AF: Small: Applied Algorithims: Tech Transfer from the Algorithims Toolbox II

在过去的几十年里，算法领域已经开发出一套理论技术工具箱，让计算机系统用更少的资源做更多的事情--更快地解决更困难的问题，使用更少的内存，更少的与其他计算机的通信，以及更少的人类用户的帮助。 算法研究成功的一个衡量标准是大量实现的系统，其设计受到算法社区贡献的影响。 还有更多这样的成功等待着个人或团体，他们可以在现有的算法技术和现有的应用问题之间建立联系。 通常，最大的挑战是认识到从业者的问题陈述和正确的算法解决技术之间的联系。 这项研究解决了从算法工具箱到其他计算机科学领域的“技术转移”过程。研究人员正在与计算机科学各个领域的从业者密切合作，以确定其有效解决方案将推动其研究议程的计算问题，挖掘理论工具箱，以找到适当适应的技术，可以用来有效地解决这些问题，并协助这种适应。 正在解决的领域包括自然语言处理，生物网络中影响路径的检测，考虑不确定延迟的交通路线规划，有效利用通信带宽的网络编码，以及有效利用众包计算。 但是，而不是由一个特定的问题域驱动，研究人员感兴趣的是在整个过程中应用算法的理论工作的问题，在实际领域，并始终寻求新的应用问题，可以受益于这种方法。成功完成拟议的工作将有助于促进许多不同的计算机科学分支。 对计算机科学其他分支的贡献将反过来使它们能够实现对社会产生广泛影响的目标。 研究人员还希望增加理论家和实践者之间的联系，增加合作和算法在理论上的成功应用，而不是直接在这个项目中进行。 该项目将通过继续雇用大量学生并关注性别多样性，为研究培训做出贡献。

Over the past decades, the field of algorithms has developed a toolbox of theoretical techniques that let computer systems to do more with less---to solve harder problems more quickly, using less memory, less communication with other computers, and less of a human user's assistance. One measure of algorithms' research success has been the large number of implemented systems whose designs have been impacted by contributions from the algorithms community. There are many more such successes waiting in the wings for individuals or groups who can draw the connection between an existing algorithmic technique and an existing applied problem. Often, the biggest challenge is recognizing the connection between the practitioner's problem statement and the proper algorithmic solution techniques. This research addresses the process of ``technology transfer'' from the algorithmic toolbox to other computer science domains.The investigator is working closely with practitioners in various areas of computer science to identify computational problems whose efficient solution would advance their research agendas, dig through the theory toolbox to find techniques that, properly adapted, can be used to efficiently solve those problems, and assist in such adaptation. Domains being addressed include natural language processing, detection of influence pathways in biological networks, traffic route planning that accounts for uncertain delays, network coding for efficient use of communication bandwidth, and efficient use of crowdsourced computation. But rather than being driven by a particular problem domain, the investigator is interested in the overall process for applying theoretical work in algorithms to problems in the practical domain, and is always seeking new applied problems that can benefit from this approach.Successful completion of the proposed work will contribute advancement to many different branches of computer science. The contributions to other branches of computer science will, in turn, allow them to achieve their goals of broad impact on society. The investigator also hopes to increase the general sense of connection between theoreticians and practitioners, yielding increased collaborations and successful applications of algorithms to theory beyond those made directly during this project. The project will contribute to research training by continuing to employ large numbers of students with attention given to gender diversity.