论文标题
下次数据科学火灾：数据科学指导的创新策略
The Data Science Fire Next Time: Innovative strategies for mentoring in data science
论文作者
论文摘要
随着数据挖掘研究和应用程序继续扩展到医学，金融，安全等各种领域，清楚地感觉到了对才华横溢和多样化的个人的需求。尤其如此，因为大数据计划已经在联邦，私营和学术领域脱颖而出，在国内和国际上提供了很多机会。扩大了对数据挖掘（BPDM）研讨会的参与是在7年前创建的，目的是促进数据科学和机器学习社区中少数群体和代表性不足的团体的指导，指导和联系，同时还丰富了一群才华横溢的学生的技术才能和曝光。迄今为止，它影响了330多名数据科学中代表性不足的学员的生活。我们提供了一个将有才华的学生与工业，学术界，专业社会和政府的创新研究人员联系起来的场所。我们的使命是促进BPDM参与者之间有意义的，持久的关系，以最终增加数据挖掘的多样性。这个最近的研讨会于2019年2月在华盛顿特区的霍华德大学举行。在这里，我们报告了我们在2019年BPDM上采取的指导策略以及如何收到的指导策略。
As data mining research and applications continue to expand in to a variety of fields such as medicine, finance, security, etc., the need for talented and diverse individuals is clearly felt. This is particularly the case as Big Data initiatives have taken off in the federal, private and academic sectors, providing a wealth of opportunities, nationally and internationally. The Broadening Participation in Data Mining (BPDM) workshop was created more than 7 years ago with the goal of fostering mentorship, guidance, and connections for minority and underrepresented groups in the data science and machine learning community, while also enriching technical aptitude and exposure for a group of talented students. To date it has impacted the lives of more than 330 underrepresented trainees in data science. We provide a venue to connect talented students with innovative researchers in industry, academia, professional societies, and government. Our mission is to facilitate meaningful, lasting relationships between BPDM participants to ultimately increase diversity in data mining. This most recent workshop took place at Howard University in Washington, DC in February 2019. Here we report on the mentoring strategies that we undertook at the 2019 BPDM and how those were received.
