Workshop for Women in Machine Learning
机器学习女性研讨会
基本信息
- 批准号:1346800
- 负责人:
- 金额:$ 4万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-01 至 2016-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Since 2006, the annual workshop for Women in Machine Learning (WiML) has brought together female researchers in industry and academia, postdoctoral fellows, and graduate students from the machine learning community to exchange research ideas and build mentoring and networking relationships. The one-day workshop has been especially beneficial for junior graduate students, giving them a supportive environment in which to present their research (in many cases, for the first time) and enabling them to meet peers and more senior researchers in the field of machine learning. The networking opportunities provided by the workshop have also helped senior graduate students find jobs following graduation. Intellectual Merit: This workshop will advance machine learning knowledge and foster collaboration within the machine learning community. As invited speakers, established researchers at top universities and research labs will teach workshop participants about cutting-edge ideas from diverse areas of machine learning. Students will present their own research and receive valuable feedback from both senior researchers and their peers. By enabling women at all stages of their careers in machine learning to exchange research ideas and form new relationships, we expect that new connections and research collaborations will be established, thereby advancing the state-of-the-art of the field. Broader Impact: This workshop will provide a forum for female graduate students, postdoctoral fellows, junior and senior faculty, and industry and government research scientists to exchange research ideas and establish networking and mentoring relationships. Undergraduates, particularly those who are interested in pursuing graduate school or industry positions in machine learning, are also welcome to attend. Bringing together women from different stages of their careers gives established researchers the opportunity to act as mentors, and enables junior women to find female role models working in the field of machine learning. The workshop will also benefit the wider machine learning community: Firstly, the WiML website, which lists all previous workshop presenters, serves as a useful resource for organizations looking for female invited speakers. Secondly, co-locating with a major machine learning conference enhances the visibility of female researchers among the wider machine learning community. Thirdly, travel funding provided to workshop participants also facilitates their travel to the co-located conference, which for some participants would otherwise not be possible. Finally, all workshop materials (slides, abstracts, etc.) will be made available on the workshop website in order to ensure broad dissemination.
自 2006 年以来,年度机器学习女性研讨会 (WiML) 汇集了来自机器学习界的工业界和学术界的女性研究人员、博士后研究员和研究生,交流研究想法并建立指导和网络关系。为期一天的研讨会对低年级研究生特别有益,为他们提供了一个支持性的环境来展示他们的研究(在许多情况下,这是第一次),并使他们能够结识机器学习领域的同行和更资深的研究人员。研讨会提供的交流机会也帮助高年级研究生毕业后找到工作。智力优势:本次研讨会将推进机器学习知识并促进机器学习社区内的协作。作为受邀演讲者,顶尖大学和研究实验室的资深研究人员将向研讨会参与者传授机器学习不同领域的前沿思想。学生将展示自己的研究成果,并从高级研究人员和同行那里获得宝贵的反馈。通过让处于机器学习职业生涯各个阶段的女性能够交流研究想法并形成新的关系,我们期望建立新的联系和研究合作,从而推进该领域的最先进水平。更广泛的影响:该研讨会将为女研究生、博士后研究员、初级和高级教师以及行业和政府研究科学家提供一个论坛,以交流研究想法并建立网络和指导关系。本科生,特别是那些有兴趣在机器学习领域攻读研究生院或行业职位的本科生,也欢迎参加。将处于职业生涯不同阶段的女性聚集在一起,为成熟的研究人员提供了充当导师的机会,并使年轻女性能够找到在机器学习领域工作的女性榜样。该研讨会还将惠及更广泛的机器学习社区:首先,WiML 网站列出了之前所有研讨会的演讲者,对于寻找女性受邀演讲者的组织来说,这是一个有用的资源。其次,与大型机器学习会议同期举办可以提高女性研究人员在更广泛的机器学习社区中的知名度。第三,为研讨会参与者提供的旅费资助也方便了他们参加同一地点的会议,否则这对一些参与者来说是不可能的。最后,所有研讨会材料(幻灯片、摘要等)将在研讨会网站上提供,以确保广泛传播。
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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Katherine Heller其他文献
OTC Product: BioSafe Diabetes Risk Assessment
- DOI:
10.1331/japha.2008.08529 - 发表时间:
2008-07-01 - 期刊:
- 影响因子:
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Katherine Heller - 通讯作者:
Katherine Heller
Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis
- DOI:
10.1038/s41598-024-63888-x - 发表时间:
2025-05-25 - 期刊:
- 影响因子:3.900
- 作者:
Subhrajit Roy;Diana Mincu;Lev Proleev;Chintan Ghate;Jennifer S. Graves;David F. Steiner;Fletcher Lee Hartsell;Katherine Heller - 通讯作者:
Katherine Heller
Evaluating the Usability and Impact of an Artificial Intelligence-Powered Clinical Decision Support System for Depression Treatment
- DOI:
10.1016/j.biopsych.2020.02.451 - 发表时间:
2020-05-01 - 期刊:
- 影响因子:
- 作者:
Myriam Tanguay-Sela;David Benrimoh;Kelly Perlman;Sonia Israel;Joseph Mehltretter;Caitrin Armstrong;Robert Fratila;Sagar Parikh;Jordan Karp;Katherine Heller;Ipsit Vahia;Daniel Blumberger;Sherif Karama;Simone Vigod;Gail Myhr;Ruben Martins;Colleen Rollins;Christina Popescu;Eryn Lundrigan;Emily Snook - 通讯作者:
Emily Snook
OTC Product: SinuCleanse for Rhinosinusitis
- DOI:
10.1331/154434506775268607 - 发表时间:
2006-01-01 - 期刊:
- 影响因子:
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Katherine Heller - 通讯作者:
Katherine Heller
The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa
全球化公平案例:关于非洲殖民主义、人工智能和健康的混合方法研究
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
M. Asiedu;Awa Dieng;Alexander Haykel;Negar Rostamzadeh;Stephen R. Pfohl;Chirag Nagpal;Maria Nagawa;Abigail Oppong;Sanmi Koyejo;Katherine Heller - 通讯作者:
Katherine Heller
Katherine Heller的其他文献
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{{ truncateString('Katherine Heller', 18)}}的其他基金
CAREER: Interacting Dynamic Bayesian Models for Social Behavior and Reasoning
职业:社会行为和推理的互动动态贝叶斯模型
- 批准号:
1553465 - 财政年份:2016
- 资助金额:
$ 4万 - 项目类别:
Standard Grant
BRAIN EAGER: Integrative Cross-Modal and Cross-Species Brain Models: Motivation and Reward
BRAIN EAGER:综合跨模式和跨物种大脑模型:动机和奖励
- 批准号:
1451017 - 财政年份:2014
- 资助金额:
$ 4万 - 项目类别:
Standard Grant
Bayesian Models of Social Behavior Using Online Resources
使用在线资源的社会行为贝叶斯模型
- 批准号:
1339593 - 财政年份:2013
- 资助金额:
$ 4万 - 项目类别:
Standard Grant
Bayesian Models of Social Behavior using Online Resources
使用在线资源的社会行为贝叶斯模型
- 批准号:
1048563 - 财政年份:2011
- 资助金额:
$ 4万 - 项目类别:
Standard Grant
Beyond Clustering: Unsupervised Modeling with Complex Representations
超越聚类:具有复杂表示的无监督建模
- 批准号:
EP/E042694/1 - 财政年份:2008
- 资助金额:
$ 4万 - 项目类别:
Fellowship
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