By task · Research code

Thesis and research code. Reproducible and documented.

Implementations, experiments and data pipelines for Masters and PhD research. Clean, reproducible code your advisor and committee can follow.

Python & JupyterPyTorch / JAXR & StanMATLABC++ / CUDALaTeX

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Upload your assignment files or browsePrompt, rubric, starter code · PDF, DOCX, ZIP, code · up to 25 MB in total

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Price cappedFrom $45Full refund if we’re late800+ students

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What we handle

Everything this service covers.

Implementation

Algorithms from papers
Simulation models
Numerical methods
Baseline reproductions

Experiments

Experiment pipelines
Hyperparameter sweeps
Statistical analysis
Ablation studies

Reproducibility

Pinned environments
Config-driven runs
Seeds and logging
Docker images

Output

Publication-quality figures
LaTeX tables
Documentation
Code release prep

Example order

One research code order, start to finish.

What the student uploaded, what came back, and how the price was set.

01The brief

Computational BiologyPhDDue in 3 weeks

Reproduce a paper’s baseline and run ablations

Reimplement the baseline model from a published paper, match its reported accuracy within 1%, then run three ablations across 5 seeds with LaTeX-ready tables.

Requirements

Faithful reimplementation
Match the paper within 1%
Config-driven runner, 5 seeds
LaTeX tables and PDF figures

02The solution

run.py13 lines

1@hydra.main(config_path="conf", config_name="baseline", version_base=None)

2def main(cfg: DictConfig) -> None:

3 results = []

4 for seed in cfg.seeds: # e.g. [0, 1, 2, 3, 4]

5 set_seed(seed) # python, numpy, torch

6 model = build_model(cfg.model)

7 metrics = train_and_eval(model, cfg.data, cfg.train)

8 results.append({"seed": seed, **metrics})

9 log.info("seed=%d auroc=%.4f", seed, metrics["auroc"])

11 df = pd.DataFrame(results)

12 df.to_csv(f"results/{cfg.name}.csv", index=False)

13 write_latex_table(df, f"tables/{cfg.name}.tex") # mean ± std

baseline within 0.4% of the paper · 5 seeds

03The explanation doc

explanation.pdf

Where it differs from the paper

Two undocumented preprocessing steps were recovered from the authors’ released config.

Reproducibility

Every run is driven by a config file and a fixed seed; versions are pinned.

Results

Baseline AUROC 0.908 ± 0.004 against 0.912 reported.

04The price

AI predicted budget

$600–$1200

Level · PhDAdvanced

Deadline · 3 weeksStandard

Shown before any contact details were shared.

Final price from our team

$850

Delivered 2 days early

How it works

From upload to predicted budget in under a minute.

The AI does one job: it predicts your price. A senior engineer reviews your files and sets the final number.

01
Step 1 of 4
Upload your files
Prompt, rubric, starter code, or a screenshot of the task. PDF, DOCX, ZIP, code or images, in any mix.
02
Step 2 of 4
The AI asks what’s missing
It confirms your due date, then asks up to 3 questions your files don’t answer. Each one has an “I don’t know” option.
03
Step 3 of 4
See your predicted budget
A price range appears right away. No email, no sign-up.
04
Step 4 of 4
A senior engineer confirms your price
Leave your email. Within 5 minutes you get one fixed price. It never goes above the top of your range.

No payment to get a price. You pay only after you accept the fixed price. If the AI can’t price your files, an engineer emails you a price instead.

Typical orders

Common requests and typical budgets.

Algorithm from a paper

$300–$800

Usually 1–2 weeks

typical range

Experiment pipeline and sweeps

$400–$1,000

Usually 1–3 weeks

typical range

Statistical analysis of results

$150–$400

Usually 3–7 days

typical range

Code cleanup for release

$200–$600

Usually 1–2 weeks

typical range

Your budget depends on your files, deadline and level. Upload them for your own prediction.

Guarantees

Every order is covered. In writing.

Full refund, in three cases

We miss your deadline. Your code still doesn’t meet your original brief after revisions. Or you cancel before an engineer starts.

Partial refunds, worked out in the open

Cancel after work starts, or keep part of the work: we refund the rest and show you how we worked it out first.

Refunds that move fast

We reply within 24 hours. Approved refunds go back to your card through Stripe within 2 business days.

Unlimited revisions for 14 days

We revise until it matches your original instructions. No fees.

Your price is capped

Your fixed price never goes above the top of your range.

How the cap works

NDA and privacy

Your name, school and files are never shared, sold or reused. Engineers never see your name or email.

Secure payment

Processed by Stripe. We never see or store your card details.

Read the full refund policyFree. No email needed.

FAQ

Questions students ask first.

Still have a question?

Email us any time. Support runs 24/7 and a real person replies.

team@domyprogramminghomework.io

Is unpublished research kept private?

Every order is covered by our NDA, and we can sign your institution’s agreement too.

Who works on research code?

Engineers with graduate degrees in the relevant field, matched to your methods.

Is this allowed for a thesis?

Rules vary by program. Use our work as implementation support and check your program’s policy.

Is the predicted budget the final price?

Not exactly, but it’s capped. Our team reviews your files and sends one fixed price before you pay anything, and it never goes above the top of your range.

What if you miss my deadline?

You get a full refund, back to your card through Stripe. It’s in our refund policy, in writing.

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