Skill UI

Provides comprehensive guidelines for selecting and rigorously justifying research designs across various academic paradigms: qualitative/ethnographic, critical, quantitative, and mixed-methods. This guide ensures the chosen methodology aligns perfectly with the theoretical question, emphasizing rigor, transparency, and advanced methodological considerations for academic manuscripts in Human Relations.

This comprehensive guide provides best practices for packaging supplemental materials and artifacts for top-tier academic conferences like ICDE. It instructs authors on how to build a robust, reproducible evidence chain, including parameterized workload generators, configuration scripts, and detailed logs. The goal is to ensure that reviewers can quickly and accurately validate all performance claims and technical contributions, making the work 'turnkey' and verifiable.

This guide outlines comprehensive standards for scientific reproducibility in data engineering. It details best practices for pinning hardware, software, datasets, and variance protocols, ensuring that all performance claims are verifiable and re-runnable by peers, making reproducibility a scored component of academic submission.

A comprehensive guide for authors submitting data-intensive systems papers to top-tier conferences (like ICDE). It details how to structure the paper, ensure technical claims are reconstructable, quantify all performance gains with associated costs, and compress complex ideas into a limited page budget while maintaining scholarly rigor.

This guide helps researchers determine if their Machine Learning project is suitable for ICLR, or if a different top-tier conference (such as NeurIPS, ICML, or CVPR) is a better fit. It emphasizes the need for deep representation-learning insights, mechanistic understanding, and theoretical contributions over mere application performance.

A comprehensive guide for authors targeting the IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR). It details the strategic framing, required evidence (e.g., measured immersive user experience), proper positioning, and necessary structural adjustments to ensure a computer science manuscript is highly relevant and competitive for this specialized venue.

This skill serves as a comprehensive guide for positioning computer communications and networking manuscripts for the IEEE INFOCOM conference. It helps authors understand the venue's specific scope, the required evidence bar (solid analytical or empirical performance evidence), and how to re-frame their work to align with INFOCOM's standards compared to sibling venues like SIGCOMM or CoNEXT. Use this for submission strategy and manuscript calibration.

A comprehensive guide for positioning computer architecture manuscripts for the IEEE HPCA conference. It covers ideal scope (accelerators, memory systems, interconnects), required evidence (benchmarks, performance/energy tradeoffs), and strategic framing needed to appeal to top-tier hardware reviewers. Use it to refine your narrative and ensure your contribution meets the high standards of high-performance computing research.

This guide helps authors determine if their communication systems manuscript is suitable for IEEE Transactions on Communications (TCOM). It outlines the criteria for a high-quality submission, emphasizing the necessity of quantitative performance analysis, analytical derivations, and robust simulation validation. It guides authors on reframing pure simulation results into deeply researched, publishable academic work.

This skill guides researchers on preparing manuscripts for IEEE Transactions on Wireless Communications (TWC). It provides a detailed framework for assessing whether a paper has genuine wireless specificity, requiring quantitative analysis and simulation under realistic channel models (e.g., imperfect CSI, mobility). It covers core topics like MIMO, resource allocation, and advanced networking, ensuring the work meets the rigorous standards of top-tier academic publications.

This guide details the comprehensive process for preparing security research artifacts for post-acceptance evaluation at major conferences like IEEE S&P. It covers the three types of evaluation badges (Available, Functional, Results Reproduced), strict handling constraints for exploits and malware, and best practices for packaging the submission (e.g., Dockerfiles, README structure) to ensure external evaluators can reliably reproduce findings within a limited time frame.

This comprehensive guide provides best practices for designing, running, and reporting computational experiments for academic journals. It teaches authors how to make performance claims scientifically defensible by addressing potential referee criticisms (e.g., tuning artifacts, seed luck). It covers advanced statistical techniques (performance profiles, nonparametric tests) and details the full structure required for a complete, verifiable GitHub data deposit.