Theory of Computation
Carl McTague studies the connection between exotic geometries 和 chromatic homotopy 理论, 这种联系揭示了拓扑和代数曲线的算术之间的惊人关系. Specifically, 他正致力于揭示椭圆上同调的高属推广，这是由Cayley平面的特殊几何(以及对特征的模空间进行分类)所提出的。. He is also working to compute the homotopy type of the string bordism spectrum MO<8> at the prime 3, based on computer-assisted computations of its BP-homology, considered as a Hopf ring. 他正在努力形式化(在Coq中)并将机器学习应用于EHP和Adams谱序列计算. He has also investigated novel uses of curvature in data analysis, pattern formation in cellular automata, as well as computational 和 geometric aspects of bookbinding 和 music composition.
传统的网络优化问题电子游戏正规平台侧重于开发顺序设置的算法，其中计算在单个处理器中完成. 今天, 许多现实世界的网络规模已经变得如此庞大，以至于单个处理器无法有效地处理所有的计算, either due to inefficiency or the infeasibility of global access. 这推动了网络优化问题的分布式和并行算法的电子游戏正规平台. For many network optimization problems, 我们仍然不知道如何在这些设置中有效地匹配相同的序列算法的解质量. Hsin-Hao Su致力于为许多网络优化问题开发高效的分布式和并行算法(在运行时间和解决方案质量上有可证明的保证), including matching, clustering, 路由, 等.
霍华德·斯特劳宾的大部分电子游戏正规平台都集中在有限自动机和逻辑之间的联系上, through the medium of abstract algebra. 这导致了许多不同逻辑的表达能力的有效表征，这些逻辑用于表达可以由有限自动机测试的词的属性. Outst和ing open problems center around extending this framework to regular languages of trees 和 forests; 和 using it to study low-depth circuit complexity.
Ilya Volkovich电子游戏正规平台了随机性在计算中的作用:给定一个有效的随机化算法, can we convert it into a deterministic one of comparable efficiency? 他还电子游戏正规平台了基本问题:各种密码原语的必要和充分假设是什么? Recently, there has been a flurry of new methods for analysis of algorithms. However, many of these methods require extensive background knowledge. The goal of 教授. Volkovich's research is simplification of the analysis, making it more accessible to a wider audience, including undergraduates. 他的一些电子游戏正规平台成果已经被纳入了课程，并被纳入了算法教科书.
Artificial Intelligence & Machine Learning
塞尔吉奥·阿尔瓦雷斯(Sergio Alvarez)正在与康奈尔护理学院和塔夫茨医学中心的本科生和同事合作，电子游戏正规平台从可穿戴传感器获得的心脏活动数据的机器学习, aiming to enable home monitoring of heart failure patients. Seed funding has been provided by the Schiller Institute at Boston College. 他还在机器学习方面追求更理论化的方向，涉及核函数的渐近性和相关的再现核希尔伯特空间.
教授. Bento's research involves underst和ing how to solve problems over networks. 这些网络可以表示需要协作解决问题的一组节点上的通信约束, or mathematical constraints among the variables of a mathematical model. In particular, 他非常关注图形模型和分布式优化算法背景下的网络. His work finds application in robot path planning, combinatorial optimization, video stylization, computer vision tracking, 和, more recently, systems biology. 教授. Bento目前是一个大型跨学科合作项目的五个pi之一，旨在了解抗生素耐药性的机制. This collaboration involves the van Opijnen Lab in the Department of 生物学 at Boston College, 和 a team of researchers at Tufts University, St. Jude Children's Hospital, 和 the University of Pittsburgh. Their joint research is supported by a $10 million U01 grant from NIH/NIAID.
Data is all around us in our daily lives, ranging from everyday human activity to environmental 和 socio-economic indicators. 理解数据正成为一项重要的技能，让每个人都能更好地了解自己，让我们的社会变得更好.教授. Kim's research vision lies in the democratization of data, lowering barriers for everyone to underst和 和 communicate complex data. 他通过使用可视化作为外部认知辅助工具来帮助人们看到看不见的东西来应对这一挑战. Within the broad context of human-computer interaction, his research investigates innovative approaches to interact with data, going beyond traditional expert systems 和 addressing the needs of a broader audience.
Technologies like Siri 和 ChatGPT are available only for a h和ful of the world's 7,000 languages. Emily Prud'hommeaux正在使用变形神经网络和统计方法来帮助电子游戏正规平台人员和土著社区记录和振兴濒危和资源不足的语言.
计算机视觉(CV)是人工智能的一个分支，它使计算机能够进行重建, recognize, 和 re-organize the rich information from input images. 特别是自动化生物医学图像分析与CV方法大大加快了科学发现和医疗创新.教授. Wei's research focuses on the interplay between natural 和 artificial intelligence. On the one h和, 他一直在开发新的计算机视觉方法，从大规模显微镜图像中重建神经元的详细接线图, revealing the brain's workings 和 accelerating drug discovery for brain diseases. On the other h和, 他一直在推进神经科学启发的设计，以增强视频理解应用的计算机视觉方法. In addition, 他一直致力于开源生物医学图像分析解决方案，以协助生物学合作者, psychology, radiology, 和 pathology.
Yuan Yuan's research primarily focuses on deep learning, computer vision, 和 the application of AI in healthcare 和 medicine. Her work has attracted widespread media attention, featuring in outlets such as Forbes, The Washington Post, 英国广播公司, TechCrunch, 和 Engadget, among others. Remarkably, 她在用于帕金森病诊断和进展跟踪的人工智能驱动的数字生物标志物方面的工作被公认为2022年医学十大显著进展之一.
George Mohler is working on a NSF funded SCC project 建造低成本的枪击探测装置，以促进社区主导的暴力中断工作. The devices utilize transformer neural networks to classify audio running on Raspberry Pis. 然后，通过手机应用程序实时通知暴力中断工作人员所在社区的枪击事件，并可能进行干预，以防止报复性枪支暴力.