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With Syed Hameed

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Senior Professional Officer

Syed
Hameed

Executive -MBA, SP Jain Global Business School (SG), Singapore
Email

Education

  • Executive -MBA
    SP Jain Global Business School (SG) , Singapore
  • Bachelor of Applied Information Technology
    The Newcastle University Australia , Australia

Professional Certification

  • Certificate in AI Ethics and Governance
  • Certified ScrumMaster® (Scrum Alliance)
  • Google IT Automation with Python (Advanced) Professional Certificate
  • Google Advanced Data Analytics Professional Certificate

Professional Memberships

  • Singapore Computer Society

Industry Experience

  • Singapore Institute of Technology
    Present
  • DBS Bank
    –
  • Standard Chartered Bank
    –
  • Cisco Systems
    –
  • Hewlett-Packard
    –
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Technical Skills

  • Data Analytics – Exploratory, Complex & Multi Source Information
  • Data Engineering & DB Management
  • Data Governance – DQM, Meta Data
  • Advanced Analytics – Data Modelling, Predictive, Validation
  • Programming – Python, SQL
  • Visualisation & Reporting – KPI & dashboard monitoring

Research Interests

  • Self-Supervised Learning

Current Projects

  • AI-Driven Wildlife Recognition for Biodiversity Monitoring
    – Present

    Role: Principal Investigator
    Project Overview: This applied research project develops an AI-powered pipeline to automate the analysis of camera trap images for wildlife monitoring in Singapore's tropical forests. The system integrates object detection (YOLOv5) and species classification (ResNet50) models targeting five priority wildlife species, with a goal of achieving 90% priority species identification accuracy.
    Key Contributions: A novel image restoration pipeline — ATCE — has been developed, combining automated scene classification, Retinex-based illumination enhancement, and Stable Diffusion-guided image restoration to significantly improve the quality of degraded camera trap footage prior to AI classification. Findings are being prepared for submission to Methods in Ecology and Evolution.
    Significance: This work addresses a critical bottleneck in biodiversity monitoring — the manual review of large volumes of camera trap images — by providing wildlife agencies and conservation practitioners with a scalable, automated alternative that preserves scientific rigour.

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