Competitive Research & Innovation Experience — 2025
In 2025 I engaged in multiple interdisciplinary innovation forums, independently proposing a Brain–Computer Interface (BCI) EEG stress‑management system. The work combined neurotechnology, signal processing and user‑centred design and was assessed by mixed academic and industry panels.
FICS Innovation Challenge — 2025
The FICS Innovation Challenge is a multi‑stage forum spanning computing, engineering and healthcare. I presented an independent technical proposal for a BCI‑based EEG stress‑management system, defended feasibility and impact, and progressed to the penultimate stage based solely on expert evaluation.
Proposal poster
Technical poster summarising architecture and evaluation plan.
Unique value
System emphasises low‑cost sensors, modular AI and closed‑loop feedback.
Venue
National Science & Technology Park, NUST — interdisciplinary evaluation setting.
Outcome: advanced to penultimate stage after expert screening; progress was performance‑based rather than awarded by certificate.
MCS DevCon IdeaThon — 2025
Certified participation in a university IdeaThon promoting cross‑domain innovation. I presented an EEG‑based BCI framework integrating sensing, signal processing, AI classification and closed‑loop feedback; an official participation certificate was issued.
Images: event highlights, conceptual diagrams and the DEVCON participation certificate — documenting validated engagement with academic peers.
Technical Concept — EEG‑Based BCI Stress Management
The system implements a complete BCI workflow: low‑cost EEG acquisition, preprocessing and noise mitigation, feature extraction with AI classifiers, and closed‑loop calming interventions (audio/visual) for real‑time stress modulation. Emphasis on accessibility, affordability and modularity supports research, wellness, and early screening applications.
Acquisition
Cost‑effective sensors and wearable ergonomics for repeated deployment.
Processing
Robust artefact mitigation and feature pipelines for reliable signals.
Classification
AI models tuned for cross‑subject generalisability and explainability.
Intervention
Closed‑loop calming stimuli with measurable physiological response.
Clockwise: device mockup, EEG plot, app demo, stress detection screen, post‑intervention output — each image supports claims about functionality and measurable effect.
Academic & Research Relevance
Presenting a BCI system in general innovation forums evidences ability to translate neuroengineering into interdisciplinary contexts, defend technical concepts before diverse evaluators, and demonstrates readiness for doctoral research that bridges applied neurotechnology and human‑centred evaluation.
Translational potential
From prototype to research studies and clinical pilot designs.
Evaluation rigour
Defended architecture and methods before mixed expert panels.
Research readiness
Modular design enables reproducible experiments and iterative studies.

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