Who I Am

I work as an R&D Consultant, where I analyse technically complex work and communicate it with clarity and methodological discipline. I am especially interested in how evidence is generated, how uncertainty is handled, and how decisions can be made more reliable through better evaluation and system design.

Career Story

Data Science & Decision Support (DUT IDSD)

I began my academic training with a Diploma in Decision Support Computing and Data Science (DUT IDSD), a program explicitly oriented toward data-driven professions. This formation provided a strong grounding in algorithmic thinking, programming, data management, and statistical reasoning, alongside core mathematical foundations such as linear algebra, probability, and numerical analysis.

The curriculum combined software development with data-centric skills, covering topics such as Python for data science, data visualisation, relational and advanced databases, and decision-support systems. I was also introduced early to artificial intelligence, natural language processing, and deep learning, as well as operational research and enhance methods.

Through applied projects and a technical internship, this training emphasised practical data exploitation, problem formulation, and communication of results, while fostering methodological rigour and autonomy. This first formation laid the foundations for my later specialisation in AI and collective intelligence, and motivated my decision to pursue further academic training.

Information Systems Engineering and Software (ISIL)

I completed a Bachelor’s degree in Information Systems Engineering and Software (ISIL), where I acquired solid technical foundations in software development, object-oriented programming, system design and modelling, database administration, and distributed applications. The program combined theoretical coursework with hands-on projects covering operating systems, computer networks, system security, and cloud computing, while also introducing a project management methodologies and agile software engineering practices.

This training strengthened my ability to analyse and design complex information systems, work with multi-tier and client–server architectures, and adapt software solutions to evolving technological environments. It also provided early exposure to emerging domains such as artificial intelligence and cloud-based systems, preparing me both for applied industry work and for further academic study.

MSc in Collective Intelligence (UM6P)

I pursued a Master’s degree in Collective Intelligence at the School of Collective Intelligence at UM6P, an interdisciplinary program combining artificial intelligence, cognitive science, data science, and social systems analysis. The program focuses on how humans, machines, and institutions generate knowledge, coordinate decisions, and manage uncertainty at scale.

During the Master’s, I worked on research-driven projects spanning experimental cognitive science (belief updating, trust, and credibility), collective intelligence systems (crowd evaluation, participatory platforms), and quantitative evaluation (forecast aggregation, statistical modelling, and error analysis). This training strengthened my interest in evaluation methodology, experimental design, and the limits of AI systems when deployed in real world, human-centred contexts.

Industry-Embedded AI Research Master’s Thesis

My Master’s thesis was conducted in collaboration with Nokia and focused on deep learning for industrial image classification. The research evaluated multiple CNN architectures and ensemble learning strategies under real-world constraints such as class imbalance, limited labelled data, and computational cost. This work strengthened my interest in AI robustness, generalisation, and evaluation beyond benchmark performance. • See thesis →

Professional Practice R&D Consultant

I currently work as an R&D Consultant, where I analyse complex software and AI-driven projects and translate technical uncertainty, experimentation, and innovation into structured research narratives. This role sharpened my ability to critically assess AI systems, reason about evidence and limitations, and communicate technical work clearly skills that directly support my preparation for PhD-level research in AI-related fields.

Research Interests (AI-related)

• Human-centred AI and decision-making under uncertainty
• Trust, credibility, and belief updating in human–AI contexts
• Evaluation methodology: experimental design, causal inference, robustness
• Collective intelligence systems and deliberation-quality improvement
• Applied ML on noisy, real-world data (NLP, forecasting, classification)

What I’m Looking For

I’m looking for a PhD position in an AI-related program or lab (applied ML / human-centred AI / computational social science / collective intelligence) where I can contribute to rigorous research that improves how AI systems are designed and evaluated in practice.

Extracurricular & Academic Engagement

Alongside my academic and professional trajectory, I have been actively involved in initiatives focused on knowledge sharing, mentorship, and community engagement. These activities reflect my commitment to supporting inclusive access to education, career development, and interdisciplinary collaboration.

• Alumni Mentor UM6P: Provide guidance and support to current students on academic choices, career orientation, and transition to industry or research paths.
• Ambassador Chnondir.ma: Contributed to initiatives promoting civic engagement and participatory approaches within local communities.
• Mentor DigiGirlz: Supported and mentored young women interested in technology and digital careers, with a focus on confidence-building and skills development.
• Ambassador School of Collective Intelligence (UM6P): Represented the program in academic and outreach activities, promoting interdisciplinary research and collective intelligence approaches.
• Member AIESEC International (Volunteer Service): Participated in volunteer-driven projects aimed at leadership development and social impact.
• Member Music Club & EPDD: Engaged in cultural and student-led initiatives supporting creativity and collaborative learning environments.