University of Wisconsin-Madison(UMW)
UMW简介
美国威斯康辛大学坐落于美国密歇根湖西岸的威斯康辛州首府麦迪逊市，有着风景如画的校园，成立于1848年, 是一所有着超过150年历史的悠久大学。威斯康辛大学是全美最顶尖的三所公立大学之一，是全美最顶尖的十所研究型大学之一。在美国，它经常被视为公立的常青藤。与加利福尼亚大学、德克萨斯大学等美国著名公立大学一样，威斯康辛大学是一个由多所州立大学构成的大学系统，也即“威斯康辛大学系统”（University of Wisconsin System）。在本科教育方面，它列于伯克利加州大学和密歇根大学之后，排在公立大学的第三位。除此之外，它还在本科教育质量列于美国大学的第八位。按美国全国研究会的研究结果，威斯康辛大学有70个科目排在全美前十名。在上海交通大学的排行中，它名列世界大学的第16名。威斯康辛大学是美国大学联合会的60个成员之一。 特专业介绍
威斯康辛大学麦迪逊分校设有100多个本科专业，一半以上可以授予硕士、博士学位，其中新闻学、生物化学、植物学、化学工程、化学、土木工程、计算机科学、地球科学、英语、地理学、物理学、经济
学、德语、历史学、语言学、数学、工商管理（MBA）、微生物学、分子生物学、机械工程、哲学、西班牙语、心理学、政治学、统计学、社会学、动物学等诸多学科具有相当雄厚的科研和教学实力，大部分在美国大学相应领域排名中居于前10名。
学术特
就学术方面的荣耀而言，威斯康辛大学麦迪逊校区的教职员和校友至今共获颁十七座诺贝尔奖和二十四座普立兹奖；有五十三位教职员是国家科学研究院的成员、有十七位是国家工程研究院的成员、有五位是隶属于国家教育研究院，另外还有九位教职员赢得了国家科学奖章、六位是国家级研究员（Searle Scholars）、还有四位获颁麦克阿瑟研究员基金。
威斯康辛大学麦迪逊校区虽然是以农业及生命科学为特，但是令人注目，同时也是吸引许多传播科系学子前来留学的最大诱因，则是当前任教于该校新闻及传播研究所、在传播学界有「近代美国传播大师」之称的杰克·麦克劳（Jack McLauld）。麦克劳教授对于传播媒体的功能及社会交互的研究，有其相当重要的地位。
1, UWM目前的计算机研究的情况。
UWM的计算机规模不算大，但质量不错，排名全美前十。
目前，UWM的计算机主要研究领域有：人工智能、计算生物学、计算机体系结构、计算机图形学、计算机网络、计算机安全、数据库、人机交互、数值分析、最优化、性能分析、编程语言与汇编、系统研究、CS理论。
下面分别简要介绍这些方向的研究情况：
人工智能
They are studying computer vision, machine learning, and biomedical informatics. Themes in computer vision include active approaches for medical image analysis, face recognition, and image-based modeling and rendering. Machine learning research focuses on both logical and statistical approaches. Current themes include design and analysis of novel algorithms for knowledge transfer in reinforcement learning, active learning for sequence models, combining logical and probabilistic representations of knowledge and multiple-instance learning. These algorithms are being applied to problems in bioinformatics, information retrieval and extraction, and the design of adaptive agents.
计算生物学
As a young science, computational biology offers a wealth of research opportunities. At the Universit
y of Wisconsin-Madison, computer science faculty are collaborating with faculty members in the biological and medical sciences on a variety of topics.
计算机体系结构
The computer architecture group at the University of Wisconsin-Madison is
one of the best in the world. The faculty have more than 100 years of
research experience resulting in key contributions to:
branch prediction (e.g., two-bit dynamic algorithm)
caches (non-blocking caches and cold, capacity, and conflict misses) coherence (write-once)
decoupled superscalar architectures (a forerunner to now conventional superscalar) distributed shared memory via hardware or software (Tempest, Typhoon, & Blizzard)) memory consistency models (processor consistency and data-race-free)
out-of-order execution (reorder buffers, RUU)
simulation (Wisconsin Wind Tunnel, SimpleScalar)
pipelines (optimal clocking)柴油机起动器
precise interrupts (reorder buffers and future files)
system area network interfaces (cacheable device registers)
synchronization (queue-on-lock-bit)
translation lookaside buffer and page table design (with superpages)
trace caches
Multiscalar architecture (speculative multithreading, Kestrel implementation, memory disambiguation/ARB)
value prediction
Token Coherence
生态砖LogTM - Log-Based Hardware Transactional Memory
GEMS - Wisconsin General Execution-Driven Multiprocessor Simulator
计算机图形学
Here is a list of the ongoing research projects.
Active:
Perceptually-Guided Analysis of Aggregation
Drawing on the methodology of perceptual psychology, we are analyzing the task of aggregation of data to determine if novel encodings can outperform standard designs for the affordance of quick summarization and comparison of data sets.
Virtual Reconstruction of complex interior rooms This work focuses on virtual reconstruction of building interiors from 3D scans provided by the Microsoft Kinect. The ultimate goal is to have a simple geometric representation of the room which may be thought as being equivalent to models made on commercial tools such as Autodesk Maya.
Deformable Solids
This research is focused on the development of efficient and accurate algorithms and numerical techniques for physics-based modeling and simulation of deformable solids using a variety of material models. This involves creating visually pleasing simulations in a reasonable amount of time while maintaining a high level of fidelity to the physics that govern the material behavior.
Designing Effective Gaze Mechanisms for Virtual Agents Virtual agents hold great promise in human-computer interaction with their ability to afford embodied interaction using nonverbal human communicative cues. Our goal is to explore how agents might achieve positive outcomes through seemingly subtle changes in gaze behavior and to identify specific design variables of gaze that might lead to such effects.
电子签章技术Visualization of Large Text Corpora
In collaboration with the Digital Humanities group, we are working on ways to visualize statistical patterns in large texts. Current projects include using tags to find out what sets apart Shakespeare from his contemporaries, and viewing the effects of Samuel Johnson's dictionary on the crystallization of the English language.
计算机网络
They are studing:
∙Network Protocols: SWORD
∙Network Traffic Management:
WAILworks, WAILnet, iSWORD
∙Network Measurement:
Packet Dynamics, Surveyor
Loss Measurement Tool
∙Network Vulnerability & Intrusion
Detection: DOMINO,
MRA of Network Anomalies, CIPART婴幼儿服装裁剪
计算机安全
They are studing:
∙Condor - High Throughput Computing
∙Fuzz Testing
∙Paradyn
∙WiSA
数据库系统
∙They have been conducting database related research for almost 30 years, and we are considered one of the best database groups in the country.
∙Our research topics include:
∙database performance
∙data mining
∙energy-efficient data processing
∙parallel database systems
∙scientific databases
打塞机∙visualization of large datasets
QDFILM
∙web database systems and information integration
人机交互
At the Human-Computer Interaction Lab, we are interested in designing and developing interactive systems—particularly social agents and robots—and understanding their relationship with people. Our current work spans analyzing and building computational models of human social behavior, developing robots and agents that can enact social behavior, and designing applications that can provide people with positive social and cognitive benefits in education, rehabilitation, and therapy.
数值分析
Four faculty: Carl de Boor, Seymour V.Parter, Amos Ron, John Strikwerda are
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