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Here is the template you are required
to use for report submission:
https://www.overleaf.com/read/btddtdztdrgs		Proposal
(1-2 pages) 		Midterm Report
(4-5 pages)		Final Report
(8-10 pages)		↴
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Overview and ContextAbstract:Clarity: The problem statement is clear and concise, understandable to a general audience.Clarity: The problem statement is understandable to non-experts.Clarity: The problem statement is clearly articulated and understandable to a non-expert audience.
Regarding the first submission - the Project Proposal:
Keep your proposal concise:
- You are trying to pitch an idea and you should convey your thoughts as comprehensively as possible but while being concise.
- Try to limit to 2 pages unless you have done some significant work, or have an extensive literature review (which we do highly support that you start working on).
- The more papers you read the better chances you have to come up with novel ideas that can be published.
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Motivation: Students briefly explain why the problem is important or relevant.Students articulate why the problem is important or who benefits.Some contextual motivation for the study is given, such as who benefits and why it is important.
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Objective:At least one broad goal or objective is outlined, even if quantitative details are not yet finalized.At least one qualitative or quantitative objective is clearly stated.Qualitative and quantitative objectives are clearly stated and related to the problem statement.
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Related Work and BackgroundLiterature Review:Students cite at least one prior work relevant to their project.Students cite 1-2 key papers related to their project.Students identify relevant prior work, preferably grouping related research lines or methodologies.
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A short explanation of how this work relates to their project is included.Connections between the related work and the student’s problem are briefly explained.Proper citation and clear connections to the student’s project are included.
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Background:If applicable, students may reference an evaluation metric or baseline related to their problem.At least one cited paper connects the evaluation metric or baseline to the problem.Cited papers explicitly connect the evaluation metric and baseline models to the problem statement.
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MethodologyModel Description:A high-level description of the approach or model is provided (e.g., the type of algorithm or framework to be used).A basic explanation of the model being proposed (e.g., inputs and outputs).Clear diagrams or tables to describe model inputs, outputs, and structure.→
Example of Model Description Table
From the following article: https://www.researchgate.net/publication/333248441_Accurate_prediction_of_boundaries_of_high_resolution_topologically_associated_domains_TADs_in_fruit_flies_using_deep_learning
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Diagrams or tables are optional but encouraged if they clarify ideas.Diagrams or tables are encouraged but not required.The shape of output maps and parameter counts for key components are included.
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Dataset:Students identify a potential data source and briefly describe how it relates to the problem.The data source is identified, and basic preparation steps are outlined.Steps for making data usable for training and evaluation are explicitly stated, including batch sampling methods. A citation for the dataset is provided.
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Evaluation Metric:The metric students plan to use for assessing success is mentioned.The metric students plan to use is stated, with a simple explanation.Mathematical definitions of metrics are provided, with variables clearly labeled and related to the problem statement.
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Loss Function:Not required at this stage but can be briefly mentioned if known.Mentioned briefly if applicable, but not required at this stage.Loss functions and optimization steps are described with mathematical precision.
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Baseline and ExtensionsBaseline Selection & Evaluation:Students propose one or more potential baselines for comparison.MANDATORY: Students implement and explain their choice of baseline.Students justify their choice of baseline, referencing relevant papers or models.
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Baseline evaluations are conducted systematically, with key experiments highlighted.
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Implemented Extensions / Experiments:Proposed Extensions/Experiments: Students describe one or two initial ideas for how their work might extend beyond the baseline.Proposed Extensions/Experiments: A high-level description of one or two extensions or experiments they aim to conduct.Results demonstrate either improvement over baselines or thoughtful analysis of why they do not outperform them.
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Results and AnalysisResults:Anticipated Results: Students describe expected outcomes in general terms (e.g., “We aim to improve performance metrics over the baseline”).Progress Results: Any preliminary results or progress metrics are encouraged (e.g., sample outputs or initial plots).Final Results: Separate and clear results for training and validation phases.
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Not required to include full validation results at this stage.Evaluation metrics and key findings are visualized through plots or tables.
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Completeness:The work is cohesive and demonstrates thoughtful engagement with the problem.
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Discussion:Students briefly discuss potential challenges or risks in executing their proposed project.Briefly discuss challenges faced so far and potential risks moving forward.The team explains the significance of their results, potential risks, and the sensitivity of results to input changes.
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Future DirectionsPlanned Work: A clear outline of next steps in the project, focusing on what will be done before the midterm report.Planned Next Steps: Students identify 2-3 specific actions they will take to move forward with their project.Students identify areas for further exploration or improvement, based on results and limitations.
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ConclusionStudents effectively summarize their key findings, progress made, and how the work relates to their original objectives.
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Bonus Contributions (Optional)Visualization:Compelling and clearly labeled visualizations (e.g., embeddings, features) receive additional points.
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Dataset Creation:Original datasets of high quality can earn extra recognition.
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Administrative DetailsBibliography:At least one citation is required, with a preference for two or more.Students include citations for all referenced work (minimum 2-3 citations).References are formatted correctly and thoughtfully selected to support the project.
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Team Contributions:If applicable, students outline initial roles and responsibilities for team members.If applicable, a basic breakdown of team roles is provided.A breakdown of contributions by team members is included.
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GitHub Repository: If the modeling is in-process, begin a GitHub Repository and include the link.Include a GitHub Repository link.Include a GitHub Repository link.→
In the case that one+ member of your team does not contribute enough to the team project,
we will use the GitHub history (as well as google docs and Overleaf) to assess each team member's contribution level.
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