Now Available - Frontier Courses on Computer Science
2017-04-24
Frontier Courses on Computer Scieince
In the summer of 2017, the School of Electronics Engineering and Computer Science will open 9 summer courses.These courses will be taught by teachers from Peking University,Carnegie Mellon University,Oxford University,Imperial College London and other famous universities.

Applied Algorithms
By Prof. Tami Tamir, the Interdisciplinary Center of Israel.
Date:July 3-15,2017 08:00am~12:00am
 
40 Years Distributed System Research
By Prof.Zhang Hui,Carnegie Mellon University
Date:July 3-15,2017 10:00am~12:00am
 
Logic and Verification
By Anthony W. Lin,Associate Professor at Oxford university
Date:July 3-14,2017 13:00~17:00
 
Computer Graphics and Advanced Topics
By Bernhard Kainz,Lecture at Imperial College London
Date: July 3-14,2017 13:00~17:00
 
Picturing Quantum Processes
By Prof.Bob Coecke,Oxford University
Date:July 10-21,2017 13:00~17:00
 
Advanced Machine Learning: Online learning and Optimization
By Dr. Andras Gyorgy,Senior Lecturer at Imperial College London
Date:July 12-21,2017 8:00~12:00
 
Compact Data Structures for Big Data
By Prof.Shigang Chen,University of Florida 
Date:July 28 -August 4,2017 8:00~12:00
 
From these courses,you will gain:
l a deep comprehension of CS theory and scientific research front
l Interaction with outstanding students around the world
l Opportunity to vist Microsoft Asia Pacific Research Institute, Huawei, Lenovo and other Chinese and foreign enterprises
l opportunity to visit IT tycoons in Beijing,i.e.Microsoft,Huawei,Lenovo and others
 
Find more from http://net.pku.edu.cn/dlib/pkusummer/

Courses and Instructors
 
Applied Algorithms
By Prof. Tami Tamir, the Interdisciplinary Center of Israel.
Date:July 3-15,2017 08:00am~12:00am
 
The goal of this course is to help you become better prepared to tackle algorithm design for "real-world" problems. This includes (1) being familiar with fundamental resource-allocation problems and solutions, (2) understanding algorithmic techniques and the tradeoffs involved in designing correct, efficient, and implementable algorithms, (3) understanding challenges in algorithm design for selfish users, and (4) knowing how to model and abstract messy real-world problems into clean problems that can be attacked using known paradigms or specific algorithms.
Hopefully, you will gain a greater appreciation of the beauty and elegance of algorithms as well as where they are used in the real world. Specifically, we will study problems arising in production planning, operating systems, media-on-demand systems, networks, and more.
Get more from http://net.pku.edu.cn/dlib/pkusummer/summer2017/AppliedAlgorithms.html
Prof.Tami Tamir
Prof.Tami Tamir, is the Dean of the Efi Arazi School of Computer Science at the Interdisciplinary Center of Israel. Received her Ph.D. from the computer science department at the Technion in 2001. Her research interests include design and analysis of algorithms, resource allocation problems, multimedia-on-demand systems, and algorithmic game theory. Prior to her Ph.D. studies, she was a member of the performance enhancement group of Intel in Haifa. After graduation, she spent two years as a lecturer and postdoctoral fellow at the University of Washington in Seattle.
 
40 Years Distributed System Research
By Prof.Zhang Hui,Carnegie Mellon University
Date:July 3-15,2017 10:00am~12:00am
 
In this course, we will use a case-study-based approach to give an overview of four decades of research on operating systems and distributed systems. Topics include Concurrency, Fault Tolerence, Measurement, Storage, File Systems, Virtual Machine and Big Data. The learning objectives are:(1)To understand historical & intellectual contexts of the evolution of operating systems and distributed systems.(2)To appreciate different styles and methodologies of conducting systems research.
This course assumes a basic familiarity with operating systems concepts. Students are required to read about 2-3 research papers each day, write reviews and actively participate in class discussion.
Get more from http://soar.pku.edu.cn/teaching/DistSys/Summer17/
Prof. Zhang Hui
Prof.Zhang is a Professor in the Computer Science Department at the School of Computer Science at Carnegie Mellon University.He is also Co-Founder and CEO of Conviva Inc. During 2000 - 2003, He was the Chief Technical Officer of Turin Networks (merged with Force 10 Networks in 2009 and acquired by Dell in 2011).Prof Zhang's research interests lie in Internet, multimedia systems, resource management and quality of service. 
 
Logic and Verification
By Anthony W. Lin,Associate Professor at Oxford university
Date:July 3-14,2017 13:00~17:00
 
Logic is an indispensable tool in computer science and is used in every facet of the field. One may even argue that computers are built on top of logic (logic gates are the basic building blocks of computers). This course introduces fundamental concepts in logic in computer science with applications in algorithmic verification of computer systems, a field that was pioneered by 2007 Turing Award Winners (Clarke, Emerson, and Sifakis).
We will discuss propositional logic, first-order logic, temporal logics, their basic algorithmic problems (e.g. model checking and satisfiability), and how they can be applied for reasoning about computer systems (hardware, software, etc.). The course requires students to do both mathematical proofs and programming.
Get more from http://net.pku.edu.cn/dlib/pkusummer/summer2017/LogicVerification.html
Anthony W. Lin 
Anthony W. Lin is an Associate Professor in Programming Languages at University of Oxford Department of Computer Science and an Official Fellow at Kellogg College. Prior to joining Oxford, Lin was an assistant professor in computer science at Yale-NUS College (National University of Singapore). Broadly speaking, he is interested in all aspects (ranging from theory to systems) of the development of principled techniques that can make software less error-prone, and more efficient.Lin was a winner of Google Faculty Research Award (2017), EPSRC Research Fellowship (2010-2013), and LICS Kleene Award (2010). He regularly publishes, reviews, and serves in the program committee at premier conferences in the areas including CAV, CONCUR, FoSSaCS, ICALP, LICS, OOPSLA, POPL, and TACAS.
 
Computer Graphics and Advanced Topics
By Bernhard Kainz,Lecture at Imperial College London
Date: July 3-14,2017 13:00~17:00
 
This course covers the fundamental principles of computer graphics and advanced concepts and their use in prominent applications. After the course you will:(1)understand principles of computer generated imagery;(2)understand advanced issues related to customising programmable shading pipelines - such as vertex, fragment, and geometry shading stages;(3)understand the ideas behind surface geometry representation, 3D geometry, polyhedral rendering and ray-based image generation methods;(4)be able to solve a given computer graphics problems by going through the basic steps of rendering pipeline specification, algorithm selection, analysis and implementation;(5)be able to competently read 'foreign' OpenGL GLSL source code and computer graphics pipeline diagrams;(6)have developed solid understanding of the mathematical principles of computer graphics and the ability to put in practice the acquired knowledge and understanding.
Get more from http://net.pku.edu.cn/dlib/pkusummer/summer2017/ComputerGraphics.html
Bernhard Kainz
Bernhard Kainz is Lecturer in the Department of Computing at Imperial College London. He is  researching translational high-performance medical data analysis and interactive real-time image processing techniques as member of the Biomedical Image Analysis, BioMedIA Group in the section of Visual Information Processing. He collaborates intensively with King's College London, Division of Imaging Sciences and Biomedical Engineering, St. Thomas Hospital London and the department of Bioengineering at Imperial.
  
Picturing Quantum Processes
By Prof.Bob Coecke,Oxford University
Date:July 10-21,2017 13:00~17:00
 
This course provides an interdisciplinary introduction to the emerging field of quantum computer science, explaining basic quantum mechanics (including finite dimensional Hilbert spaces and their tensor products), quantum entanglement, its structure and its physical consequences (e.g. non-locality, no-cloning principle), and introduces qubits. We give detailed discussions of some key algorithms and protocols such as Grover's search algorithm and Shor's factorization algorithm, quantum teleportation and quantum key exchange. At the same time, this course provides an introduction to diagrammatic reasoning. As an entirely diagrammatic presentation of quantum theory and its applications, this course is the first of its kind.
Get more from http://net.pku.edu.cn/dlib/pkusummer/summer2017/QuantumProcesses.html
Prof.Bob Coecke
Bob Coecke is Professor of computer science at the University of Oxford,and fellow of Wolfson College.He is interested in the Foundations of Physics, in particular the structures involved, with a strong structural bias towards Logic, Order and Category Theory, and their applications.He leads a multidisciplinary research group, the Quantum Group, which now has 50 plus members. Nearly 1,000 pages of monographs co-authored with Kissinger were published at Cambridge University Press, which will be selected as a textbook. 
 
Advanced Machine Learning: Online learning and Optimization
By Dr. Andras Gyorgy,Senior Lecturer at Imperial College London
Date:July 12-21,2017 8:00~12:00
 
Designing autonomous systems that can adapt to their environments is arguably one of the most important goals in computer science and engineering. In some cases the environment is too complex to be modeled, and the best is to take a robust approach: continuously optimize the system as it interacts with its environment. Online learning, a subfield of machine learning, provides the theoretical foundations to solve such problems. The course will provide an introduction to online learning, covering the basic techniques and ideas. We will also discuss its connections and applications to other areas of machine learning, as well as how the same techniques lead to efficient methods for large scale optimization.
Get more from http://net.pku.edu.cn/dlib/pkusummer/summer2017/OnlineLearing.html
Dr. Andras Gyorgy
Dr. Andras Gyorgy was a Visiting Research Scholar in the Department of Electrical and Computer Engineering, University of California, San Diego, USA, in spring of 1998. In 2012-2015, he was a researcher in the Department of Computing Science, University of Alberta, Edmonton, AB, Canada. He joined the Department of Electrical and Electronic Engineering of Imperial College London, London, UK, where he is currently a Senior Lecturer.Dr. György received the Gyula Farkas prize of the János Bolyai Mathematical Society in 2001 and the Academic Golden Ring of the President of the Hungarian Republic in 2003.
 
Advanced Topics in Foundations of Databases
By Prof. Leonid Libkin,University of Edinburgh
Date:July 24-28,July 31,August 1,2017 13:00~17:00
 
The course is about foundations of big data. It aims to prepare students for conducting research in the areas of querying and managing big data, and expose them to current research and development in connection with big data theory. This course will cover fundamental issues in connection with three of four big V’s in the typical characterization of big data, namely, Volume, Variety and Veracity.
Get more from http://net.pku.edu.cn/dlib/pkusummer/summer2017/Databases.html
Prof. Leonid Libkin
Leonid Libkin is Professor of Foundations of Data Management in the School of Informatics at the University of Edinburgh. He was previously a Professor at the University of Toronto and a member of research staff at Bell Laboratories in Murray Hill. His main research interests are in the areas of data management and applications of logic in computer science. He has written five books and over 200 technical papers. His awards include a Marie Curie Chair Award, a Royal Society Wolfson Research Merit Award, and five Best Paper Awards. He has chaired programme committees of major database conferences (ACM PODS, ICDT) and was the conference chair of the 2010 Federated Logic Conference. He has given many invited conference talks and has served on multiple program committees and editorial boards. He is an ACM fellow, a fellow of the Royal Society of Edinburgh, and a member of Academia Europaea.
 
Compact Data Structures for Big Data
By Prof.Shigang Chen,University of Florida 
Date:July 28 -August 4,2017 8:00~12:00
 
The course teaches compact data structures and corresponding algorithms, probabilistic methods, and statistical tools for handling big data (especially big network data). At present the largest big data may be the data flow on the Internet. The analysis of big data can provide a theoretical basis for improving the network performance, network user experience and network security. However, network big data can not be retained. In this context, this course teaches a series of compact data structures and their theoretical analysis that have evolved over the past 30 years , which can be used to make big data smaller for storage and application.
Get more from http://net.pku.edu.cn/~yangtong/pages/SummerForm17.html
Prof.Chen Shigang
 Prof.Chen received his M.S. and Ph.D. degrees in Computer Science from University of Illinois at Urbana-Champaign in 1996 and 1999, respectively and B.S. degree in Computer Science from University of Science and Technology of China in 1993. He joined University of Florida as an assistant professor in 2002, and was promoted to associate professor in 2008 and to professor in 2013. He was a recipient of IEEE Communications Society Best Tutorial Paper Award in 1999, NSF CAREER Award in 2007, and Cisco University Research Award in 2007, 2012. He published 140+ peer-reviewed journal/conference papers and hold 12 US patents. Currently he serves as an associate editor for IEEE/ACM Transactions on Networking and IEEE Journal of RFID. He is an IEEE Fellow. 

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