1. 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. Zhiyi Huang Bioinformatics Quantum Information Programming Languages Algorithms and Complexity

2. Zhiyi Huang Background: -B.E., Tsinghua University -Ph.D., University of Pennsylvania Research Interest: -Theoretical Computer Science -Algorithmic game theory, online algorithm, privacy-preserving computation

3. Computer Science Meets Economics The Internet created a new economy: -Ad Auctions (Baidu, Google, Microsoft Bing) -Auctions on Taobao and eBay

4. 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]

5. 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)

6. 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 query 2 6 & 2?Yes query 31 & 4? No query 44 & 5? Yes query 5 1 & 3?No 1 2 3 4 6 5 Matching: (6, 2) and (4, 5)

7. 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]

8. Bioinformatics Faculty Members: -Prof. Tak-Wah Lam -Dr. Hing-Fung Ting -Dr. Siu-Ming Yiu Approach: -Algorithms => Software => Technologies => Scientific findings

9. What is Bioinformatics? Bioinformatics is about the computational analysis of biological or genetic data (DNA, RNA). -Applications: biological discovery, cancer diagnostics, gene-based drug discovery -Objectives: better algorithms & software in terms of speed, sensitivity, and accuracy -Other concerns: big data, high performance computing

10. 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.

11. Publications, Software, Industrial Partnership Publications: -Bioinformatics, Journal of Computational Biology, RECOMB, ISMB, ECCB Software: -IDBA, Meta-IDBA, SOAP3-dp Industrial partnership: -HKU-BGI Bioinformatics Algorithm Research Laboratory

12. Research Grants ITF Grants: (2013-15, HK$ 5.6 Million) -A Genomic and Pharmaceutical Knowledge-based System for Clinical Diagnosis and Case Repository GRF Grants (2011-13, over HK$ 2.5 Million) -Next-Generation Sequencing Algorithms -Ultrafast SNP-sensitive & Gap-sensitive alignment of short reads to human genome via better indexing -Structural Alignment and prediction for non-coding RNAs with triple helix structure)

13. Quantum Information and Foundations Faculty Members: -Dr. Giulio Chiribella Winner of Hermann Weyl Prize 2010 Students: -Yuxiang Yang (PhD) -Daniel Ebler (PhD)

15. Taking up the challenge David Deutsch (Oxford), 1985: Quantum Turing Machine Peter Shor (MIT), 1994: quantum factoring algorithm in polynomial time Lov Grover (Bell Labs), 1996: quantum search algorithm with quadratic speed-up

17. Research Topics Quantum Information Theory: discover new machines and protocols that can process information more efficiently -What 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 Physics

18. Programming Languages Programming languages research team: Dr Bruno C. d. S. Oliveira Students: X. Bi H. Zhang Programming Languages

20. 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

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

22. Thank you!