Conference: Workshop for Rigorous and Reproducible Scientific Reasoning
会议:严谨且可重复的科学推理研讨会
基本信息
- 批准号:2336329
- 负责人:
- 金额:$ 9.21万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-10-01 至 2024-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The workshop explores a rigorous and reproducible approach to the specification, analysis, and validation of scientific workflows by assembling diverse scientists from scientific disciplines such as biology, physics and climate science, along with researchers from formal methods focusing on logic, theorem proving and constraint solving. Fundamental scientific breakthroughs are key to human advancement in diverse areas including agriculture, vaccines, climate prediction and next-generation computers. At the same time, science increasingly relies on enormous volumes of data that are processed through software to provide evidence supporting scientific conclusions. Failure to maintain the highest levels of scientific rigor and reproducibility can lead to a lot of confusion and wasted resources. Above all, this can lead to loss of trust in science and scientists among the public, when this is crucial for making informed policies. The recent spate of high-profile retractions suggests that the process of ensuring rigor and reproducibility is failing to keep pace with the volume of new scientific research. Formal methods, as an area, has successfully tackled the problems of specification and verification in areas including hardware, software, and cyber-physical systems. The workshop, to be held in-person in Boulder, CO, will enable robust conversations to help formal methods experts understand the nature of scientific research workflows while simultaneously exposing scientists to ideas from formal specification, modeling, and verification. In addition, the workshop will include editors from major journals in these areas and participants from government, as they are critical part in the chain of scientific endeavor. The workshop’s novelties include a first of its kind meeting between scientists, formal methods experts, and other stakeholders in a bid to spark new ideas and collaborations between participants that address the issue of rigor and reproducibility for scientific workflows. The workshop’s impacts include new ideas that could revolutionize how scientists present the entire scientific workflow from data gathering to the final conclusions in a way that is easy to verify and reproduce. The workshop is an important step towards ensuring that the scientific discoveries of the future are clearly rigorous in a manner that is easy to comprehend, validate and reproduce independently. This will benefit the scientific community and society by building confidence in our basic scientific research. The workshop celebrates diversity in science by involving people from many different backgrounds including under-represented groups in the conversation to shape the future of the scientific research methodology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该研讨会通过组装诸如生物学,物理学和气候科学等科学学科的分歧,以及针对逻辑,定理提供和约束解决方案的正式方法的研究人员,探讨了对科学工作流的规范,分析和验证的严格且可重复的方法。基本的科学突破是人类在不同地区发展的关键,包括农业,疫苗,气候预测和下一代计算机。同时,科学越来越依赖大量数据,这些数据通过软件处理来提供支持科学结论的证据。无法保持最高水平的科学严谨性和可重复性会导致很多混乱和浪费的资源。最重要的是,当这对于制定知情政策至关重要时,这可能会导致对科学和科学家的信任。最近的备受瞩目的缩回表明,确保严格和可重复性的过程无法与新的科学研究的数量保持空间。作为一个领域,正式方法已成功解决了包括硬件,软件和网络物理系统在内的领域的规范和验证问题。该研讨会将在科罗拉多州的博尔德举行,将实现强大的对话,以帮助正式的方法专家了解科学研究工作流的性质,同时使科学家从正式的规范,建模和验证中接触思想。此外,研讨会将包括来自这些领域主要期刊的编辑以及政府的参与者,因为它们在科学努力链中至关重要。研讨会的新颖性包括科学家,正式方法专家和其他利益相关者之间的首次同类会议,以激发参与者之间的新想法和合作,以解决对科学工作流的严格性和可重复性问题的问题。研讨会的影响包括新想法,这些想法可以彻底改变科学家如何以易于验证和复制的方式展示从数据收集到最终结论的整个科学工作流程。研讨会是确保未来的科学发现以易于理解,验证和独立繁殖的方式的重要一步。这将通过对我们的基础科学研究建立信心来使科学界和社会受益。讲习班名人在科学方面的多样性通过参与来自许多不同背景的人们,包括对话中代表性不足的群体,以塑造科学研究方法的未来。该奖项反映了NSF的法定使命,并被认为是通过基金会的知识分子优点和更广泛的影响来评估的,并被认为是珍贵的支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Sriram Sankaranarayanan其他文献
Worst-Case Convergence Time of ML Algorithms via Extreme Value Theory
基于极值理论的 ML 算法的最坏情况收敛时间
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Saeid Tizpaz;Sriram Sankaranarayanan - 通讯作者:
Sriram Sankaranarayanan
Large Language Models Enable Automated Formative Feedback in Human-Robot Interaction Tasks
大型语言模型可在人机交互任务中实现自动形成反馈
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Emily Jensen;Sriram Sankaranarayanan;Bradley Hayes - 通讯作者:
Bradley Hayes
A bit too precise? Verification of quantized digital filters
是不是有点太精确了?
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Arlen Cox;Sriram Sankaranarayanan;Bor - 通讯作者:
Bor
Algorithms for Identifying Flagged and Guarded Linear Systems
识别标记和保护线性系统的算法
- DOI:
10.1145/3641513.3650140 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Guillaume O. Berger;M. Narasimhamurthy;Sriram Sankaranarayanan - 通讯作者:
Sriram Sankaranarayanan
Automated Assessment and Adaptive Multimodal Formative Feedback Improves Psychomotor Skills Training Outcomes in Quadrotor Teleoperation
自动评估和自适应多模态形成反馈可改善四旋翼飞行器远程操作的精神运动技能训练成果
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Emily Jensen;Sriram Sankaranarayanan;Bradley Hayes - 通讯作者:
Bradley Hayes
Sriram Sankaranarayanan的其他文献
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{{ truncateString('Sriram Sankaranarayanan', 18)}}的其他基金
CPS: Medium: Collaborative Research: Learning and Verifying Conformant Data-Driven Models for Cyber-Physical Systems
CPS:媒介:协作研究:学习和验证网络物理系统的一致数据驱动模型
- 批准号:
1932189 - 财政年份:2019
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
SHF: Small: Rigorous Synthesis and Verification of Decisions Using Data-Driven Models
SHF:小型:使用数据驱动模型对决策进行严格的综合和验证
- 批准号:
1815983 - 财政年份:2018
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
SHF: Small: Bilinear Constraint Solving and Optimization for Program Verification and Synthesis Problems
SHF:小型:程序验证和综合问题的双线性约束求解和优化
- 批准号:
1527075 - 财政年份:2015
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
CPS: Synergy: Collaborative Research: In-Silico Functional Verification of Artificial Pancreas Control Algorithms.
CPS:协同作用:协作研究:人工胰腺控制算法的计算机功能验证。
- 批准号:
1446900 - 财政年份:2014
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
CSR: Small: Collaborative Research: Gray Box Testing of Complex Cyber-Physical Systems Using Optimization and Optimal Control Techniques
CSR:小型:协作研究:使用优化和最优控制技术对复杂信息物理系统进行灰盒测试
- 批准号:
1319457 - 财政年份:2013
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
SHF: Small: Reasoning Rigorously About Probabilistic Programs
SHF:小:对概率程序进行严格推理
- 批准号:
1320069 - 财政年份:2013
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
CAREER: Automatic Analysis of Cyber Physical Systems: Bridging the Gap between Research and Industrial Practice
职业:网络物理系统的自动分析:弥合研究与工业实践之间的差距
- 批准号:
0953941 - 财政年份:2010
- 资助金额:
$ 9.21万 - 项目类别:
Continuing Grant
CPS: Small: Formal Analysis of Man-Machine Interfaces to Cyber-Physical Systems
CPS:小型:网络物理系统人机接口的形式分析
- 批准号:
1035845 - 财政年份:2010
- 资助金额:
$ 9.21万 - 项目类别:
Standard Grant
SHF: Small: Collaborative Research: Statistical Techniques for Verifying Temporal Properties of Embedded and Mixed-Signal Systems
SHF:小型:协作研究:验证嵌入式和混合信号系统时间特性的统计技术
- 批准号:
1016994 - 财政年份:2010
- 资助金额:
$ 9.21万 - 项目类别:
Continuing Grant
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