Phd Proposal

PhD/Master's Research Proposal

Structure and write a rigorous research proposal that satisfies committee requirements.

Standard Proposal Structure (IEEE/ACM CS)

1. Title & Abstract          (~200 words)
2. Introduction              (~500 words)
3. Related Work              (~800 words)
4. Research Questions        (~200 words)
5. Methodology               (~1000 words) ← most important
6. Preliminary Results       (~500 words, if any)
7. Timeline & Milestones     (table/Gantt)
8. Expected Contributions    (~300 words)
9. References                (BibTeX)

Section-by-Section Guidance

1. Title & Abstract

Title formula: [Method/Approach] for [Problem] in [Domain/Context] Example: "Federated Multi-Level Feedback Queue Scheduling for Resource-Constrained Healthcare IoT Networks"

Abstract (one paragraph, no citations, no math):

[Context]: In [domain], [background challenge].
[Gap]: However, [specific gap from literature].
[Approach]: We propose [method name], which [key idea].
[Validation]: We evaluate on [datasets/benchmarks] using [metrics].
[Impact]: Results show [expected outcome], enabling [application].

2. Introduction

• Hook: real-world motivation (1 paragraph)
• Background: what exists (1 paragraph)
• Problem: specific gap (1 paragraph)
• Solution sketch: your approach (1 paragraph)
• Contributions: bulleted list (use research-question output)
• Thesis structure: "Chapter 2 covers..."

3. Related Work

Organize by taxonomy (not chronologically):

3.1 [Approach A] — summarize 3-5 papers, explain why insufficient
3.2 [Approach B] — same
3.3 [Your positioning] — "Unlike X, we address Y by Z"

4. Research Questions

• State main RQ + 2-4 sub-questions (paste from research-question skill output)
• Each sub-question should be answerable in ~1 chapter/paper

5. Methodology (Most Critical)

5.1 Research Paradigm Choose and justify:

• Quantitative / Qualitative / Mixed
• Paradigm: Design Science Research (DSR) / Experimental / Simulation

5.2 System/Model Design

Input: [what]
Processing: [how — algorithm, model, framework]
Output: [what]
Assumption: [what you assume]

5.3 Experimental Protocol

Datasets: [name, size, source, why chosen]
Baselines: [method1, method2 — why these are fair comparisons]
Metrics: [primary metric] + [secondary metrics]
Evaluation protocol: [k-fold CV / train-val-test split / simulation rounds]
Statistical tests: [t-test / Wilcoxon / effect size — for significance]

5.4 Reproducibility Plan

• Code: GitHub repo (public after publication)
• Environment: Docker / conda environment file
• Seeds: fixed random seeds
• Hardware: specify GPU/CPU specs

6. Preliminary Results

Include if you have any early experiments. Even partial results strengthen the proposal.

• 1-2 preliminary experiments showing feasibility
• Small-scale validation of core idea
• If none: state "Preliminary experiments are planned for Month 3-4"

7. Timeline & Milestones

For a 2-year Master's program (align with milestone-tracker skill):

8. Expected Contributions

Restate from research-question skill, add:

• Theoretical contribution (if any)
• Practical contribution (system, dataset, tool)
• Publication targets (venues + tier)

Committee Checklist

Before submitting proposal for committee review:

• Problem is clearly stated in 1-2 sentences
• Gap is supported by ≥3 recent papers
• RQ is specific and measurable
• Methodology is detailed enough to replicate
• Baselines are state-of-the-art, fairly chosen
• Timeline is realistic (pad 20% for delays)
• Limitations are acknowledged
• Ethical considerations addressed (IRB, data privacy)

Output Format

Produce a structured Markdown document following the section order above. Export to LaTeX using the paper-writing skill templates.

Links to Other Skills

• Requires → sota-survey + research-question
• Feeds into → research-design (methodology details)
• Feeds into → milestone-tracker (timeline)
• Feeds into → paper-writing (proposal becomes thesis chapters)