Sl. No. 1 and Sl. No. 2 constitute the core domains. Sl. No. 3 serves as an extension of either of these domains. Enrollment in Sl. No. 3 will be allowed only upon successful completion of Sl. No. 1 or Sl. No. 2.

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Biomedical Signal & Image Intelligence Lab (BSI² Lab)

Department of ECE, Gauhati University

                         From fundamentals to publication — a structured pathway into real research.

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Internship Tracks:

1. Medical Image Intelligence (Core Track)

Intake: 10 | Duration: 30 Days

Work on AI-driven medical image analysis with a focus on practical problem-solving.

• Retinal image analysis (DR, glaucoma, vessel segmentation)

• X-ray / HRCT / Mammography-based diagnosis

• Deep learning for classification and segmentation

• Model evaluation and interpretation

Integrated Research Skills:

• AI-assisted literature review and concept understanding

• Code support and debugging using AI tools

• LaTeX-based reporting (figures, tables, references)

2. Biomedical Signal Processing (Foundation Track)

Intake: 10 | Duration: 30 Days

Develop strong analytical foundations using physiological signals.

• ECG, EEG, EMG signal analysis/instrumentation

• Time, frequency, and time-frequency domain methods

• Feature extraction and basic ML models

• Signal interpretation and validation

Integrated Research Skills:

• AI-assisted concept exploration and workflow design

• Structured report generation using AI tools

• LaTeX documentation for technical reporting

3. Research & Publication Track (Advanced Extension) 

          Intake: 5 | Duration: 45 Days (30 + 15 Days Extension)

          This track is an advanced continuation of Tracks 1 & 2, designed for students who
          demonstrate strong performance and research inclination during the initial 30 days.

          Additional 15-Day Advanced Phase Includes:

• • Research gap identification from recent literature

  • Problem refinement and focused implementation

  • Comparative analysis and result validation

  • End-to-end manuscript preparation

Advanced Integration:

• • Strategic use of AI for:

    • research gap discovery

    • drafting and refinement (with ethical use)

  • Full LaTeX manuscript development (IEEE/Springer format)

  • Guidance toward conference/journal submission readiness

Eligibility:

• B.Tech (2nd/4th/Final Year), M.Tech, or equivalent

• ECE / EE / CSE or related disciplines

• Basic knowledge of:

  • Signals & Systems / Image Processing / Python or MATLAB

• Strong motivation and willingness to work consistently

 Program Structure:

• Guided internship with periodic reviews

• Task-driven progression (not lecture-based)

• Final presentation + technical report

 Outcomes

• Hands-on research exposure

• Strong foundation in AI-assisted research workflows

• LaTeX-based professional documentation

• Opportunity for advanced track (publication pathway)