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Provides a comprehensive guide for packaging complex research artifacts, integrating hardware, firmware, and datasets. It outlines best practices for achieving academic badges (e.g., Available, Functional, Reusable) and winning the Best Research Artifact Award. Learn how to structure analysis paths, manage raw traces, and ensure reproducibility across different evaluation environments.

A comprehensive guide for designing and auditing rigorous experiments for sensing systems and information processing claims. It emphasizes the necessity of measuring performance on real hardware (not simulation), accurately instrumenting ground truth, quantifying energy consumption, latency, and physical footprint, and establishing fair, skeptical baselines. This ensures scientific rigor and reproducibility in research submissions.

A comprehensive guideline for establishing and documenting the reproducibility of complex sensor-systems artifacts. It covers necessary components such as firmware sources, detailed hardware Bills of Materials (BOMs) and board files, raw sensor traces, ground truth data, and calibrated measurements. Use this guide to ensure that scientific claims can be verified by a competent reader, detailing the exact dependencies on physical equipment and software toolchains.

This guide helps researchers determine the primary focus of their work—whether it lies in Information Processing (algorithms, estimation) or Sensor Platforms, Tools, and Design Methods (hardware, deployment). It provides a structured methodology for selecting the most appropriate academic venue (e.g., SenSys, MobiSys, INFOCOM) based on the project's technical contribution and maturity.

A comprehensive project management guide detailing the entire lifecycle of a high-stakes sensing systems research submission. It provides a detailed backward planning timeline, covering critical milestones from initial venue and track selection, hardware freezing, field deployment logistics, double-blind review, and final submission to major conferences like SenSys. It emphasizes managing the critical path of field work and data artifacts.

This guide provides structured rules for authors writing sensor-systems or information-processing papers. It emphasizes leading with the physical sensing problem, requiring real-hardware measurements for energy, latency, and ground truth, and adhering to strict academic formatting constraints. Use this when revising submissions to ensure technical depth and practical deployability.

A comprehensive guide for structuring the evidence bundle required for robotics research submissions. It details the critical components—including hardware ledgers, time-stamped logs, configuration files, code, and data—necessary to ensure that scientific claims are fully auditable and reproducible, addressing the needs of skeptical reviewers.

This guide establishes standards for reporting reproducibility in robotics research, addressing the difference between traditional ML and physical systems. It mandates that every claim must be classified as either 'rerunnable' (executable code/simulation) or 'auditable' (detailed logs, hardware specs, and protocols). It covers creating a complete evidence map, detailing the hardware specification ledger, explicitly reporting the sim-to-real gap, and writing an honest availability statement, all within the main paper body.

This detailed guide helps researchers pre-write their papers by evaluating if their intelligent robotic system is a strong fit for IROS or other top-tier conferences (ICRA, RSS, CoRL). It emphasizes the importance of demonstrating integrated systems (perception, planning, control) on real hardware under defined embodiment constraints, ensuring the contribution is demonstrably hard and system-based.

A comprehensive guide on achieving scientific reproducibility for complex computer architecture and system simulations. It details how to manage and pin all dependencies—including simulator commit hashes, local patches, workload binaries, hardware states, and post-processing scripts—to ensure that every reported figure and number can be accurately regenerated, regardless of time or environment changes.

This guide provides expert advice on positioning research papers for top-tier computer architecture conferences (e.g., ISCA, MICRO, ASPLOS). It teaches authors how to identify the 'center-of-gravity' of their novelty—whether it lies in the hardware organization, the hardware/software contract, or the software layer alone—to maximize review acceptance chances and successfully navigate the competitive academic publication landscape.

A comprehensive guide detailing the specific conventions required for submitting high-quality, data-driven papers in computer architecture to top-tier conferences like ISCA. It covers structuring the core argument around a single insight, developing measured motivation sections, describing mechanisms with checkable precision, and calibrating quantitative claims with empirical data and instruments. Essential for academic research communication in hardware design.