advanced analytics, I automate processes and enhance predictive capabilities. I lead Agile data science projects, delivering impactful solutions on time, and develop computer vision applications for traffic monitoring and infrastructure safety. I also supervise PhD students, guiding research and fostering innovation in intelligent transportation systems. Through interactive Power BI dashboards, I transform complex data into actionable insights, supporting strategic decision-making and driving business growth.
Project: Cooperative cOllision avoidaNce in a Connected and Autonomous Vehicles Environment (CONCAVE)
I led the CONCAVE project, which focused on enhancing cooperative collision avoidance in connected and autonomous vehicle (CAV) environments. My role involved developing machine learning algorithms and leveraging big data techniques to drive CAV operations towards zero fatalities. I collaborated extensively with academic peers and industry partners, published my findings, and actively contributed to securing research grants. Additionally, I mentored and guided both undergraduate and postgraduate students through teaching and supervision, inspiring the next generation of researchers.
Project: Connected and Autonomous Vehicles Infrastructure Appraisal Readiness (CAVIAR)
The project was funded by InnovateUK (Highways England) with a value of £1 million. As the team leader, I managed a group of research associates to ensure timely delivery of the work packages. I oversaw the instrumentation of the research vehicle with multiple advanced sensors, coordinating with companies for sensor procurement and collaborating with technicians to ensure accurate and reliable data collection. My work included developing LiDAR-detection algorithms and conducting big data analytics. I also performed sub-microscopic simulations to evaluate emerging vehicle safety technologies and presented our research findings to key industry stakeholders, including Highways England and Galliford Try.
Project: Developing Vehicle-Based Traffic Conflict Prediction Algorithms Using Deep Learning
Supervisors: Professor Mohammed Quddus, Professor Stephen Ison , Dr Andrew Timmis
My PhD research addresses the safety challenges in the rapidly evolving vehicle industry, driven by AI technologies such as machine learning, big data analytics, and image recognition. With vehicles now integrating Advanced Driver Assistance Systems (ADAS), predicting and preventing traffic conflicts is crucial for enhancing safety. Traditional algorithms often fall short by relying on single factors like Time-To-Collision (TTC) and failing to account for uncertainties and multiple influencing variables, such as traffic density, speed, and weather conditions. To overcome these limitations, I developed a robust, centralised digital architecture and framework that utilises cost-sensitive learning to handle class imbalances in data, employing advanced machine learning techniques, including Deep Neural Networks (DNNs) and hybrid LSTM-CNN models. These algorithms, validated through simulations and real-world data from the UK M1 motorway, demonstrated superior accuracy and sensitivity in predictinfg traffic conflicts, making them highly transferable to similar road networks.
This research is particularly valuable for intelligent transportation and vehicle safety systems, offering actionable insights and solutions for implementing more reliable ADAS in connected and autonomous vehicles, ultimately aiming to reduce collisions and improve overall traffic safety.
Supervisors: Professor Maria Attard
I utilised my skills in GIS modeling, data analysis, and strategic planning to make substantial contributions to transportation and territorial research. I played a key role in developing a digital map of the Maltese transport network and analysing traffic flows in and out of ports, including the movement of passengers and goods between Malta and Sicily. My responsibilities also included drafting joint strategies to address current territorial challenges, assisting with the day-to-day research activities of the school, and supporting the institution through meetings, report compilation, and conference attendance. My proactive involvement extended to participating in research networks both locally and internationally, seeking collaborative opportunities and contributing to the development of project ideas for various funding programs. My commitment to research excellence and collaboration has been a driving force in my role, aiming to advance impactful research initiatives.
I delivered engaging lectures on subjects including Physics, Signal Processing, Mathematics for Engineers, and Statistics, AI, and Deep Learning, effectively communicating complex concepts to students. I prepared comprehensive lectures that were closely aligned with the syllabus, ensuring a well-structured and coherent learning experience. In addition, I provided timely and constructive feedback on assignments, which helped foster student learning and growth, supporting their academic development.
As a STEM Ambassador, I played a key role in inspiring and engaging students in Science, Technology, Engineering, and Mathematics (STEM) through a variety of outreach activities, workshops, and presentations. I worked closely with schools, colleges, and community organisations to promote STEM subjects, with a particular focus on encouraging young women to explore and pursue careers in engineering and related fields. By sharing my personal experiences and real-world insights, I aimed to demystify STEM concepts and highlight the diverse opportunities available within these industries. My efforts were geared towards breaking down stereotypes and supporting the next generation of female engineers, fostering an inclusive environment that celebrates diversity in STEM. This role not only enhanced my communication and mentoring skills but also allowed me to contribute to the promotion of women in engineering and make a meaningful impact on the future of the STEM community.
During my PhD, I served as a Sub-Warden for Telford Hall, where I demonstrated leadership and interpersonal skills by contributing to the establishment of a strong and positive residential community. In this role, I provided valuable support and guidance to students facing challenges, fostering an environment that promoted both personal and academic growth. I proactively managed incidents, ensuring the safety and well-being of residents while upholding standards of behavior. My experience enhanced my conflict resolution and problem-solving abilities, as I handled diverse situations and promoted effective communication among residents. I collaborated with a team of wardens and staff to organize community-building events and activities, fostering a sense of belonging among residents. Additionally, I contributed to the development and implementation of policies and initiatives to enhance the living experience for all students in Telford Hall, while displaying empathy and understanding to support students during difficult times.
As a Student Ambassador at Loughborough University, I represented the university at various events, engaging with prospective students and their families. My role involved leading campus tours, providing insights into university life, and assisting with open days and other outreach activities. I effectively communicated the benefits of studying at Loughborough, sharing my personal experiences and offering guidance to help prospective students make informed decisions about their education. This position allowed me to develop strong communication and public speaking skills while contributing to the university's recruitment and community engagement efforts.
With a strong background in Data Science, AI, and Machine Learning, I bring innovative solutions to your complex challenges. Let’s work together to drive success and explore new opportunities.
Got a project in mind or just want to chat about possibilities? I’m all ears and ready to collaborate. Reach out, and let’s make great things happen.
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