T HEORETICAL C OMPUTER S CIENCE Real World Problems Abstract Models Modeling Solutions Math Tools Inspire More Problems.

Slides:



Advertisements
Similar presentations
1 Perspectives from Operating a Large Scale Website Dennis Lee VP Technical Operations, Marchex.
Advertisements

Decision Support and Artificial Intelligence Jack G. Zheng July 11 th 2005 MIS Chapter 4.
ITRS Roadmap Design + System Drivers Makuhari, December 2007 Worldwide Design ITWG Good morning. Here we present the work that the ITRS Design TWG has.
Grant review at NIH for statistical methodology Jeremy M G Taylor Michelle Dunn Marie Davidian.
Developing a Learning Culture in Public Administrations EAS 7 March 2008.
Pathway to Proficiency Chaffey Colleges Plan to Achieve Proficiency in Student Learning Outcomes March, 2010.
Impact of Interference on Multi-hop Wireless Network Performance Kamal Jain, Jitu Padhye, Venkat Padmanabhan and Lili Qiu Microsoft Research Redmond.
Energy-efficient Task Scheduling in Heterogeneous Environment 2013/10/25.
Schulich School of Medicine & Dentistry The University of Western Ontario London Regional Genomics Centre Next Generation Sequencing Meeting April 1, 2010.
Distributed Systems Major Design Issues Presented by: Christopher Hector CS8320 – Advanced Operating Systems Spring 2007 – Section 2.6 Presentation Dr.
Jose-Luis Blanco, Javier González, Juan-Antonio Fernández-Madrigal University of Málaga (Spain) Dpt. of System Engineering and Automation May Pasadena,
The Decision Tool for MPP-Dairy Mark Stephenson Director of Dairy Policy Analysis University of Wisconsin.
13-Optimization Assoc.Prof.Dr. Ahmet Zafer Şenalp Mechanical Engineering Department Gebze Technical.
Learning in Neural and Belief Networks - Feed Forward Neural Network 2001 년 3 월 28 일 안순길.
Presented by Dealing with the Scale Problem Innovative Computing Laboratory MPI Team.
A NOVEL APPROACH TO SOLVING LARGE-SCALE LINEAR SYSTEMS Ken Habgood, Itamar Arel Department of Electrical Engineering & Computer Science GABRIEL CRAMER.
1 An Adaptive GA for Multi Objective Flexible Manufacturing Systems A. Younes, H. Ghenniwa, S. Areibi uoguelph.ca.
Kick-off Meeting, July 28, 2008 ONR MURI: NexGeNetSci Distributed Coordination, Consensus, and Coverage in Networked Dynamic Systems Ali Jadbabaie Electrical.
Locating conserved genes in whole genome scale Prudence Wong University of Liverpool June 2005 joint work with HL Chan, TW Lam, HF Ting, SM Yiu (HKU),
Introduction BNFO 602 Usman Roshan. Course grade Project: –Find a bioinformatics topic by Feb 5th. This can be a paper or a research question you wish.
AI and Bioinformatics From Database Mining to the Robot Scientist.
Claude TADONKI Mines ParisTech – LAL / CNRS / INP 2 P 3 University of Oujda (Morocco) – October 7, 2011 High Performance Computing Challenges and Trends.
Introduction to Evolutionary Computation  Genetic algorithms are inspired by the biological processes of reproduction and natural selection. Natural selection.
Map-Reduce and Parallel Computing for Large-Scale Media Processing Youjie Zhou.
Evolutionary Algorithms Guilherme Oliveira. What is it about ? Population based optimization algorithms Reproduction Mutation Recombination Selection.
Learning Programs Danielle and Joseph Bennett (and Lorelei) 4 December 2007.
OPL: Our Pattern Language. Background Design Patterns: Elements of Reusable Object-Oriented Software o Introduced patterns o Very influential book Pattern.
Energy, Energy, Energy  Worldwide efforts to reduce energy consumption  People can conserve. Large percentage savings possible, but each individual has.
CS 712 | Fall 2007 Using Mobile Relays to Prolong the Lifetime of Wireless Sensor Networks Wei Wang, Vikram Srinivasan, Kee-Chaing Chua. National University.
1 Bio + Informatics AAACTGCTGACCGGTAACTGAGGCCTGCCTGCAATTGCTTAACTTGGC An Overview پرتال پرتال بيوانفورماتيك ايرانيان.
Sensor-Based Fast Thermal Evaluation Model For Energy Efficient High-Performance Datacenters Q. Tang, T. Mukherjee, Sandeep K. S. Gupta Department of Computer.
WMU CS6260 Parallel Computations II Spring 2013 Presentation #2 Professor: Dr. de Doncker Name: Xuanyu Hu March/11/2013.
Advances in Modeling Neocortex and its impact on machine intelligence Jeff Hawkins Numenta Inc. VS265 Neural Computation December 2, 2010 Documentation.
BLAST: A Case Study Lecture 25. BLAST: Introduction The Basic Local Alignment Search Tool, BLAST, is a fast approach to finding similar strings of characters.
Sogang University Advanced Computing System Chap 1. Computer Architecture Hyuk-Jun Lee, PhD Dept. of Computer Science and Engineering Sogang University.
Kevin Ross, UCSC, September Service Network Engineering Resource Allocation and Optimization Kevin Ross Information Systems & Technology Management.
Center for Evolutionary Functional Genomics Large-Scale Sparse Logistic Regression Jieping Ye Arizona State University Joint work with Jun Liu and Jianhui.
For Wednesday No reading No homework There will be homework for Friday, as well the program being due – plan ahead.
Mobile Agent Migration Problem Yingyue Xu. Energy efficiency requirement of sensor networks Mobile agent computing paradigm Data fusion, distributed processing.
Embedded System Lab 김해천 Thread and Memory Placement on NUMA Systems: Asymmetry Matters.
1 HKU CS Bioinformatics Research Siu Ming Yiu Department of Computer Science The University of Hong Kong Other faculty members: Prof. Francis Chin Prof.
Introduction to Bioinformatics Dr. Rybarczyk, PhD University of North Carolina-Chapel Hill
EB3233 Bioinformatics Introduction to Bioinformatics.
An approach to carry out research and teaching in Bioinformatics in remote areas Alok Bhattacharya Centre for Computational Biology & Bioinformatics JAWAHARLAL.
COMPUTATIONAL BIOLOGIST DR. MARTIN TOMPA Place of Employment: University of Washington Type of Work: Develops computer programs and algorithms to identify.
Biocomputation: Comparative Genomics Tanya Talkar Lolly Kruse Colleen O’Rourke.
1 Thermal Management of Datacenter Qinghui Tang. 2 Preliminaries What is data center What is thermal management Why does Intel Care Why Computer Science.
Motif Search and RNA Structure Prediction Lesson 9.
Onlinedeeneislam.blogspot.com1 Design and Analysis of Algorithms Slide # 1 Download From
CSC321: Neural Networks Lecture 1: What are neural networks? Geoffrey Hinton
Theory Group Faculty Members: -Prof. Tak-Wah Lam -Dr. Hing-Fung Ting -Dr. Siu-Ming Yiu -Dr. Giulio Chiribella -Dr. Bruno Oliveira -Dr. Hubert Chan -Dr.
Computational Challenges in BIG DATA 28/Apr/2012 China-Korea-Japan Workshop Takeaki Uno National Institute of Informatics & Graduated School for Advanced.
BNFO 615 Fall 2016 Usman Roshan NJIT. Outline Machine learning for bioinformatics – Basic machine learning algorithms – Applications to bioinformatics.
R-Storm: Resource Aware Scheduling in Storm
Impact of Interference on Multi-hop Wireless Network Performance
Bioinformatics Overview
Cohesive Subgraph Computation over Large Graphs
WABI: Workshop on Algorithms in Bioinformatics
Computing and Compressive Sensing in Wireless Sensor Networks
Genomic Data Clustering on FPGAs for Compression
Latent Space Model for Road Networks to Predict Time-Varying Traffic
1 Department of Engineering, 2 Department of Mathematics,
Lesson Objectives Aims You should be able to:
1 Department of Engineering, 2 Department of Mathematics,
1 Department of Engineering, 2 Department of Mathematics,
Introduction to Bioinformatic
What is Computer Science About? Part 2: Algorithms
Applying principles of computer science in a biological context
Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
Presentation transcript:

T HEORETICAL C OMPUTER S CIENCE Real World Problems Abstract Models Modeling Solutions Math Tools Inspire More Problems

C AREER D IRECTIONS Study Algorithms College ResearchInstitute Industry

Network Algorithm Team Hubert Chan Postgraduates: Li Ning 宁立 Fei Chen 陈飞 Mingfei Li 李明飞 Xiaowei Wu 吴晓伟

Natural Algorithm: to Achieve Consensus Observation: An individual’s opinion will be influenced by its friends/neighbors. In some cases, people will achieve a consensus finally, even when their neighborhoods keep changing. Researcher: This kind of natural behavior is modeled by dynamic systems. By our results, it is very fast for people to achieve consensus even under dynamic networks. “Fast convergence for consensus in dynamic networks”, Hubert Chan, Li Ning, ICALP

Spanners: “Building the Roads” Government: We need roads to connect cities, and we want save the cost. Traveler: Travelling along the roads should save time. Researcher: This is a spanner problem. Use our methods, then you don’t need many roads, and travelling distance along the roads is almost the same with travelling directly. “Sparse fault-tolerant spanners for doubling metrics with bounded hop-diameter or degree”, Hubert Chan, Mingfei Li, Li Ning, ICALP 2012.

Observation: People will spread information, e.g., news, via talking to their friends. Moreover, the news talked by more friends attract more attention. Information Spreading in Social Networks News … Not a big dealAll my friends are talking about this news Not a big deal News … Advertiser: Persuade one person, then he will spread the advertisement… Researcher: To spread information efficiently, which person should be picked initially? … “Maximizing influence in information networks under the non-progressive linear threshold model”, Hubert Chan, Li Ning, ongoing project.

Bargaining Rent sharing: The total cost to rent a flat is 100. It can be shared by two persons. I’ll pay 50. I’ll pay 40. I’ll pay 30. I’ll pay 40. I’ll pay 45. I’ll pay more Good. I’ll pay less I have to pay more… 60. Sociologist: Human behavior is so complicated. What are the stable deals? Researcher: This is studied as the problem called bargaining game. “Optimizing Social Welfare for Network Bargaining Games in the Face of Unstability Greed and Spite”, Hubert Chan, Fei Chen, Li Ning, ESA 2012.

ONLINE ALGORITHMS: JOB SCHEDULING & POWER MANAGEMENT Scheduling research team: T.W. Lam 林德华 H.F. Ting 田慶豐 H.L. Chan 陳昊樑 L.K. Lee 李立基 S.H. Chan R. Li

O NLINE PROBLEMS ARE CHALLENGING. Robot motion Bin Packing Paging Load balancing Deadline Flow Trading Broadcasting Scheduling Response time Without knowing the future, one often makes the wrong decision.

“What matters most to the computer designers at Google is not speed, but power, low power, because data centers can consume as much electricity as a city.“ Eric Schmidt, CEO Google NY Times, 2002

R EPRESENTATIVE PUBLICATIONS Sleep Management on Multiple Machines for Energy and Flow Time. ICALP 2011: Non-clairvoyant Speed Scaling for Weighted Flow Time. ESA 2010: Sleep with Guilt and Work Faster to Minimize Flow Plus Energy. ICALP 2009: Speed scaling with an arbitrary power function. SODA 2009: Scheduling for Speed Bounded Processors. ICALP 2008: Energy efficient online deadline scheduling. SODA 2007:

BIOINFORMATICS F. Chin T.W. Lam H.F. Ting S.M. Yiu

Bioinformatics involves the analysis of biological and genetic information, the results of which can then be applied to gene-based drug discovery and development to cure illnesses Our objective is to develop better software tools to aid bioinformatics research.

Next Generation Sequencing NGS is the new & cornerstone technology for today’s biological research and tomorrow’s medical care. Nowadays NGS equipment (Solexa, SOLiD, Illumina) can produce short fragments (read) of a DNA sequence (genome) efficiently and at a low cost. Our research work is to base on our algorithmic expertise to develop efficient and effective software tools for NGS data.

Research Publications and Funding Publications: Bioinformatics, J of Computational Biology, RECOMB, ISMB, ECCB GRF Grants Structural Alignment and prediction for non-coding RNAs with triple helix structure ( , HK$681,195) Algorithms for Inferring k-articulated Phylogenetic Network ( , HK$591,080) Combinatorial Phenotype Testing ( , HK$394,053) Finding Conserved Patterns In Biological Networks ( , HK$777,108) A New Motif Representation Based on Position Specific Patterns ( , HK$775,008) Compressed Indexes for Approximate String Matching, with Applications to Biological Sequences ( , HK$654,000) Design and Analysis of Algorithms for Constrained Structure Comparison ( , HK$612,816) Computationally Haplotyping Pedigree Data ( , HK$359,224) Algorithms for Uncovering Conserved Genes on Whole Genomes ( , HK$650,000) Finding Motifs for Sequences with Weak Binding Sites ( , HK$339,414)

Programming Languages Programming languages research team: B. C. d. S. Oliveira X. Bi H. Zhang Programming Languages

PROGRAMMING LANGUAGES ARE FUNDAMENTAL TO PROGRAMMER PRODUCTIVITY PROGRAMMING LANGUAGE RESEARCH AIMS AT: - ALLOWING FASTER DEVELOPMENT CYCLES - SUPPORTING LARGE-SCALE PROGRAMMING - PREVENTING MORE BUGS BY CREATING NEW PROGRAMMING LANGUAGES/ABSTRACTIONS

RESEARCH TOPICS - BETTER PROGRAMMING MODELS FOR MULTI-CORE COMPUTING, GPU PROGRAMMING - BETTER MODULARITY ABSTRACTIONS FOR LARGE-SCALE SOFTWARE - FUNCTIONAL PROGRAMMING (SCALA, HASKELL, OCAML, SCHEME …)