I-Corps: Data Analytics and Automated Candidate Assessment

这个I-Corps项目的更广泛影响和商业潜力将提高大学生向公司转型的质量和效率。该平台将有可能为学生、公司和大学等多个客户群体提供解决方案，消除目前使求职和招聘成为一项耗时、昂贵、压力大且往往带有偏见的奋进的许多障碍。该产品的影响超出了特定的学术专业，并有可能涵盖所有科学主题，其中有一个强大的就业市场。最重要的是，该解决方案将通过自动化技能评估过程和最大限度地减少人力参与来消除当前对代表性不足的少数群体的潜在偏见。这个I-Corps项目将开发有效，公正和自动化的技能评估平台和算法。目标客户将是公司和大学毕业生，他们希望进入就业市场，没有以前的经验。这项研究将提出新的技术和工作工具，使用人工智能和机器学习方法，在面试过程中提供评估引擎和受访者之间的互动。该项目进一步开发了新颖的形式化方法和编程语言分析技术，以分析候选人在面试期间提交的答案，并自适应地为每个特定候选人选择下一个问题序列。一个现实的测试平台的基础设施上，候选人将被要求进行实验是用来评估候选人的专业知识水平。 这些自动化面试的新技术将为公司和学生减少成本和时间。

The broader impact and commercial potential of this I-Corps project will improve the transition quality and efficiency of university students to companies. This platform will potentially provide several customer segments such as students, companies and universities with solutions that remove many barriers that currently make job hunting and hiring a time-consuming, costly, stressful, and often biased endeavor. The impact of the product goes beyond a specific academic major, and has the potential to cover all scientific subject matters for which there is a robust job market. Most importantly, the solution will remove the current potential biases against underrepresented minorities by automating the skill assessment process and minimizing the human involvement in the process.This I-Corps project will develop effective, unbiased, and automated platforms and algorithms for skill assessment. The target customers will be the companies, and university graduates that would like to enter the job market with no prior experience. This research will propose novel techniques and working tools using artificial intelligence and machine learning methods to provide interaction during the interview process between the assessment engine and the interviewee. The project further develops novel formal methods and programming language analysis techniques to analyze the answers submitted by the candidate during the interview and adaptively select the next sequence of questions for each specific candidate. A realistic test-bed infrastructures on which the candidates will be asked to perform experiments is used to assess the expertise level of the candidates. These novel techniques for automated interviews will reduce the cost and time for both companies and students.