Student Outcomes

Through personalised mentoring, students consistently achieve results that stand out:

• Completion of structured AI research projects with real datasets.
• Submission of papers to student research journals.
• Participation in STEM competitions and research showcases.
• Research used for selective school and summer program applications.
• Technical skills at early university-level machine learning.

Due to GDPR, detailed success stories are shared upon request.

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• Cyberbullying detection using transformer NLP.
• Financial forecasting with LSTMs + sentiment.
• MRI tumour classification via CNNs + XAI.
• Medical time-series modelling.
• Environmental anomaly detection.
• Satellite imagery land-use classification.
• Energy demand forecasting.
• Emotion recognition from speech/text.
• Deepfake & forgery detection.
• Recommendation systems (sports, media, analytics).

Projects are ambitious yet achievable, emphasising scientific clarity and reproducibility.

Many students choose to pursue a paper because:

• It demonstrates independent thinking.
• It builds real scientific writing experience.
• It strengthens personal statements and interviews.
• It differentiates from coursework-only profiles.

From topic selection to modelling, evaluation, and writing, mentors guide students through every stage of the research process.