REU Site: Artificial Intelligence for Computational Creativity

这个REU网站将使一组不同的本科生参与生产的原始，跨学科的人工智能计算创造力的研究。它将帮助个别学生建立关键的计算机科学研究能力，沟通和专业技能，以增加他们的信心，并获得更好的了解研究过程。他们将获得研究生学位的途径的理解，并准备申请过程。更广泛地说，该项目将开发一个由不同学生研究人员组成的多年管道，帮助提高人工智能和视觉计算领域的多样性。虽然学生可能是人工智能研究的新手，但这一领域的创造力应用可以帮助弥合差距，并通过帮助学生实现个人创造性愿景和人工智能研究的交叉点，让他们对计算机科学感到兴奋。该网站将汇集领导联盟少数民族服务和以本科生为重点的机构的完善网络，提供多个人工智能研究机会，以培养高素质的研究生学位课程的多样化学生。研究项目涵盖机器学习、强化学习、计算机视觉、自然语言处理和机器人等人工智能学科，以及图形学和人机交互等相邻学科。感兴趣的领域包括创意生成模型，评估生成的内容，以及创意AI的用户体验设计。学生将在他们的研究实验室由教师和研究生密切指导，并由周围的研究小组和领导力联盟提供的资源支持。他们将接受人工智能和机器学习基础的技术培训，包括深度神经网络。他们将接受阅读、写和展示工作的培训，并将在研究研讨会和讲习班上将这些技能付诸实践。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This REU site will enable a diverse group of undergraduates to participate in the production of original, interdisciplinary research on artificial intelligence for computational creativity. It will help individual students build critical computer science research capacity, communication and professional skills, to increase their confidence and gain a greater understanding of the research process. They will gain understanding of pathways to graduate degrees and prepare for the application process. More generally, this project will develop a multi-year pipeline of diverse student researchers, helping to improve diversity in the fields of AI and visual computing. While students may be new to AI research, creativity applications in this field can help bridge the gap and get students excited about computer science by helping them realize the intersection of their personal creative visions and AI research. This site will bring together the well-established network of Leadership Alliance minority-serving and undergraduate-focused institutions with multiple AI research opportunities to produce cohorts of diverse students highly-qualified for graduate degree programs. The research projects encompass the AI disciplines of machine learning, reinforcement learning, computer vision, natural language processing, and robotics, plus adjacent disciplines such as graphics and human-computer interaction. Areas of interest include creative generative models, evaluating generated content, and user experience design for creative AI. Students will be closely mentored by faculty and graduate students in their research labs, and supported by surrounding research groups and the resources provided by the Leadership Alliance. They will receive technical training in AI and machine learning fundamentals, including deep neural networks. They will be trained in reading, writing, and presenting their work and will put these skills into practice at research symposia and workshops.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.