Prof TakWah Lam Dr HingFung Ting Dr SiuMing Yiu Dr Giulio Chiribella Dr Bruno Oliveira Dr Hubert Chan Dr Zhiyi Huang Bioinformatics Quantum Information Programming Languages Algorithms and Complexity ID: 673446
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Theory Group
Faculty Members:Prof. Tak-Wah LamDr. Hing-Fung TingDr. Siu-Ming YiuDr. Giulio ChiribellaDr. Bruno OliveiraDr. Hubert ChanDr. Zhiyi Huang
Bioinformatics
Quantum
Information
Programming Languages
Algorithms and ComplexitySlide2
Zhiyi Huang
Background:B.E., Tsinghua UniversityPh.D., University of PennsylvaniaResearch Interest:Theoretical Computer ScienceAlgorithmic game theory, online algorithm, privacy-preserving computationSlide3
Computer Science Meets Economics
The Internet created a new economy:Ad Auctions (Baidu, Google, Microsoft Bing)Auctions on Taobao and eBaySlide4
New Challenges
Larger scale: (billions of users and transactions per day) traditional auctions are not efficient.[Cai and Huang SODA 2013] [Bei and Huang SODA 2011]More data: How to protect user privacy? How to design auctions based on data?[Huang, Mansour, and Roughgarden EC 2015]
[Hsu, Huang, Roth, Roughgarden, and Wu STOC 2014][Huang and Kannan FOCS 2012]
Online decisions: E.g., how to adjust reserve prices over time without knowing the future?[Huang and Kim SODA15] [Devanur, Huang, Korula, Mirrokni, and Yan EC 2013]
[Chakraborty, Huang, and Khanna FOCS 2009]Slide5
Network/Graph Algorithms
Faculty Member:Hubert Chan (Ph.D., Carnegie Mellon University)Students:Zhichao Zhao (PhD)Ning Kang (PhD)Zhihao Tang (PhD)Shaofeng
Jiang (PhD)Chenzi Zhang (PhD)Wenbin Tang (MPhil)Slide6
Recent Work on Oblivious Matching
Motivated by applications like kidney exchange, greedy algorithms for querying an unknown graph to find a maximum size matching has been studied.Deterministic query order: performance ratio 0.5.Randomized query order: should be better?
query 1Is 1 & 5 an edge?
No
Slide7
How difficult is the problem?
First Attempt:0.5000025 [Aronson, Dyer, Frieze and Suen 1995]
It took 17 years to get a better analysis:0.5039[Poloczek
and Szegedy FOCS 2012]
Recent result:0.523 [Chan, Chen, Wu, and Zhao SODA 2014]Slide8
Bioinformatics
Faculty Members:Prof. Tak-Wah LamDr. Hing-Fung TingDr. Siu-Ming YiuApproach:Algorithms => Software => Technologies => Scientific findingsSlide9
What is Bioinformatics?
Bioinformatics is about the computational analysis of biological or genetic data (DNA, RNA).Applications: biological discovery, cancer diagnostics, gene-based drug discoveryObjectives: better algorithms & software in terms of speed, sensitivity, and accuracyOther concerns: big data, high performance computingSlide10
Example
Cancer (or genetic disease) diagnostic in a hospital.Data volume: a high-throughput DNA sequencer (e.g., HiSeq X Ten), in 24 hours, can serve 60 patients (WGS) and produce 6,000 Gb data (or 40G random DNA fragments of length 150).Analysis: map each fragment (150) to a reference genome (3G) and detect mutations.Slide11
Publications, Software, Industrial Partnership
Publications: Bioinformatics, Journal of Computational Biology, RECOMB, ISMB, ECCBSoftware: IDBA, Meta-IDBA, SOAP3-dpIndustrial partnership: HKU-BGI Bioinformatics Algorithm Research LaboratorySlide12
Research Grants
ITF Grants: (2013-15, HK$ 5.6 Million)A Genomic and Pharmaceutical Knowledge-based System for Clinical Diagnosis and Case RepositoryGRF Grants (2011-13, over HK$ 2.5 Million)Next-Generation Sequencing AlgorithmsUltrafast SNP-sensitive & Gap-sensitive alignment of short reads to human genome via better indexingStructural Alignment and prediction for non-coding RNAs with triple helix structure)Slide13
Quantum Information and Foundations
Faculty Members:Dr. Giulio Chiribella Winner of Hermann Weyl Prize 2010Students:Yuxiang Yang (PhD)Daniel Ebler (PhD)Slide14Slide15
Taking up the challenge
David Deutsch (Oxford), 1985:Quantum Turing Machine
Peter Shor (MIT), 1994:quantum factoring algorithmin polynomial time
Lov Grover (Bell Labs), 1996:quantum search algorithm
with quadratic speed-upSlide16Slide17
Research Topics
Quantum Information Theory: discover new machines and protocols that can process information more efficientlyWhat is the best way to copy data at the quantum scale? What is the minimum energy cost of a computation?How fast can a microscopic machine learn from its environment?Quantum Foundations:
rebuild the laws of physics from ideas about information and computation.In a sense, this can be considered as the modern version of Hilbert’s Sixth Problem: Mathematical Treatment of the Axioms of PhysicsSlide18
Programming Languages
Programming languages research team:
Dr Bruno C. d. S. Oliveira
Students:X.
BiH. Zhang
Programming LanguagesSlide19Slide20
PROGRAMMING LANGUAGES ARE FUNDAMENTAL TO PROGRAMMER PRODUCTIVITY
PROGRAMMING LANGUAGE RESEARCH AIMS AT:
- Allowing faster development cycles
- Supporting large-scale programming -
Preventing more bugsBY CREATING NEW PROGRAMMING LANGUAGES/ABSTRACTIONSSlide21
RESEARCH TOPICS
- BETTER PROGRAMMING MODELS FOR MULTI-CORE COMPUTING, GPU PROGRAMMING
- BETTER MODULARITY ABSTRACTIONS FOR LARGE-SCALE SOFTWARE
- FUNCTIONAL PROGRAMMING (SCALA, HASKELL, OCAML, SCHEME …)Slide22
Thank you!