IEEE ICBK 2017:

The 8^th IEEE International Conference on Big Knowledge

August 9 -10, 2017

Hefei, China

Big Knowledge deals with fragmented knowledge from heterogeneous, autonomous information sources for complex and evolving relationships, in addition to domain expertise. The IEEE International Conference on Big Knowledge (ICBK) provides a premier international forum for presentation of original research results in Big Knowledge opportunities and challenges, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of Big Knowledge, including algorithms, software, systems, and applications. ICBK draws researchers and application developers from a wide range of Big Knowledge related areas such as statistics, machine learning, pattern recognition, knowledge visualization, expert systems, high performance computing, World Wide Web, and big data analytics. By promoting novel, high quality research findings, and innovative solutions to challenging Big Knowledge problems, the conference seeks to continuously advance the state-of-the-art in Big Knowledge.

Accepted papers will be published in the conference proceedings by the IEEE Computer Society. Awards will be conferred at the conference on the authors of the best paper and the best student paper. A selected number of best papers will be invited for possible inclusion, in an expanded and revised form, in the Knowledge and Information Systems Journal.

Important Dates

• Paper submission: March 15, 2017  April 7, 2017

• Notification of acceptance/rejection: May 18, 2017

• Camera-Ready Papers: June 16, 2017

• Conference: August 9-10, 2017

All deadlines are 11:59PM, UTC-12; thus submissions are allowed as long as the deadline date is not past anywhere in the world.

Contact

For any issue with ICBK 2017, please email: bigke2016@gmail.com 

Important Dates

• Paper submission: March 15, 2017  April 7, 2017

• Notification of acceptance/rejection: May 18, 2017

• Camera-Ready Papers: June 16, 2017

• Registration Deadline: June 23, 2017

• Conference: August 9-10, 2017

All deadlines are 11:59PM, UTC-12; thus submissions are allowed as long as the deadline date is not past anywhere in the world. 

Accepted Papers

(BK237) Towards Question Improvement on Knowledge Sharing Platforms: A Stack Overflow Case Study by Rishabh Gupta and P. Krishna Reddy

(BK253) Keyphrase Extraction Using Sequential Pattern Mining and Entropy by Qingren Wang and Victor Sheng

(BK270) Multi-layered Big Knowledge Visualization Scheme for Comprehending Neoplasm Ontology Content by Ling Zheng, Christopher Ochs, James Geller, Hao Liu, Yehoshua Perl, and Sherri de Coronado

(BK233) Subpopulation-Wise Conditional Correlation Modeling and Analysis by Guozhu Dong and Sanjeev Bhatta

(BK265) Privacy-Preserving Pattern Mining on Online Density Estimates by Michael Geilke and Stefan Kramer

(BK263) Multi-Label Classification using Stacked Hierarchical Dirichlet Processes with Reduced Sampling Complexity by Sophie Burkhardt and Stefan Kramer

(BK239) Crime Hot Spot Forecasting: A Recurrent model with Spatial and Temporal Information by Yong Zhuang, Matthew Almeida, Melissa Morabito, and Wei Ding

(BK272) Self-learning and Embedding Based Entity Alignment by Saiping Guan, Xiaolong Jin, Yantao Jia, Yuanzhuo Wang, Huawei Shen, and Xueqi Cheng

(BK269) Learning Question Similarity with Recurrent Neural Networks by Borui Ye, Guangyu Feng, Anqi Cui, and Ming Li

(BK213) Analyzing Structure of Terrorist Networks by Using Graph Metrics by M Serkan CINAR, Burkay GENC, Hayri SEVER, and Vijay V RAGHAVAN

(BK225) Iteratively Multiple Projections Optimization for Product Quantization in Nearest Neighbor Search by Jin Li, Xuguang Lan, and Nanning Zheng

(BK214) A Novel Three-way Clustering Algorithm for Mixed-type Data by Hong Yu, Zhihua Chang, and Bing Zhou

(BK219) Granger Causality for Multivariate Time Series Classification by Dandan Yang, Huanhuan Chen, Yinlong Song, and Zhichen Gong

(BK220) Factored Proximity Models for Top-N Recommendations by Athanasios N. Nikolakopoulos, Vassilis Kalantzis, Efstratios Gallopoulos, and John Garofalakis

(BK223) A New Online Feature Selection Method Using Neighborhood Rough Set by Peng Zhou, Xuegang Hu, and Peipei Li

(BK221) Revisit Word Embeddings With Semantic Lexicons for Modeling Lexical Contrast by Jiawei Liu, Zhenyu Liu, and Huanhuan Chen

(BK207) TDN: Twice-least-square Double-parallel Neural Networks by Guoqiang Li and Keith C.C. Chan

(BK227) A Global Flight Networks Analysis Approach using Markov Clustering and PageRank by Kecheng Xu, Teng Long, Shaojie Qiao, Yating Zheng, and Nan Han

(BK224) Exploiting Nonlinear Relationships for Top-N Recommender Systems by Zhao Kang, Chong Peng, Ming Yang, and Qiang Cheng

(BK204) Visual Analytics as a tool to assist the preprocess by Glauber Cini and Joao F. Valiati

Author Final Paper Preparation and Submission Instructions

Please refer to the IEEE online submission system for the preparation and submission of the accepted final papers.

Submission Guidelines

Paper submissions should be no longer than 8 pages, in the IEEE 2-column format, including the bibliography and any possible appendices. Submissions longer than 8 pages will be rejected without review. All submissions will be triple-blind reviewed by the Program Committee on the basis of technical quality, relevance to Big Knowledge, originality, significance, and clarity. 

The following sections give further information for authors.  

1.      Triple blind submission guidelines

ICBK will adopt a triple blind submission and review policy for all submissions. Authors must hence not use identifying information in the text of the paper and bibliographies must be referenced to preserve anonymity. 

2.      What is triple blind reviewing?

The traditional blind paper submission hides the referee name from the authors. The triple-blind paper submission and review, in addition, also hides the authors’ names from the referees, and the referees’ names during review discussions. The names of authors and referees remain known only to the PC Chairs, and the author names are disclosed only after the ranking and acceptance of submissions are finalized. Although there is much debate on the merits and perceived benefits of triple blind reviewing, these are not discussed here. Our main purpose is to implement this policy in ICBK toward understanding the influence of the authors’ identity, whether conscious or unconscious, on the reviewer’s attitude toward a submission. Hence it is imperative that all authors of ICBK submissions work on concealing their identity in the content of the paper. It does not suffice to simply remove the authors’ names from the first page.

3.      How to prepare your submissions

• The authors shall omit their names from the submission. For formatting templates with author and institution information, simply replace all these information in the template by “Anonymous”.

• In the submission, the authors’ should refer to their own prior work like the prior work of any other author, and include all relevant citations. This can be done either by referring to their prior work in the third person or referencing      papers generically. For example, if your name is Jack and you have worked on classification, instead of saying “We extend our earlier classification model (Gordan 2010),” you may say “We extend Gordan’s (Gordan 2010) earlier classification model.”

• The authors shall exclude citations to their own work which is not fundamental to understanding the paper, including prior versions (e.g., technical reports, unpublished internal documents) of the submitted paper. They should reference only necessary work using point (2). Hence, do not write: “In our previous work [5]” as it reveals that citation 5 is written by the current authors.

• The authors shall remove mention of funding sources, personal acknowledgments, and other such auxiliary information that could be related to their identities. These can be reinstituted in the camera-ready copy once the paper is accepted for publication.

• The authors shall make statements on well-known or unique systems that identify an author, as vague in respect to identifying the authors as possible.

• The submitted files shall be named with care to ensure that authors’ anonymity is not compromised by the file name. E.g., do not name your submission “.pdf”, instead give it a name that is descriptive of the title of your paper, such as “NewApproachForClassfication.pdf” (or a shorter version of the same).

All manuscripts are submitted as full papers and are reviewed based on their scientific merit. The reviewing process is confidential. There is no separate abstract submission step. There are no separate industrial, application, short paper or poster tracks. Manuscripts must be submitted electronically in online submission system. We do not accept email submissions.

LaTeX and Word Templates

To help ensure correct formatting, please use the style files for U.S. Letter as template for your submission. These include LaTeX and Word.

Violations of any of the above paper specifications may result in rejection of your paper. Please note that the Latex template does not allow for keywords. If you are using the Latex template, do not include keywords in your paper.

ICBK2017Program.rar

• Call for Papers

• Call for Workshop Proposals

• Call for Workshop Papers

• Call for Tutorials

• Call for Doctoral Symposium
  

Honorary Chair:

Nanning Zheng

Xi'an Jiaotong University, China

Conference Chairs:

Jim Hendler	Rensselaer Polytechnic Institute, USA
Ruqian Lu	Academy of Mathematics and Systems Science,  Chinese Academy of Sciences

Program Committee Chairs:

Xindong Wu	Hefei University of Technology, China University of Louisiana at Lafayette, USA
Tamer Ozsu	University of Waterloo, Canada

Panel Chairs:

Guoyin Wang	Chongqing University of Posts and Telecommunications, China
Witold Pedrycz	University of Alberta, Canada

Finance Chair:

Lei Li

Hefei University of Technology, China

Local Arrangement Chair:

Qiping Zhang

Hefei University of Technology, China

Publication Chairs:

Huanhuan Chen

University of Science and Technology of China

Award Committee Chairs:

Jun Liu	Xi'an Jiaotong University, China
Michel Dumontier	Stanford University, USA

PhD Forum Chairs:

Zhi Jin	Peking University, China
Dimitris Karagiannis	University of Vienna, Austria

Sponsorship Chairs:

Dandan Song	Beijing Institute of Technology, China
Angel Rubio	Ceit-IK4 Research Alliance, Spain

Publicity Chairs:

Xiaolong Jin	Institute of Computing Technology,  Chinese Academy of Sciences
Francoise Soulie Fogelman	KXEN, France Tianjing University, China

Tutorial Chairs:

Songmao Zhang	Academy of Mathematics and Systems Science,  Chinese Academy of Sciences
Martin Wirsing	Ludwig-Maximilian's University of Munich, Germany

Workshops Chairs:

Enhong Chen	University of Science and Technology of China
Alfredo Cuzzocrea	University of Trieste, Italy

Program Committee:

Elena Baralis	Politecnico di Torino	Italy
Christian Bauckhage	Fraunhofer IAIS	Germany
Rohan Baxter	Australian Taxation Office	Australia
Michelangelo Ceci	University of Bari	Italy
Keith Chan	The Hong Kong Polytechnic University	Hong Kong
Huanhuan Chen	University of Science and Technology of China	China
Jinjun Chen	University of Technology, Sydney	Australia
Lei Chen	Hong Kong University of Science and Technology	Hong Kong
James Cheng	The Chinese University of Hong Kong	Hong Kong
Qiang Cheng	Southern Illinois University Carbondale	USA
Xueqi Cheng	Institute of Computing Technology, Chinese Academy of Sciences	China
Yiu-ming Cheung	Hong Kong Baptist University	Hong Kong
Peng Cui	Tsinghua University	China
Manoranjan Dash	Nanyang Technological University	Singapore
Sarah Jane Delany	Dublin Institute of Technology	Ireland
Ayhan Demiriz	Gebze Technical University	Turkey
Giuseppe Desolda	University of Bari "Aldo Moro"	Italy
Wei Ding	University of Massachusetts Boston	USA
Nemanja Djuric	Uber ATG	USA
Josep Domingo-Ferrer	Universitat Rovira i Virgili	Spain
Guozhu Dong	Wright State University	USA
Dejing Dou	University of Oregon	USA
Stefano Ferilli	University of Bari Aldo Moro	Italy
Yun Fu	Northeastern University	USA
Efstratios Gallopoulos	University of Patras	Greece
Aryya Gangopadhyay	University of Maryland Baltimore County	USA
Ming Gao	East China Normal University	China
Yang Gao	Beijing Institute of Technology	China
Aris Gkoulalas-Divanis	IBM Watson Health	USA
Le Gruenwald	University of Oklahoma	USA
Haibing Guan	Shanghai Jiaotong University	China
Jie Gui	Hefei Institute of Physical Science， Chinese Academy of Sciences	China
Francesco Gullo	UniCredit	Italy
Howard J. Hamilton	University of Regina	Canada
Haibo He	University of Rhode Island	USA
Jingrui He	Arizona State University	USA
Xiaofeng He	East China Normal University	China
Shen-Shyang Ho	Rowan University	USA
Jaakko Hollmén	Aalto University School of Science	Finland
Andreas Hotho	University of Wuerzburg	Germany
Bin Hu	Lanzhou University	China
Heng Huang	University of Texas at Arlington	USA
Nitin Indurkhya	AI Data-Miner LLC	USA
Alfred Inselberg	Tel-Aviv University	Israel
Szymon Jaroszewicz	Institute of Computer Science, Polish Academy of Sciences	Poland
He Jiang	Dalian University of Technology	China
Meng Jiang	University of Illinois at Urbana-Champaign	USA
Licheng Jiao	Xidian University	China
Hai Jin	Huazhong University of Science and Technology	China
Xiaolong Jin	Institute of Computing Technology, Chinese Academy of Sciences	China
Konstantinos Kalpakis	University of Maryland, Baltimore County	USA
Kamalakar Karlapalem	International Institute of Information Technology Hyderabad	India
Mehmet Kaya	Firat University	Turkey
Larry Kerschberg	George Mason University	USA
Latifur Khan	University of Texas at Dallas	USA
Stefan Kramer	Johannes Gutenberg University Mainz	Germany
Ercan Kuruoglu	ISTI-CNR	Italy
Wai Lam	The Chinese University of Hong Kong	Hong Kong
Jean-Charles Lamirel	TALARIS- LORIA	France
Xuguang Lan	Xi'an Jiaotong University	China
Anne Laurent	University Montpellier 2	France
Aleksandar Lazarevic	United Technology Research Center	USA
Guoliang Li	Tsinghua University	China
Jiuyong Li	University of South Australia	Australia
Ming Li	University of Waterloo	Canada
Peipei Li	Hefei University of Technology	China
Qing Li	City University of Hong Kong	Hong Kong
Tao Li	Florida International University	USA
Xiaoli Li	Institute for Infocomm Research	Singapore
Huan Liu	Arizona State University	USA
Huawen Liu	University of South Australia	Australia
Jun Liu	Xi'an Jiaotong University	China
Lei Liu	Huawei	USA
Mengchi Liu	Carleton University	Canada
Qi Liu	University of Science and Technology of China	China
Grigorios Loukides	King's College London	United Kingdom
Simone Ludwig	North Dakota State University	USA
Shuai Ma	Beihang University	China
Sanjay Madria	University of Missouri-Rolla	USA
Arun Maiya	Institute for Defense Analyses	USA
Donato Malerba	University of Bari	Italy
Bradley Malin	Vanderbilt University	USA
Giuseppe Manco	ICAR-CNR	Italy
Murali Mani	University of Michigan, Flint	USA
Brandeis Marshall	Spelman College	USA
Sameep Mehta	IBM	India
Nasrullah Memon	University of Southern Denmark	Denmark
Ernestina Menasalvas	Universidad Politecnica de Madrid	Spain
Prasenjit Mitra	Pennsylvania State University	USA
Anna Monreale	University of Pisa	Italy
Christine O'Keefe	Commonwealth Scientific and Industrial Research Organisation	Australia
Riccardo Ortale	ICAR-CNR	Italy
Dimitris Papadias	Hong Kong University of Science and Technology	China
Jian Pei	Simon Fraser University	Canada
Ruggero G. Pensa	University of Torino	Italy
Jean-Marc Petit	University de Lyon	France
Giuseppe Psaila	University of Bergamo	Italy
Ali Qamar	National University of Science and Technology Pakistan	Pakistan
Chedy Raissi	INRIA Nancy	France
Alessandra Raffaetà	University of Venice	Italy

Davood Rafiei	University of Alberta	Canada
Vijay Raghavan	University of Louisiana- Lafayette	USA
Ganesh Ramesh	SAP Ariba	USA
Jan Ramon	Katholieke Universiteit Leuven	Belgium
Sanjay Ranka	University of Florida	USA
Zbigniew Ras	University of North Carolina at Charlotte	USA
Jan Rauch	University of Economics, Prague	Czech Republic
Sourav S Bhowmick	Nanyang Technological University	Singapore
Reza Sadoddin	University of Alberta	Canada
Lorenza Saitta	University del Piemonte Orientale	Italy
Saeed Salem	North Dakota State University	USA
Yucel Saygin	Sabanci University	Turkey
Peter Scheuermann	Northwestern University	USA
Friedhelm Schwenker	University of Ulm	Germany
Jialie Shen	Singapore Management University	Singapore
Victor Sheng	University of Central Arkansas	USA
Zhongzhi Shi	Institute of Computing Technology, Chinese Academy of Sciences	China
Kyuseok Shim	Seoul National University	Republic of Korea
Dan Simovici	University of Massachusetts at Boston	USA
Andrzej Skowron	University of Warsaw and Systems Research Institute, Polish Academy of Siences	Poland
V.S. Subrahmanian	University of Maryland, College Park	USA
Chih-Hua Tai	National Taipei University	Taiwan
Ah-Hwee Tan	Nanyang Technological University	Singapore
Maguelonne Teisseire	TETIS - Cemagref	France
Masahiro Terabe	Mitsubishi Research Institute, Inc.	Japan
Takao Terano	Tokyo Institute of Technology	Japan
Hang Hang Tong	Arizona State University	USA
Panayiotis Tsaparas	Microsoft Research	USA
Shusaku Tsumoto	Shimane University	Japan
K.P. Unnikrishnan	Global Data Insight & Analytics (GDIA), Ford Motor Company	USA
Vassilios Verykios	Hellenic Open University	Greece
Chang-Dong Wang	Sun Yat-sen University	China
Guoyin Wang	Chongqing University of Posts and Telecommunications	China
Hao Wang	Chinese Academy of Sciences	China
Jason T. L. Wang	New Jersey Institute of Technology	USA
Jianyong Wang	Tsinghua University	China
Lipo Wang	Nanyang Technological University	Singapore
Ji-Rong Wen	Renmin University of China	China
Adalbert Wilhelm	Jacobs University Bremen	Germany
Stefan Wrobel	Fraunhofer IAIS and University of Bonn	Germany
Gongqing Wu	Hefei University of Technology	China
Yanghua Xiao	Fudan University	China
Xing Xie	Microsoft Research	China
Hui Xiong	Rutgers University	USA
Guandong Xu	University of Technology, Sydney	Australia
Takahira Yamaguchi	Keio University	Japan
Yiyu Yao	University of Regina	Canada
Jin Soung Yoo	Indiana University - Purdue University Fort Wayne	USA
Linlin You	Singapore University of Technology and Design	Singapore
Jeffrey Yu	The Chinese University of Hong Kong	China
Demetris Zeinalipour	University of Cyprus	Cyprus
Aidong Zhang	University at Buffalo, The State University of New York	USA
Jing Zhang	Nanjing University of Science and Technology	China
Min-Ling Zhang	Southeast University	China
Peng Zhang	University of Technology, Sydney	Australia
Songmao Zhang	Academy of Mathematics and Systems Science, Chinese Academy of Sciences	China
Weixiong Zhang	Washington University in St. Louis	USA
Yanchun Zhang	Victoria University	Australia
Yu Zheng	Microsoft Research Asia	China
Ning Zhong	Maebashi Institute of Technology	Japan
Aoying Zhou	East China Normal University	China
Zhi-Hua Zhou	Nanjing University	China
Feida Zhu	Singapore Management University	Singapore
Xingquan Zhu	Florida Atlantic University	USA

Registration

All attendees/participants should register to the conference through the online registration system. We have discounts for IEEE members and students. There is also an early-bird rate. The registration fees in US Dollar are as follows.

1. Advance Registration (early-bird deadline is June 23, 2017)

Type	Rate
IEEE Member Registration (conference & workshop)	$600
Non IEEE Member Registration (conference & workshop)	$720
Student IEEE Member Registration (conference & workshop)	$330
Student Non IEEE Member Registration (conference & workshop)	$600
Life/Retired members Fee (conference & workshop)	$330

2. Late/On-site Registration

Type	Rate
IEEE Member Registration (conference & workshop)	$720
Non IEEE Member Registration (conference & workshop)	$864
Student IEEE Member Registration (conference & workshop)	$396
Student Non IEEE Member Registration (conference & workshop)	$720
Life/Retired members Fee (conference & workshop)	$396

Note:

(1) The registration allows you to participate both the conference and affiliated workshops, daily coffee breaks, lunch, reception, and banquet. Also it includes the conference or workshop proceedings on a USB drive.

(2) The Advance registration deadline is June 23, 2017. Late/On-site registration is also available with a higher fee.

(3) For each accepted paper, at least one author must register at the full rate (IEEE Member Registration $600\ Non IEEE Member Registration $720 before early-bird deadline), even if all authors are students.

(4) Authors of each accepted paper can publish up to 2 extra pages at a charge of  $125/page.

(5) If you have multiple accepted papers, each paper must have a separate full registration. 

(6) IEEE Member Registration: IEEE Members (including professional members and student members) must provide their Membership Number for verification during registration.

Visa Application 

    If you need an invitation letter for visa application to China for the IEEE ICBK 2017 conference, please contact: bigke2016@gmail.com with the following information:

• Name

• Address

• Email

• Citizenship

• Passport Number

    If you are an author of IEEE ICBK 2017 paper (main conference paper, or workshop paper), please also include the paper id, title.

Attendance

ICBK is a premier forum for presenting and discussing current research in big knowledge science and engineering. Therefore, at least one author of each accepted paper should complete the conference registration and present the paper at the conference, in order for the paper to be included in the proceedings and conference program.

Hotel

The conference hotel will be Shangri-La Hefei (http://www.shangri-la.com/hefei/shangrila/about/)

Shangri-la Hotel Hefei Reservation Information:

Deluxe King Room (45㎡): CNY430 net

Deluxe Twin Room (45㎡): CNY430 net

The above rates include: service charge, government tax and Breakfast. The price is limited to the duration of the meeting. 

Reservation Tel: 0551-6297 9766

                           (09:00am-18:00pm GMT+8) 

Reservation E-mail: Reservations.SLHF@shangri-la.com

                                (09:00am-18:00pm GMT+8)

Online Booking: Individual reservations under the group rate can now be booked on the website with the following direct hyperlink. The hotel and Group Code will be pre-selected if this direct hyperlink is used:

http://www.shangri-la.com/reservations/booking/en/index.aspx?hid=SLHF&group_code=IEE090817&check_in=20170808&check_out=20170812

Alternatively, guests can make their bookings directly on Shangri-La website using the Group Code:
1) Go to the Shangri-La website.
2) Select the appropriate hotel and enter all the necessary stay requirements like check-in date, check-out date, number of rooms, adults and children.
3) Under the "Special Rate" area, select "Group Code" and enter the Group Code.
4) Click the Check Availability button to continue.
5) If all the search criteria are correct and rooms are still available for the group, the group rate will be returned in the availability search result. Simply follow the on-screen instructions to complete the online booking.

Tourist information

Should you have some time off to visit Huanshan, which is near to Hefei and very famous in China, during your stay, please find below some additional information.

The description about Huangshan in Wikipedia: https://en.wikipedia.org/wiki/Huangshan

The description about Huangshan in UNESCO World Heritage Centre: http://whc.unesco.org/en/list/547/

Keynote 1: Tracking in Dynamic Networks

Keynote Speaker: Jian Pei, Simon Fraser University.

Abstract:

In many application scenarios ranging from social networks to IoT, we need to process and analyze a huge amount of data, connected, evolving, linkages being more interesting than entities individually.  Modeling such temporal data in nature as graphs provides a conceptually convenient way to support novel and meaningful intelligent applications.  At the same time, it also posts grant challenges in many aspects, such as algorithm design and computing system development.  In this talk, I will present some interesting and novel application scenarios where graphs play a central role, as well as the corresponding algorithms.  Moreover, I will briefly introduce our on-going effort to build a distributed cloud-based graph computing engine that can query huge graphs and networks in seconds.

Short Bio:

Jian Pei is a Canada Research Chair (Tier 1) in Big Data Science and a Professor in the School of Computing Science at Simon Fraser University. His expertise is on developing effective and efficient data analysis techniques for novel data intensive applications. He is one of the most cited authors in data mining, database systems, and information retrieval. Since 2000, he, with H-index 73, has published one textbook, two monographs and over 200 research papers in refereed journals and conferences, which have been cited by more than 67,000 in literature. His research has generated remarkable impact substantially beyond academia. He is the recipient of several prestigious awards, such as the IEEE ICDM Research Contributions Award and the ACM SIGKDD Service Award. He is an ACM Fellow and an IEEE Fellow.

Keynote 2: Deep Learning in Bioinformatics

Keynote Speaker: Ming Li, University of Waterloo.

Abstract:

I will discuss several applications of deep learning in bioinformatics, and focus on our recent work on de novo peptide sequencing by deep learning. De novo peptide sequencing from tandem mass spectrometry data is the key technology in proteomics for the characterization of proteins, especially for antibodies. During the past 20 years, many traditional computer science algorithms were developed for this problem. These algorithms include dynamic programming, linear programming, HMM, graph algorithms, and statistical methods. Deep learning significantly improves these traditional approaches.

This is joint work with H.N. Tran, X. Zhang, L. Xin and P. Shan, to appear in PNAS.

Short Bio:

Dr. Ming Li is a Canada Research Chair in Bioinformatics and a University Professor at the University of Waterloo. He is a fellow of the Royal Society of Canada, ACM, and IEEE. He is a recipient of E.W.R. Steacie Fellowship Award in 1996, the 2001 Killam Fellowship, and the 2010 Killam Prize. Together with Paul Vitanyi they have co-authored the book "An Introduction to Kolmogorov Complexity and Its Applications".