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工程与应用科学

计算机科学

 学校:  

布朗大学

   硕士生项目

MS in Computer Science

标准考试成绩要求

TOFEL:105

IELTS:7.5

学年学制

3-4 semesters

学年学费

52,231美元

奖学政策

暂无

所在校区

暂无

专业排名

暂无

招生人数

暂无

申请材料清单

Academic performance: The GPA isn't the only criterion. Grades in computer science and related disciplines (for example, math) count more than grades in other areas. Also, we take into account the fact that at some very competitive schools it's very difficult to achieve a high GPA.

Letters of recommendation: Letters must give a detailed, factual, and candid evaluation of your capabilities. Rankings and comparisons with other students are very useful. Ask your recommenders to follow these guidelines. Remind your recommenders of deadlines to ensure they meet them. We routinely find ourselves unable to admit potentially qualified students because their letters of recommendation haven't arrived in time.

Work experience: Please describe any work experience you might have. Obviously, not all applicants have work experience, but for those who do, some description of it helps us better evaluate your application.

General GRE scores: These scores let us compare the basic skills of applicants from diverse backgrounds. We're aware that test performance can improve considerably with practice, some people don't perform well on tests, and the verbal GRE is harder for some foreign applicants. While we don't require general test scores, the test provides an additional objective form of evaluation that's often helpful in determining your abilities.

Subject GRE scores: The subject test scores are most useful when they're from the computer science exam. While we don't require subject test scores, the test provides an additional objective form of evaluation that's often helpful in determining your abilities.

TOEFL and IELTS scores: If your native language isn't English and you haven't received a college degree from an institution in an English-speaking country, you must take the TOEFL exam. Additional evidence (for example, a certificate of completion of an English course) may also be submitted. We generally don't consider applicants who have scored below 620 (PBT) or 260 (CBT) or IBT (105), and prefer scores higher than that. The corresponding minimum IELTS score is 7.5. If you feel you're exempt from taking the TOEFL, please email the Graduate School directly to get a waiver.

Statement: The statement that accompanies your application helps us learn more about you.

Awards, honors, and prizes: Unless they're well known (for example, an NSF fellowship or graduation with honors), please give details about them (how many candidates? how many awards? what were the selection criteria?). This is especially important for foreign applicants. If these awards are really important, we'd expect your recommenders to mention them.

Research experience: Research experience isn't required for Master's applicants and many of our applicants don't have any, but you can use experience you've had to demonstrate your ability to handle graduate-level computer science material.


截止申请时间:

3月15日 秋季/10月15日 春季

专业介绍

Since our inception in 1979, the Computer Science Department at Brown has forged a path of innovative information technology research and teaching at both the undergraduate and graduate levels. From our modest beginnings as an interest group within the Divisions of Applied Mathematics and Engineering in the 1960s to its current stature as one of the nation's leading computer science programs, the Computer Science Department has continuously produced prominent contributors in the field, at both the undergraduate and graduate levels.

Multidisciplinary

We are a diverse community of scholars engaged in all aspects of research, teaching and mentoring in computer science and its related interdisciplinary disciplines. Realizing the importance of computing and algorithmic thinking in so many scientific, social and technological endeavors, we collaborate extensively with colleagues in archaeology, applied mathematics, biology, cognitive and linguistic sciences, economics, engineering, mathematics, medicine, physics and neuroscience.

Our undergraduate offerings reflect the department's multidisciplinary orientations, with joint concentrations in mathematics, applied mathematics, computational biology and economics. We have strong undergraduate research groups in graphics, neuroscience and robotics as well as a long history of involving undergraduates in projects that span disciplinary boundaries. Graduate students find it easy to tailor their education to meet the challenges of multidisciplinary research and commonly have advisors in two or more departments.

Research

Research in the department crosses traditional boundaries and projects spring from shared interests more than from established groups. Faculty work with post-doctoral students, graduate students and undergraduates. Ideas and expertise are drawn from other disciplines and departments at the University. A long tradition of combining theory and practice is as strong and relevant today as it ever was. Research areas the department participates in include: algorithms; cloud computing; computational biology; computational geometry; computational neuroscience; computational photography; computer graphics; computer networks; computer vision; cryptography; data management; distributed systems; educational technology; electronic commerce; information visualization; intelligent agents; machine learning; mobile and ubiquitous computing; nanocomputing; natural language processing; operating systems; optimization; parallel computing; programming languages; robotics; scientific visualization and modeling; security and privacy; sensor networks; software engineering; user interfaces; theory of computation; verification and reliable systems; virtual reality.

Teaching

Excellence in teaching and mentoring is highly prized in our department. Our faculty is encouraged to develop new, more effective ways of teaching computer science and to lead in the development of new curricula and materials for teaching. For example, our introductory courses are subject to constant revision to keep the content fresh and exciting. Junior and senior faculty alike teach undergraduate courses; the teaching load distributed so that junior faculty can spend more time getting their research on track.

Graduate Program

Graduate students work closely with faculty and with one another and are supported through a variety of university, government and corporate grants and fellowships. The research facilities available to graduate students are state of the art, and their offices, intermingled with the faculty offices, are comfortable and spacious. Open areas for socializing and working are also intermingled, and well-equipped kitchens and common areas provide an inviting environment for impromptu brainstorming and collaborative research.

Undergraduate Program

We have a long history of involving undergraduates in research and education. Encouraging undergraduates to do research was novel when we began, more than 25 years ago, and we remain unique in the extent to which undergraduates create and take part in research programs and coauthor research papers. We expect that most of our undergraduate concentrators will participate in research during their time at Brown, and we make sure that they have ample opportunity to exercise their interests.

In our extensive undergraduate teaching assistant (UTA) program, qualified undergraduates participate in all aspects of course development and instruction and play an important peer-teaching and mentoring role in all our undergraduate courses. Having UTAs run study sections and explain computing concepts to their peers appropriately blurs the line between teaching and learning and encourages all students to take an active part in their education. This early teaching experience positions students to become leaders and prepares them for the many computing careers in which team-based, collaborative problem solving is the norm. Our UTA program is frequently cited by our graduates, their employers and their graduate advisors as an important contributing factor to the high quality of our graduates and goes far to account for the large number of our graduates who become leaders in academia and industry.

Providence

Our home city is one of the most vibrant, affordable, and lively places around. We've recently started compiling rave reviews about its cultural attractions, quality of life, and food here.

Center for Computational Molecular Biology

The Center for Computational Molecular Biology (CCMB) at Brown was founded in September 2003 with the aim of establishing a world-class center for research and scholarship in this new discipline. The CCMB's central mission is to make breakthrough discoveries in the life sciences at the molecular and cellular level through the creative application of existing data analytic methods, and the development of novel computational, mathematical, and statistical technologies required exploit the opportunities emerging from advances in genomics and proteomics. Computer Science is one of several departments at Brown which is affiliated with the CCMB.

Industrial Partners Program

Our Industrial Partners Program (IPP) exists to provide interaction between the academic and corporate information technology communities and allows us to offer corporations exceptional opportunities for productive collaboration with a leading academic research institution. We are committed to progress in research and the transfer of state-of-the-art technologies beyond the campus. We are also committed to informing our students and faculty about the career opportunities in industry and keeping them current on the technical problems that drive industrial research and development. Strong, mutually beneficial links with leaders in computer-related industries will advance these goals.

Paris C. Kanellakis Memorial Lecture

Each year, the department hosts a Paris C. Kanellakis Memorial Lecture. This lecture series honors Paris Kanellakis, a distinguished computer scientist who was an esteemed and beloved member of the Brown Computer Science department. Paris joined the Computer Science Department in 1981 and became a full professor in 1990. His research area was theoretical computer science, with emphasis on the principles of database systems, logic in computer science, the principles of distributed computing and combinatorial optimization. He died in an airplane crash on December 20, 1995, along with his wife, Maria Teresa Otoya, and their two young children, Alexandra and Stephanos Kanellakis.

Artemis

The Artemis Project is a free, five-week summer day camp for rising 9th grade girls in the Providence area who are interested in learning about science and technology. Traditionally, it has been run by four undergraduate women from Brown University in connection with Brown's Computer Science Department. By teaching students computer skills, programming, and computer science concepts through engaging activities, the Artemis Project encourages young women to join the field of computer science.

Facilities

Located on the top three floors of Brown's Center for Information Technology, members of the computer science community enjoy large open-plan spaces designed to support collaborative research and facilitate social and intellectual interaction. The department's computing infrastructure is separate from the rest of the university and supports all our administrative, research and educational needs. In particular, we maintain several state-of-the-art classrooms and computing labs with high-performance computing clusters and graphics workstations. The Center for Computation and Visualization hosts multiple parallel high-performance computer clusters and an Immersive Virtual Reality Cave which are used for both research and teaching.

课程设置

  • The Digital World
  • Introduction to Computation for the Humanities and Social Sciences
  • Introduction to Scientific Computing and Problem Solving
  • A Data-Centric Introduction to Programming
  • A First Byte of Computer Science
  • Building a Web Application
  • Computers and Human Values
  • Talking with Computers
  • Data Fluency for All
  • User Interfaces and User Experience
  • Introduction to Object-Oriented Programming and Computer Science
  • Introduction to Algorithms and Data Structures
  • CS: An Integrated Introduction
  • CS: An Integrated Introduction
  • Accelerated Introduction to Computer Science
  • Introduction to Discrete Structures and Probability
  • Introduction to Computer Systems
  • Introduction to Software Engineering
  • Introduction to Computer Systems
  • Introduction to Systems Programming
  • Introduction to Probability and Computing
  • Models of Computation
  • Directions: The Matrix in Computer Science
  • Educational Software Seminar
  • Introduction to Computation for the Humanities and Social Sciences
  • Theory of Computation
  • Computer Graphics
  • Computer Graphics Lab
  • Introduction to Computer Animation
  • Compilers and Program Analysis
  • Database Management Systems
  • Intermediate 3D Computer Animation
  • Computational Photography
  • User Interfaces and User Experience
  • Fundamentals of Computer Systems
  • Creating Modern Web Applications
  • Innovating Game Development
  • Virtual Reality Design for Science
  • Distributed Computer Systems
  • Artifical Intelligence
  • Machine Learning
  • Computer Vision
  • Probability and Computing
  • Computational Linguistics
  • Deep Learning
  • Building Intelligent Robots
  • Introduction to Combinatorial Optimization
  • Introduction to Cryptography and Computer Security
  • Probabilistic Methods in Computer Science
  • Design and Analysis of Algorithms
  • Information Retrieval and Web Search
  • Introduction to Computational Complexity
  • Real-time and Embedded Software
  • Building High-Performance Servers
  • Computer Systems Security Lab
  • Software Security and Exploitation
  • Computer Systems Security
  • Operating Systems
  • Computer Networks
  • Operating Systems Laboratory
  • Programming Languages Lab
  • Design and Implementation of Programming Languages
  • Multiprocessor Synchronization
  • Parallel and Distributed Programming
  • Cybersecurity and International Relations
  • Computational Molecular Biology
  • Algorithmic Foundations of Computational Biology
  • Information Theory
  • csciStartup
  • Advanced Programming for Digital Art and Literature
  • Human-Robot Interaction Seminar
  • Intro. to Machine Learning
  • Computational Photography
  • Computational Topology
  • Designing, Developing and Evaluating User Interfaces
  • Introduction to Computational Geometry
  • Algorithmic Foundations of Computational Biology
  • 2D Game Engines
  • Cybersecurity and International Relations
  • Programming for the Humanities and Social Sciences
  • Compiler Practice
  • Fundamentals of Computer Systems
  • Advanced Animation Production
  • Topics in 3D Game Engine Development
  • Advanced GPU Programming
  • Topics in Data Science
  • Software Foundations
  • Logic for Systems
  • Computational Methods for Biology
  • Data Science
  • Virtual Citizens or Subjects? The Global Battle Over Governing Your Internet
  • Designing Humanity Centered Robots
  • Computer Systems Security: Principles and Practice
  • Computers, Freedom and Privacy: Current Topics in Law and Policy
  • Optimization Methods in Finance
  • Software Security and Exploitation
  • Interdisciplinary Scientific Visualization
  • Algorithmic Game Theory
  • Introduction to Robotics
  • Virtual Reality Software Review
  • CS for Social Change
  • Individual Independent Study
  • Independent Study in 2D Game Engines
  • Topics in 3D Game Engine Development
  • Interactive Computer Graphics
  • Topics in Database Management
  • Human-Computer Interaction Seminar
  • Human Factors and User Interface Design
  • Software Engineering
  • Interdisciplinary Scientific Visualization
  • Statistical Models in Natural-Language Understanding
  • Probabilistic Graphical Models
  • Topics in Game-Theoretic Artificial Intelligence
  • Deep Learning
  • Advanced Algorithms
  • Optimization Algorithms for Planar Graphs
  • Approximation Algorithms
  • Computational Geometry
  • Internet and Web Algorithms
  • Advanced Probabilistic Methods in Computer Science
  • Parallel Computation: Models, Algorithms, Limits
  • Advanced Complexity
  • Introduction to Nanocomputing
  • Solving Hard Problems in Combinatorial Optimization: Theory and Systems
  • Advanced Topics in Cryptography
  • Programming Language Theory
  • Topics in Parallel & Distributed Computing
  • Medical Bioinformatics
  • Algorithms for Cancer Genomics
  • Stochastic Optimization
  • Large-Scale Networked Systems
  • Cognition, Human-Computer Interaction and Visual Analysis
  • Special Topics in Computational Linguistics
  • Medical Bioinformatics: Disease Associations, Protein Folding and Immunogenomics
  • Topics in Brain-Computer Interfaces
  • Special Topics in Machine Learning
  • Topics in Computer Vision
  • Special Topics in Advanced Algorithms
  • Topics in Distributed Databases & Systems
  • Special Topics on Networking and Distributed Systems
  • Topics in Applied Cryptography
  • Online Algorithms
  • Topics in Programming Languages & Systems
  • Robot Learning and Autonomy
  • Robots for Education
  • Data-Driven Vision and Graphics
  • Autonomous Agents and Computational Market Design
  • Topics in Information Retrieval and Web Search
  • Topics in Computer System Security
  • Learning and Sequential Decision Making
  • Computational Protein Folding
  • Algorithms for Big Data
  • Computer Vision for Graphics and Interaction
  • Topics in Advanced Algorithmics: Algorithmic Game Theory, 3D Computational Geometry, Quantum Computing
  • Topics in Collaborative Robotics
  • Human-Computer Interaction Seminar
  • Advanced Algorithms Seminar
  • Advanced Algorithms in Computational Biology
  • Foundations of Prescriptive Analytics
  • Human-Robot Interaction Seminar
  • Topics in Advanced Algorithms
  • Personal Informatics Seminar
  • Distributed Computing through Combinatorial Topology
  • Data-Drive Computer Vision
  • Topics in Software Security
  • Systems for Interactive Data Exploration
  • Creative Artificial Intelligence for Computer Graphics Reintegrating AI
  • Special Topics in Formal Semantics and Notional Machines
  • Advanced Algorithmic Game Theory
  • Blockchains and Cryptocurrencies
  • Topics in Computer Science Education Research
  • The Design and Analysis of Trading Agents
  • Machine Learning Reading Group
  • A Data-Centric Introduction to Programming
  • Introduction to Topics in Data and Computational Science
  • Data and Computational Science
  • 3D Photography
  • Pattern Recognition and Machine Learning
  • Computational Theory of Molecular Evolution
  • 3D Photography and Geometry Processing
  • Internet of Everything
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