Research Fellow Australian National University, Canberra, Australia

Size: px
Start display at page:

Download "Research Fellow Australian National University, Canberra, Australia"

Transcription

1 1011 S 2nd Street Lafayette, IN USA tao.wang.cs@gmail.com twang mobile: SKILLS SUMMARY Management and Leadership: Excellent problem analysis and solving Excellent time management Effective organization skills e.g., leading a group of people Experience with conducting individual consultations as well as facilitating workshops Computer Skills: Familiar with Java, C/C++, and Matlab Good at Microsoft Office Word/PowerPoint/Excel Experience with Unix/Linux, Mac OS X, and various flavors of Windows Languages: Fluent in English Chinese (mother tongue) EMPLOYMENT HISTORY Research Fellow Australian National University, Canberra, Australia System Analyst and Technical Consultant DELL Computer (China) Co., Ltd., Shanghai, China Software Engineer Telecommunication Technological Research Institute, Shanghai, China EDUCATION Ph.D. in Computing Science, University of Alberta, Canada 2007 Advisors: Dale Schuurmans and Michael Bowling Committee: Richard S. Sutton, Paul R. Messinger, and Doina Precup Thesis: New Representations and Approximations for Sequential Decision Making Finalist for the Department of Computing Science 2007 Ph.D. Thesis Award M.E. in Automatic Control, Northwestern Polytechnical University, China 1998 Thesis: Text-Independent Speaker Recognition Based on Continuous HMMs B.E. in Automatic Control, Northwestern Polytechnical University, China 1996 With University Honors ADDITIONAL PROFESSIONAL DEVELOPMENT Academic Leadership and Management (Australian National University) 2008 Microsoft Certified System Engineer (MCSE) 2000 Sun Certified Java Programmer (SCJP) 1999

2 OUTREACH Program Committee Member The Twenty-Third Conference on Artificial Intelligence (AAAI) 2008 International Conference on Machine Learning and Cybernetics (ICMLC) 2007 Reviewer Neural Information Processing Systems (NIPS) 2007 International Conference on Machine Learning (ICML) 2005 and 2007 Journal of Adaptive Behavior 2004 IEEE Transactions on Systems, Man and Cybernetics 2002 and 2003 Councilor Graduate Students Association of the University of Alberta Volunteer Team Leader International Conference on Intelligent Systems for Molecular Biology (ISMB) 2002 Volunteer Neural Information Processing Systems (NIPS) 2006 Grace Hopper Celebration of Women in Computing (GHC) 2006 IEEE International Conference on Robotics and Automation (ICRA) 2001 International Community Outreach Programs at University of Alberta Ambassador of Univ. of Alberta for the World Track and Field Championships 2001 Media Attention CBC Radio, Canada 2007 Express News, University of Alberta, Canada 2007 CH Television News, Canada 2006 Victoria Times Colonist, Canada 2006 A-Channel Victoria, Canada 2006 AWARDS AND HONORS Best Student Paper Award 2007 At the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning [?]. Scholarships and Awards SIGAR/AAAI Doctoral Consortium Scholarship 2006 Canberra Machine Learning Summer School Scholarship 2006 ICML 2005 Student Scholarship 2005 J Gordin Kaplan Graduate Student Award 2004 Sea Eagle Comprehensive Award 1997 Excellent Graduate Student Fellowship Excellent Undergraduate Student Fellowship Honors Third Prize, Shanghai Science & Technology Promotion 1999 Second Prize, Experimental Skill Competition in Physics 1994 October,

3 PUBLICATIONS Journal Articles [1] Adam Milstein and Tao Wang. Dynamic motion models in Monte Carlo localization. Integrated Computer-Aided Engineering, 14(3): , [2] Tao Wang and Naiping Xu. Speaker recognition and its applications. Journal of Microprocessors, (4):50 53, November Top Peer Refereed Conferences [3] Tao Wang, Daniel Lizotte, Michael Bowling, and Dale Schuurmans. Stable dynamic programming. In Proceedings of Advances in Neural Information Processing Systems 20 (NIPS), To appear (8 pages), [Acceptance Rate: 10% (poster spotlight)]. [4] Daniel Lizotte, Tao Wang, Michael Bowling, and Dale Schuurmans. Automatic gait optimization with Gaussian process regression. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), pages , [Acceptance Rate: 35%]. [5] Tao Wang, Pascal Poupart, Michael Bowling, and Dale Schuurmans. Compact, convex upper bound iteration for approximate POMDP planning. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages , [Acceptance Rate: 22% (oral presentation)]. [6] Adam Milstein and Tao Wang. Localization with dynamic motion models: Determining motion model parameters dynamically in Monte Carlo localization. In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics (ICINCO), pages , [Acceptance Rate: 10% (full paper and oral presentation)]. [7] Tao Wang, Daniel Lizotte, Michael Bowling, and Dale Schuurmans. Bayesian sparse sampling for on-line reward optimization. In Proceedings of the Twenty-second International Conference on Machine Learning (ICML), pages , [Acceptance Rate: 27% (oral presentation)]. Book Chapters [8] C. Ronald Kube, Chris A. C. Parker, Tao Wang, and Hong Zhang. Biologically Inspired Collective Robotics, chapter 15. Recent Developments in Biologically Inspired Computing. Idea Group, ISBN: Other Refereed Publications [9] Tao Wang, Michael Bowling, and Dale Schuurmans. Dual representations for dynamic programming and reinforcement learning. In Proceedings of the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning, pages 44 51, April [Acceptance Rate: 61.5% (oral presentation)]. [10] Tao Wang and Hong Zhang. Collective sorting with multiple robots. In Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO), pages , October,

4 [11] Tao Wang and Hong Zhang. Multi-robot collective sorting with local sensing. In Proceedings of the IEEE Intelligent Automation Conference (IAC), [12] Tao Wang, Juhua Shi, and Mario A. Nascimento. Experimental results towards content-based sub-image retrieval. In Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC), pages , Refereed Abstracts and Short Papers [13] Tao Wang. Action selection in Bayesian reinforcement learning. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI), pages , [Acceptance Rate: 37% (oral presentation)]. [14] Tao Wang, Michael Bowling, and Dale Schuurmans. Reinforcement learning with dual representations. NIPS Workshop on Towards a New Reinforcement Learning, [15] Daniel Lizotte, Tao Wang, Michael Bowling, and Dale Schuurmans. Gaussian process regression for optimization. NIPS Workshop on Value of Information in Inference, Learning and Decision-Making, [16] Linli Xu, Li Cheng, Tao Wang, and Dale Schuurmans. Convex hidden Markov models. NIPS (Neural Information Processing Systems) Workshop on Advances in Structured Learning for Text and Speech Processing, [17] Tao Wang and Naiping Xu. Speaker recognition based on continuous Gaussian mixture HMMs. In Proceedings of the Second Conference of Graduate Students Academic Reports, pages , June [18] Tao Wang. A multi-channels data acquisition and dynamic display system. In Proceedings of the First Conference of Graduate Students Academic Reports, pages , November Presentations and Demonstrations [1] Dual dynamic programming and reinforcement learning. Workshop on Modelling and Mining of Networked Information Spaces, MITACS (Mathematics of Information Technology and Complex Systems), December Banff, Canada. [2] Action selection for reinforcement learning and approximate POMDP planning. Game Theory and Decision Theory Seminar at University of British Columbia, December Vancouver, Canada. [3] Quadratic approximation for POMDP planning. Logic Lab Seminar at Simon Fraser University, November Vancouver, Canada. [4] Bayesian reinforcement learning. Women in Machine Learning Workshop, October San Diego, USA. [5] Action selection in Bayesian reinforcement learning. AAAI/SIGART Doctoral Consortium, July Boston, USA. [6] Compact, convex upper bound iteration for approximate POMDP planning. Artificial Intelligence Seminar at University of Alberta, June Edmonton, Canada. October,

5 [7] Bayesian action selection. The Sixteenth Annual Canadian Conference on Intelligent Systems, June Victoria, Canada. [8] Sony AIBO ERS-7 (robotic dog) technology demonstration. The Sixteenth Annual Canadian Conference on Intelligent Systems, June Victoria, Canada. [9] Bayesian sparse sampling. Banff Informatics Summit, Best Student Poster Award, September Banff, Canada. [10] Bayesian sparse sampling for on-line reward optimization. Artificial Intelligence Seminar at University of Alberta, July Edmonton, Canada. OTHER RESEARCH EXPERIENCE Stochastic Optimization, Canberra, Australia April June 2007 Visiting Researcher. Investigated stochastic optimization algorithms with researchers in the Statistical Machine Learning program at National Information and Communications Technology Australia. Swarm Intelligence Based Robotics, Edmonton, Canada Graduate Researcher. Designed strategies for controlling robots to achieve a representative task collective sorting motivated by brood sorting in ants. The challenge is to design robotic behaviors that only depend on local sensing information in order to cluster objects of different types into piles. Speaker Recognition System Project, Xi an, China Project Leader. Designed and developed a speaker recognition system for police to analyze wiretaps. I proposed a new feature extraction method and built a speaker recognition system based on continuous Hidden Markov Models. The project was sponsored by the National Security Bureau of China and Aptronix Research Institute of Hainan Co., Ltd. User Interface Design for Heart Disease Inspection, Xi an, China 1995 Undergraduate Researcher. Designed and developed the user interface for a heart disease inspection system. TEACHING Lecturer Signal Processing in Fault-Tolerant Control Winter 1996 Computer Control and Computer Simulation Fall 1995 Lab Instructor User Interfaces and Software Design Fall 2001; Winter, Fall 2002 Java Programming Fall 2000; Winter, Fall 2003 Programming with Data Structures Winter 2001 PERSONAL INFORMATION Citizenship: Canadian Gender: Female October,

Xinyu Tang. Education. Research Interests. Honors and Awards. Professional Experience

Xinyu Tang. Education. Research Interests. Honors and Awards. Professional Experience Xinyu Tang Parasol Laboratory Department of Computer Science Texas A&M University, TAMU 3112 College Station, TX 77843-3112 phone:(979)847-8835 fax: (979)458-0425 email: xinyut@tamu.edu url: http://parasol.tamu.edu/people/xinyut

More information

Hongyan Ma. University of California, Los Angeles

Hongyan Ma. University of California, Los Angeles SUMMARY, 300 Young Drive North, Mailbox 951520, hym@ucla.eduhttp://polaris.gseis.ucla.edu/hma/ Objective is a faculty position in library and information science devoted to research and teaching Research

More information

Massachusetts Institute of Technology Tel: Massachusetts Avenue Room 32-D558 MA 02139

Massachusetts Institute of Technology Tel: Massachusetts Avenue  Room 32-D558 MA 02139 Hariharan Narayanan Massachusetts Institute of Technology Tel: 773.428.3115 LIDS har@mit.edu 77 Massachusetts Avenue http://www.mit.edu/~har Room 32-D558 MA 02139 EMPLOYMENT Massachusetts Institute of

More information

Speech Emotion Recognition Using Support Vector Machine

Speech Emotion Recognition Using Support Vector Machine Speech Emotion Recognition Using Support Vector Machine Yixiong Pan, Peipei Shen and Liping Shen Department of Computer Technology Shanghai JiaoTong University, Shanghai, China panyixiong@sjtu.edu.cn,

More information

Learning Methods for Fuzzy Systems

Learning Methods for Fuzzy Systems Learning Methods for Fuzzy Systems Rudolf Kruse and Andreas Nürnberger Department of Computer Science, University of Magdeburg Universitätsplatz, D-396 Magdeburg, Germany Phone : +49.39.67.876, Fax : +49.39.67.8

More information

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur Module 12 Machine Learning 12.1 Instructional Objective The students should understand the concept of learning systems Students should learn about different aspects of a learning system Students should

More information

Top US Tech Talent for the Top China Tech Company

Top US Tech Talent for the Top China Tech Company THE FALL 2017 US RECRUITING TOUR Top US Tech Talent for the Top China Tech Company INTERVIEWS IN 7 CITIES Tour Schedule CITY Boston, MA New York, NY Pittsburgh, PA Urbana-Champaign, IL Ann Arbor, MI Los

More information

IAT 888: Metacreation Machines endowed with creative behavior. Philippe Pasquier Office 565 (floor 14)

IAT 888: Metacreation Machines endowed with creative behavior. Philippe Pasquier Office 565 (floor 14) IAT 888: Metacreation Machines endowed with creative behavior Philippe Pasquier Office 565 (floor 14) pasquier@sfu.ca Outline of today's lecture A little bit about me A little bit about you What will that

More information

CSL465/603 - Machine Learning

CSL465/603 - Machine Learning CSL465/603 - Machine Learning Fall 2016 Narayanan C Krishnan ckn@iitrpr.ac.in Introduction CSL465/603 - Machine Learning 1 Administrative Trivia Course Structure 3-0-2 Lecture Timings Monday 9.55-10.45am

More information

Welcome to. ECML/PKDD 2004 Community meeting

Welcome to. ECML/PKDD 2004 Community meeting Welcome to ECML/PKDD 2004 Community meeting A brief report from the program chairs Jean-Francois Boulicaut, INSA-Lyon, France Floriana Esposito, University of Bari, Italy Fosca Giannotti, ISTI-CNR, Pisa,

More information

Master s Programme in Computer, Communication and Information Sciences, Study guide , ELEC Majors

Master s Programme in Computer, Communication and Information Sciences, Study guide , ELEC Majors Master s Programme in Computer, Communication and Information Sciences, Study guide 2015-2016, ELEC Majors Sisällysluettelo PS=pääsivu, AS=alasivu PS: 1 Acoustics and Audio Technology... 4 Objectives...

More information

Course Outline. Course Grading. Where to go for help. Academic Integrity. EE-589 Introduction to Neural Networks NN 1 EE

Course Outline. Course Grading. Where to go for help. Academic Integrity. EE-589 Introduction to Neural Networks NN 1 EE EE-589 Introduction to Neural Assistant Prof. Dr. Turgay IBRIKCI Room # 305 (322) 338 6868 / 139 Wensdays 9:00-12:00 Course Outline The course is divided in two parts: theory and practice. 1. Theory covers

More information

FEIRONG YUAN, PH.D. Updated: April 15, 2016

FEIRONG YUAN, PH.D. Updated: April 15, 2016 FEIRONG YUAN, PH.D. Assistant Professor The University of Texas at Arlington College of Business Department of Management Box 19467 701 S. West Street, Suite 226 Arlington, TX 76019-0467 Phone: 817-272-3863

More information

Reinforcement Learning by Comparing Immediate Reward

Reinforcement Learning by Comparing Immediate Reward Reinforcement Learning by Comparing Immediate Reward Punit Pandey DeepshikhaPandey Dr. Shishir Kumar Abstract This paper introduces an approach to Reinforcement Learning Algorithm by comparing their immediate

More information

The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X

The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, 2013 10.12753/2066-026X-13-154 DATA MINING SOLUTIONS FOR DETERMINING STUDENT'S PROFILE Adela BÂRA,

More information

Wenguang Sun CAREER Award. National Science Foundation

Wenguang Sun CAREER Award. National Science Foundation Wenguang Sun Address: 401W Bridge Hall Department of Data Sciences and Operations Marshall School of Business University of Southern California Los Angeles, CA 90089-0809 Phone: (213) 740-0093 Fax: (213)

More information

Soft Computing based Learning for Cognitive Radio

Soft Computing based Learning for Cognitive Radio Int. J. on Recent Trends in Engineering and Technology, Vol. 10, No. 1, Jan 2014 Soft Computing based Learning for Cognitive Radio Ms.Mithra Venkatesan 1, Dr.A.V.Kulkarni 2 1 Research Scholar, JSPM s RSCOE,Pune,India

More information

Evolutive Neural Net Fuzzy Filtering: Basic Description

Evolutive Neural Net Fuzzy Filtering: Basic Description Journal of Intelligent Learning Systems and Applications, 2010, 2: 12-18 doi:10.4236/jilsa.2010.21002 Published Online February 2010 (http://www.scirp.org/journal/jilsa) Evolutive Neural Net Fuzzy Filtering:

More information

ISFA2008U_120 A SCHEDULING REINFORCEMENT LEARNING ALGORITHM

ISFA2008U_120 A SCHEDULING REINFORCEMENT LEARNING ALGORITHM Proceedings of 28 ISFA 28 International Symposium on Flexible Automation Atlanta, GA, USA June 23-26, 28 ISFA28U_12 A SCHEDULING REINFORCEMENT LEARNING ALGORITHM Amit Gil, Helman Stern, Yael Edan, and

More information

Chen Zhou. June Room 492, Darla Moore School of Business Office: (803) University of South Carolina 1014 Greene Street

Chen Zhou. June Room 492, Darla Moore School of Business Office: (803) University of South Carolina 1014 Greene Street Chen Zhou June 2017 Room 492, Darla Moore School of Business Office: (803) 777-4914 University of South Carolina 1014 Greene Street Email: chen.zhou@moore.sc.edu Columbia, SC, 29201 USA ACADEMIC APPOINTMENT

More information

A Reinforcement Learning Variant for Control Scheduling

A Reinforcement Learning Variant for Control Scheduling A Reinforcement Learning Variant for Control Scheduling Aloke Guha Honeywell Sensor and System Development Center 3660 Technology Drive Minneapolis MN 55417 Abstract We present an algorithm based on reinforcement

More information

ACS HONG KONG INTERNATIONAL CHEMICAL SCIENCES CHAPTER 2014 ANNUAL REPORT

ACS HONG KONG INTERNATIONAL CHEMICAL SCIENCES CHAPTER 2014 ANNUAL REPORT ACS HONG KONG INTERNATIONAL CHEMICAL SCIENCES CHAPTER 2014 ANNUAL REPORT Author: Date ACS Hong Kong International Chemical Sciences Chapter 2014 Annual Report DESCRIPTION OF CHAPTER: The chapter is composed

More information

MABEL ABRAHAM. 710 Uris Hall Broadway mabelabraham.com New York, New York Updated January 2017 EMPLOYMENT

MABEL ABRAHAM. 710 Uris Hall Broadway mabelabraham.com New York, New York Updated January 2017 EMPLOYMENT MABEL ABRAHAM Columbia Business School mabel.abraham@columbia.edu 710 Uris Hall 212-854-7788 3022 Broadway mabelabraham.com New York, New York 10027 Updated January 2017 EMPLOYMENT 2015 Columbia University,

More information

CURRICULUM VITAE OF MARIE-LOUISE VIERØ

CURRICULUM VITAE OF MARIE-LOUISE VIERØ October 23, 2017 NAME WORK ADDRESS Marie-Louise Vierø Department of Economics Dunning Hall Room 306 Queen s University 94 University Avenue Kingston, Ontario K7L 3N6 CANADA E-ADDRESSES Email: viero@econ.queensu.ca

More information

Albert (Yan) Wang. Flow-induced Trading Pressure and Corporate Investment (with Xiaoxia Lou), Forthcoming at

Albert (Yan) Wang. Flow-induced Trading Pressure and Corporate Investment (with Xiaoxia Lou), Forthcoming at Albert (Yan) Wang 315 Lowder Hall 405 W. Magnolia Ave Auburn, AL 36849 Office: 334-844-5324 Cell: 205-737-2677 albertwang@auburn.edu Employment 2017/8 present: Synovus Fellow and Associate Professor, Department

More information

DOCTOR OF PHILOSOPHY HANDBOOK

DOCTOR OF PHILOSOPHY HANDBOOK University of Virginia Department of Systems and Information Engineering DOCTOR OF PHILOSOPHY HANDBOOK 1. Program Description 2. Degree Requirements 3. Advisory Committee 4. Plan of Study 5. Comprehensive

More information

Regret-based Reward Elicitation for Markov Decision Processes

Regret-based Reward Elicitation for Markov Decision Processes 444 REGAN & BOUTILIER UAI 2009 Regret-based Reward Elicitation for Markov Decision Processes Kevin Regan Department of Computer Science University of Toronto Toronto, ON, CANADA kmregan@cs.toronto.edu

More information

Machine Learning from Garden Path Sentences: The Application of Computational Linguistics

Machine Learning from Garden Path Sentences: The Application of Computational Linguistics Machine Learning from Garden Path Sentences: The Application of Computational Linguistics http://dx.doi.org/10.3991/ijet.v9i6.4109 J.L. Du 1, P.F. Yu 1 and M.L. Li 2 1 Guangdong University of Foreign Studies,

More information

Laboratorio di Intelligenza Artificiale e Robotica

Laboratorio di Intelligenza Artificiale e Robotica Laboratorio di Intelligenza Artificiale e Robotica A.A. 2008-2009 Outline 2 Machine Learning Unsupervised Learning Supervised Learning Reinforcement Learning Genetic Algorithms Genetics-Based Machine Learning

More information

Georgetown University at TREC 2017 Dynamic Domain Track

Georgetown University at TREC 2017 Dynamic Domain Track Georgetown University at TREC 2017 Dynamic Domain Track Zhiwen Tang Georgetown University zt79@georgetown.edu Grace Hui Yang Georgetown University huiyang@cs.georgetown.edu Abstract TREC Dynamic Domain

More information

Knowledge-Based - Systems

Knowledge-Based - Systems Knowledge-Based - Systems ; Rajendra Arvind Akerkar Chairman, Technomathematics Research Foundation and Senior Researcher, Western Norway Research institute Priti Srinivas Sajja Sardar Patel University

More information

Word Segmentation of Off-line Handwritten Documents

Word Segmentation of Off-line Handwritten Documents Word Segmentation of Off-line Handwritten Documents Chen Huang and Sargur N. Srihari {chuang5, srihari}@cedar.buffalo.edu Center of Excellence for Document Analysis and Recognition (CEDAR), Department

More information

Prof. Dr. Hussein I. Anis

Prof. Dr. Hussein I. Anis Curriculum Vitae Prof. Dr. Hussein I. Anis 1 Personal Data Full Name : Hussein Ibrahim Anis Date of Birth : November 20, 1945 Nationality : Egyptian Present Occupation : Professor, Electrical Power & Machines

More information

Australian Journal of Basic and Applied Sciences

Australian Journal of Basic and Applied Sciences AENSI Journals Australian Journal of Basic and Applied Sciences ISSN:1991-8178 Journal home page: www.ajbasweb.com Feature Selection Technique Using Principal Component Analysis For Improving Fuzzy C-Mean

More information

2017 Florence, Italty Conference Abstract

2017 Florence, Italty Conference Abstract 2017 Florence, Italty Conference Abstract Florence, Italy October 23-25, 2017 Venue: NILHOTEL ADD: via Eugenio Barsanti 27 a/b - 50127 Florence, Italy PHONE: (+39) 055 795540 FAX: (+39) 055 79554801 EMAIL:

More information

TD(λ) and Q-Learning Based Ludo Players

TD(λ) and Q-Learning Based Ludo Players TD(λ) and Q-Learning Based Ludo Players Majed Alhajry, Faisal Alvi, Member, IEEE and Moataz Ahmed Abstract Reinforcement learning is a popular machine learning technique whose inherent self-learning ability

More information

InTraServ. Dissemination Plan INFORMATION SOCIETY TECHNOLOGIES (IST) PROGRAMME. Intelligent Training Service for Management Training in SMEs

InTraServ. Dissemination Plan INFORMATION SOCIETY TECHNOLOGIES (IST) PROGRAMME. Intelligent Training Service for Management Training in SMEs INFORMATION SOCIETY TECHNOLOGIES (IST) PROGRAMME InTraServ Intelligent Training Service for Management Training in SMEs Deliverable DL 9 Dissemination Plan Prepared for the European Commission under Contract

More information

Time series prediction

Time series prediction Chapter 13 Time series prediction Amaury Lendasse, Timo Honkela, Federico Pouzols, Antti Sorjamaa, Yoan Miche, Qi Yu, Eric Severin, Mark van Heeswijk, Erkki Oja, Francesco Corona, Elia Liitiäinen, Zhanxing

More information

EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10. Instructor: Kang G. Shin, 4605 CSE, ;

EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10. Instructor: Kang G. Shin, 4605 CSE, ; EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10 Instructor: Kang G. Shin, 4605 CSE, 763-0391; kgshin@umich.edu Number of credit hours: 4 Class meeting time and room: Regular classes: MW 10:30am noon

More information

QuickStroke: An Incremental On-line Chinese Handwriting Recognition System

QuickStroke: An Incremental On-line Chinese Handwriting Recognition System QuickStroke: An Incremental On-line Chinese Handwriting Recognition System Nada P. Matić John C. Platt Λ Tony Wang y Synaptics, Inc. 2381 Bering Drive San Jose, CA 95131, USA Abstract This paper presents

More information

Human Emotion Recognition From Speech

Human Emotion Recognition From Speech RESEARCH ARTICLE OPEN ACCESS Human Emotion Recognition From Speech Miss. Aparna P. Wanare*, Prof. Shankar N. Dandare *(Department of Electronics & Telecommunication Engineering, Sant Gadge Baba Amravati

More information

Axiom 2013 Team Description Paper

Axiom 2013 Team Description Paper Axiom 2013 Team Description Paper Mohammad Ghazanfari, S Omid Shirkhorshidi, Farbod Samsamipour, Hossein Rahmatizadeh Zagheli, Mohammad Mahdavi, Payam Mohajeri, S Abbas Alamolhoda Robotics Scientific Association

More information

JAMALIN R. HARP. Adjunct, Texas Christian University, Department of History January 2016 May 2016 HIST 10603: United States Before 1877

JAMALIN R. HARP. Adjunct, Texas Christian University, Department of History January 2016 May 2016 HIST 10603: United States Before 1877 JAMALIN R. HARP CONTACT Department of History University of Texas Rio Grande Valley jamalin.harp@utrgv.edu EDUCATION PhD, Texas Christian University, May 2017 History Advisor: Dr. Kenneth Stevens Dissertation:

More information

Department of Economics Phone: (617) Boston University Fax: (617) Bay State Road

Department of Economics Phone: (617) Boston University Fax: (617) Bay State Road Barton L. Lipman Department of Economics Phone: (617) 353 2995 Boston University Fax: (617) 353 4449 270 Bay State Road Email: blipman@bu.edu Boston, MA 02215 web page: people.bu.edu/blipman Education

More information

SAM - Sensors, Actuators and Microcontrollers in Mobile Robots

SAM - Sensors, Actuators and Microcontrollers in Mobile Robots Coordinating unit: Teaching unit: Academic year: Degree: ECTS credits: 2017 230 - ETSETB - Barcelona School of Telecommunications Engineering 710 - EEL - Department of Electronic Engineering BACHELOR'S

More information

Computerized Adaptive Psychological Testing A Personalisation Perspective

Computerized Adaptive Psychological Testing A Personalisation Perspective Psychology and the internet: An European Perspective Computerized Adaptive Psychological Testing A Personalisation Perspective Mykola Pechenizkiy mpechen@cc.jyu.fi Introduction Mixed Model of IRT and ES

More information

Predicting Future User Actions by Observing Unmodified Applications

Predicting Future User Actions by Observing Unmodified Applications From: AAAI-00 Proceedings. Copyright 2000, AAAI (www.aaai.org). All rights reserved. Predicting Future User Actions by Observing Unmodified Applications Peter Gorniak and David Poole Department of Computer

More information

ZHANG Xiaojun, XIONG Xiaoliang School of Finance and Business English, Wuhan Yangtze Business University, P.R.China,

ZHANG Xiaojun, XIONG Xiaoliang School of Finance and Business English, Wuhan Yangtze Business University, P.R.China, Studies on the Characteristic Training Mode of Foreign Business Talents of Private University Taking International Economy and Trade Major of Wuhan Yangtze Business University as an Example ZHANG Xiaojun,

More information

Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for

Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for Email Marilyn A. Walker Jeanne C. Fromer Shrikanth Narayanan walker@research.att.com jeannie@ai.mit.edu shri@research.att.com

More information

Learning Methods in Multilingual Speech Recognition

Learning Methods in Multilingual Speech Recognition Learning Methods in Multilingual Speech Recognition Hui Lin Department of Electrical Engineering University of Washington Seattle, WA 98125 linhui@u.washington.edu Li Deng, Jasha Droppo, Dong Yu, and Alex

More information

Ph.D. Computer Engineering and Information Science. Case Western Reserve University. Cleveland, OH, 1986

Ph.D. Computer Engineering and Information Science. Case Western Reserve University. Cleveland, OH, 1986 Victor Matos Address: 4984 Farnhurst Rd. Lyndhurst OH 44124 Phone: (216) 382-2264 (Home) Email: matos@cis.csuohio.edu Web-Page: http://cis.csuohio.edu/~matos Education Ph.D. Computer Engineering and Information

More information

Mining Association Rules in Student s Assessment Data

Mining Association Rules in Student s Assessment Data www.ijcsi.org 211 Mining Association Rules in Student s Assessment Data Dr. Varun Kumar 1, Anupama Chadha 2 1 Department of Computer Science and Engineering, MVN University Palwal, Haryana, India 2 Anupama

More information

Rule Learning with Negation: Issues Regarding Effectiveness

Rule Learning with Negation: Issues Regarding Effectiveness Rule Learning with Negation: Issues Regarding Effectiveness Stephanie Chua, Frans Coenen, and Grant Malcolm University of Liverpool Department of Computer Science, Ashton Building, Ashton Street, L69 3BX

More information

Semi-Supervised GMM and DNN Acoustic Model Training with Multi-system Combination and Confidence Re-calibration

Semi-Supervised GMM and DNN Acoustic Model Training with Multi-system Combination and Confidence Re-calibration INTERSPEECH 2013 Semi-Supervised GMM and DNN Acoustic Model Training with Multi-system Combination and Confidence Re-calibration Yan Huang, Dong Yu, Yifan Gong, and Chaojun Liu Microsoft Corporation, One

More information

NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches

NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches Yu-Chun Wang Chun-Kai Wu Richard Tzong-Han Tsai Department of Computer Science

More information

A New Perspective on Combining GMM and DNN Frameworks for Speaker Adaptation

A New Perspective on Combining GMM and DNN Frameworks for Speaker Adaptation A New Perspective on Combining GMM and DNN Frameworks for Speaker Adaptation SLSP-2016 October 11-12 Natalia Tomashenko 1,2,3 natalia.tomashenko@univ-lemans.fr Yuri Khokhlov 3 khokhlov@speechpro.com Yannick

More information

A survey of multi-view machine learning

A survey of multi-view machine learning Noname manuscript No. (will be inserted by the editor) A survey of multi-view machine learning Shiliang Sun Received: date / Accepted: date Abstract Multi-view learning or learning with multiple distinct

More information

An Estimating Method for IT Project Expected Duration Oriented to GERT

An Estimating Method for IT Project Expected Duration Oriented to GERT An Estimating Method for IT Project Expected Duration Oriented to GERT Li Yu and Meiyun Zuo School of Information, Renmin University of China, Beijing 100872, P.R. China buaayuli@mc.e(iuxn zuomeiyun@263.nct

More information

On the Combined Behavior of Autonomous Resource Management Agents

On the Combined Behavior of Autonomous Resource Management Agents On the Combined Behavior of Autonomous Resource Management Agents Siri Fagernes 1 and Alva L. Couch 2 1 Faculty of Engineering Oslo University College Oslo, Norway siri.fagernes@iu.hio.no 2 Computer Science

More information

Stephanie Ann Siler. PERSONAL INFORMATION Senior Research Scientist; Department of Psychology, Carnegie Mellon University

Stephanie Ann Siler. PERSONAL INFORMATION Senior Research Scientist; Department of Psychology, Carnegie Mellon University Stephanie Ann Siler PERSONAL INFORMATION Senior Research Scientist; Department of Psychology, Carnegie Mellon University siler@andrew.cmu.edu Home Address Office Address 26 Cedricton Street 354 G Baker

More information

Dr. Tang has been an active member of CAPA since She was Co-Chair of Education Committee and Executive committee member ( ).

Dr. Tang has been an active member of CAPA since She was Co-Chair of Education Committee and Executive committee member ( ). 2015 CAPA Candidates Profiles For President-elect (alphabetic order): Dr. Ping Tang Dr. Ping Tang is a Professor at Department of Pathology and Laboratory Medicine, University of Rochester Medical Center,

More information

CNS 18 21th Communications and Networking Simulation Symposium

CNS 18 21th Communications and Networking Simulation Symposium CNS 18 21th Communications and Networking Simulation Symposium Spring Simulation Multi-conference 2018 Organizing Committee AAA General Chair: Dr. Abdolreza Abhari, aabhari@ryerson.ca Ryerson University,

More information

ReinForest: Multi-Domain Dialogue Management Using Hierarchical Policies and Knowledge Ontology

ReinForest: Multi-Domain Dialogue Management Using Hierarchical Policies and Knowledge Ontology ReinForest: Multi-Domain Dialogue Management Using Hierarchical Policies and Knowledge Ontology Tiancheng Zhao CMU-LTI-16-006 Language Technologies Institute School of Computer Science Carnegie Mellon

More information

Rule Learning With Negation: Issues Regarding Effectiveness

Rule Learning With Negation: Issues Regarding Effectiveness Rule Learning With Negation: Issues Regarding Effectiveness S. Chua, F. Coenen, G. Malcolm University of Liverpool Department of Computer Science, Ashton Building, Ashton Street, L69 3BX Liverpool, United

More information

Laboratorio di Intelligenza Artificiale e Robotica

Laboratorio di Intelligenza Artificiale e Robotica Laboratorio di Intelligenza Artificiale e Robotica A.A. 2008-2009 Outline 2 Machine Learning Unsupervised Learning Supervised Learning Reinforcement Learning Genetic Algorithms Genetics-Based Machine Learning

More information

Guide to the Program in Comparative Culture Records, University of California, Irvine AS.014

Guide to the Program in Comparative Culture Records, University of California, Irvine AS.014 http://oac.cdlib.org/findaid/ark:/13030/kt2f59q8v9 No online items University of California, Irvine AS.014 Finding aid prepared by Processed by Mary Ellen Goddard and Michelle Light; machine-readable finding

More information

FF+FPG: Guiding a Policy-Gradient Planner

FF+FPG: Guiding a Policy-Gradient Planner FF+FPG: Guiding a Policy-Gradient Planner Olivier Buffet LAAS-CNRS University of Toulouse Toulouse, France firstname.lastname@laas.fr Douglas Aberdeen National ICT australia & The Australian National University

More information

A study of speaker adaptation for DNN-based speech synthesis

A study of speaker adaptation for DNN-based speech synthesis A study of speaker adaptation for DNN-based speech synthesis Zhizheng Wu, Pawel Swietojanski, Christophe Veaux, Steve Renals, Simon King The Centre for Speech Technology Research (CSTR) University of Edinburgh,

More information

Reducing Features to Improve Bug Prediction

Reducing Features to Improve Bug Prediction Reducing Features to Improve Bug Prediction Shivkumar Shivaji, E. James Whitehead, Jr., Ram Akella University of California Santa Cruz {shiv,ejw,ram}@soe.ucsc.edu Sunghun Kim Hong Kong University of Science

More information

Learning to Schedule Straight-Line Code

Learning to Schedule Straight-Line Code Learning to Schedule Straight-Line Code Eliot Moss, Paul Utgoff, John Cavazos Doina Precup, Darko Stefanović Dept. of Comp. Sci., Univ. of Mass. Amherst, MA 01003 Carla Brodley, David Scheeff Sch. of Elec.

More information

MAE Flight Simulation for Aircraft Safety

MAE Flight Simulation for Aircraft Safety MAE 482 - Flight Simulation for Aircraft Safety SYLLABUS Fall Semester 2013 Instructor: Dr. Mario Perhinschi 521 Engineering Sciences Building 304-293-3301 Mario.Perhinschi@mail.wvu.edu Course main topics:

More information

ACS HONG KONG_INTERNATIONAL CHEMICAL SCIENCES CHAPTER 2011 ANNUAL REPORT

ACS HONG KONG_INTERNATIONAL CHEMICAL SCIENCES CHAPTER 2011 ANNUAL REPORT ACS HONG KONG_INTERNATIONAL CHEMICAL SCIENCES CHAPTER 2011 ANNUAL REPORT David Lee Phillips 2/8/2012 ACS Hong Kong_International Chemical Sciences Chapter 2011 Annual Report Description of Chapters Structures,

More information

Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model

Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model Unsupervised Learning of Word Semantic Embedding using the Deep Structured Semantic Model Xinying Song, Xiaodong He, Jianfeng Gao, Li Deng Microsoft Research, One Microsoft Way, Redmond, WA 98052, U.S.A.

More information

Introduction to Simulation

Introduction to Simulation Introduction to Simulation Spring 2010 Dr. Louis Luangkesorn University of Pittsburgh January 19, 2010 Dr. Louis Luangkesorn ( University of Pittsburgh ) Introduction to Simulation January 19, 2010 1 /

More information

Shintaro Yamaguchi. Educational Background. Current Status at McMaster. Professional Organizations. Employment History

Shintaro Yamaguchi. Educational Background. Current Status at McMaster. Professional Organizations. Employment History Shintaro Yamaguchi Department of Economics McMaster University 1280 Main Street West Hamilton, ON L8S 4M4 Phone: (905) 525-9140 x23672 Office: 440 Kenneth Taylor Hall Email: yamtaro@mcmaster.ca Homepage:

More information

Chapter 10 APPLYING TOPIC MODELING TO FORENSIC DATA. 1. Introduction. Alta de Waal, Jacobus Venter and Etienne Barnard

Chapter 10 APPLYING TOPIC MODELING TO FORENSIC DATA. 1. Introduction. Alta de Waal, Jacobus Venter and Etienne Barnard Chapter 10 APPLYING TOPIC MODELING TO FORENSIC DATA Alta de Waal, Jacobus Venter and Etienne Barnard Abstract Most actionable evidence is identified during the analysis phase of digital forensic investigations.

More information

Prairie View A&M University Houston, TX P.O. Box 519; MS 2220; Hilliard Hall (281)

Prairie View A&M University Houston, TX P.O. Box 519; MS 2220; Hilliard Hall (281) DEJUN LIU Dept. of Languages and Communications 11222 Stoney Meadow Dr. Prairie View A&M University Houston, TX 77095 P.O. Box 519; MS 2220; Hilliard Hall (281) 256-0164 Prairie View, TX 77446 deliu@pvamu.edu

More information

TEACHING AND EXAMINATION REGULATIONS (TER) (see Article 7.13 of the Higher Education and Research Act) MASTER S PROGRAMME EMBEDDED SYSTEMS

TEACHING AND EXAMINATION REGULATIONS (TER) (see Article 7.13 of the Higher Education and Research Act) MASTER S PROGRAMME EMBEDDED SYSTEMS TEACHING AND EXAMINATION REGULATIONS (TER) (see Article 7.13 of the Higher Education and Research Act) 2015-2016 MASTER S PROGRAMME EMBEDDED SYSTEMS UNIVERSITY OF TWENTE 1 SECTION 1 GENERAL... 3 ARTICLE

More information

REVIEW OF CONNECTED SPEECH

REVIEW OF CONNECTED SPEECH Language Learning & Technology http://llt.msu.edu/vol8num1/review2/ January 2004, Volume 8, Number 1 pp. 24-28 REVIEW OF CONNECTED SPEECH Title Connected Speech (North American English), 2000 Platform

More information

Culture, Tourism and the Centre for Education Statistics: Research Papers

Culture, Tourism and the Centre for Education Statistics: Research Papers Catalogue no. 81-595-M Culture, Tourism and the Centre for Education Statistics: Research Papers Salaries and SalaryScalesof Full-time Staff at Canadian Universities, 2009/2010: Final Report 2011 How to

More information

Language Acquisition Fall 2010/Winter Lexical Categories. Afra Alishahi, Heiner Drenhaus

Language Acquisition Fall 2010/Winter Lexical Categories. Afra Alishahi, Heiner Drenhaus Language Acquisition Fall 2010/Winter 2011 Lexical Categories Afra Alishahi, Heiner Drenhaus Computational Linguistics and Phonetics Saarland University Children s Sensitivity to Lexical Categories Look,

More information

arxiv: v1 [cs.lg] 15 Jun 2015

arxiv: v1 [cs.lg] 15 Jun 2015 Dual Memory Architectures for Fast Deep Learning of Stream Data via an Online-Incremental-Transfer Strategy arxiv:1506.04477v1 [cs.lg] 15 Jun 2015 Sang-Woo Lee Min-Oh Heo School of Computer Science and

More information

SHARIF F. KHAN. June 16, 2015

SHARIF F. KHAN. June 16, 2015 SHARIF F. KHAN June 16, 2015 University Address: 75 University Avenue West Wilfrid Department of Economics Waterloo, ON N2L 3C5, Canada E-mail: khans@econ.queensu.ca Mailing Address: 455 Rideau River St

More information

Humboldt-Universität zu Berlin

Humboldt-Universität zu Berlin Humboldt-Universität zu Berlin Department of Informatics Computer Science Education / Computer Science and Society Seminar Educational Data Mining Organisation Place: RUD 25, 3.101 Date: Wednesdays, 15:15

More information

A Case-Based Approach To Imitation Learning in Robotic Agents

A Case-Based Approach To Imitation Learning in Robotic Agents A Case-Based Approach To Imitation Learning in Robotic Agents Tesca Fitzgerald, Ashok Goel School of Interactive Computing Georgia Institute of Technology, Atlanta, GA 30332, USA {tesca.fitzgerald,goel}@cc.gatech.edu

More information

A SURVEY OF FUZZY COGNITIVE MAP LEARNING METHODS

A SURVEY OF FUZZY COGNITIVE MAP LEARNING METHODS A SURVEY OF FUZZY COGNITIVE MAP LEARNING METHODS Wociech Stach, Lukasz Kurgan, and Witold Pedrycz Department of Electrical and Computer Engineering University of Alberta Edmonton, Alberta T6G 2V4, Canada

More information

AQUA: An Ontology-Driven Question Answering System

AQUA: An Ontology-Driven Question Answering System AQUA: An Ontology-Driven Question Answering System Maria Vargas-Vera, Enrico Motta and John Domingue Knowledge Media Institute (KMI) The Open University, Walton Hall, Milton Keynes, MK7 6AA, United Kingdom.

More information

ERIN A. HASHIMOTO-MARTELL EDUCATION

ERIN A. HASHIMOTO-MARTELL EDUCATION ERIN A. HASHIMOTO-MARTELL EDUCATION Ph.D., Curriculum and Instruction, Boston College, 2014 Dissertation title: Using Rasch Models to Develop and Validate An Environmental Thinking Learning Progression

More information

Experiments with SMS Translation and Stochastic Gradient Descent in Spanish Text Author Profiling

Experiments with SMS Translation and Stochastic Gradient Descent in Spanish Text Author Profiling Experiments with SMS Translation and Stochastic Gradient Descent in Spanish Text Author Profiling Notebook for PAN at CLEF 2013 Andrés Alfonso Caurcel Díaz 1 and José María Gómez Hidalgo 2 1 Universidad

More information

Jon N. Kerr, PhD, CPA August 2017

Jon N. Kerr, PhD, CPA August 2017 JON NATHAN KERR, PhD, CPA ASSISTANT PROFESSOR THE OHIO STATE UNIVERSITY FISHER COLLEGE OF BUSINESS 2100 NEIL AVENUE 400 FISHER HALL COLUMBUS, OH 43210 Email: kerr.360@osu.edu Office: Fax: EDUCATION Columbia

More information

Web-based Learning Systems From HTML To MOODLE A Case Study

Web-based Learning Systems From HTML To MOODLE A Case Study Web-based Learning Systems From HTML To MOODLE A Case Study Mahmoud M. El-Khoul 1 and Samir A. El-Seoud 2 1 Faculty of Science, Helwan University, EGYPT. 2 Princess Sumaya University for Technology (PSUT),

More information

Dinesh K. Sharma, Ph.D. Department of Management School of Business and Economics Fayetteville State University

Dinesh K. Sharma, Ph.D. Department of Management School of Business and Economics Fayetteville State University Department of Management School of Business and Economics Fayetteville State University EDUCATION Doctor of Philosophy, Devi Ahilya University, Indore, India (2013) Area of Specialization: Management:

More information

CURRICULUM VITAE PERSONAL DETAILS. Evans Anderson Kirimi Miriti Year of Birth: English (Excellent), Kiswahili (Excellent), French (Fair).

CURRICULUM VITAE PERSONAL DETAILS. Evans Anderson Kirimi Miriti Year of Birth: English (Excellent), Kiswahili (Excellent), French (Fair). CURRICULUM VITAE PERSONAL DETAILS Name: Evans Anderson Kirimi Miriti Year of Birth: 1975 Gender: Marital Status: Nationality: Religion: Languages: Male Married Kenyan Christian English (Excellent), Kiswahili

More information

Curriculum Vitae of Chiang-Ju Chien

Curriculum Vitae of Chiang-Ju Chien Contact Information Curriculum Vitae of Chiang-Ju Chien Affiliation : Department of Electronic Engineering, Huafan University, Taiwan Address : Department of Electronic Engineering, Huafan University,

More information

Seminar - Organic Computing

Seminar - Organic Computing Seminar - Organic Computing Self-Organisation of OC-Systems Markus Franke 25.01.2006 Typeset by FoilTEX Timetable 1. Overview 2. Characteristics of SO-Systems 3. Concern with Nature 4. Design-Concepts

More information

Discriminative Learning of Beam-Search Heuristics for Planning

Discriminative Learning of Beam-Search Heuristics for Planning Discriminative Learning of Beam-Search Heuristics for Planning Yuehua Xu School of EECS Oregon State University Corvallis,OR 97331 xuyu@eecs.oregonstate.edu Alan Fern School of EECS Oregon State University

More information

Case Acquisition Strategies for Case-Based Reasoning in Real-Time Strategy Games

Case Acquisition Strategies for Case-Based Reasoning in Real-Time Strategy Games Proceedings of the Twenty-Fifth International Florida Artificial Intelligence Research Society Conference Case Acquisition Strategies for Case-Based Reasoning in Real-Time Strategy Games Santiago Ontañón

More information

Curriculum Vitae FARES FRAIJ, Ph.D. Lecturer

Curriculum Vitae FARES FRAIJ, Ph.D. Lecturer Current Address Curriculum Vitae FARES FRAIJ, Ph.D. Lecturer Department of Computer Science University of Texas at Austin 2317 Speedway, Stop D9500 Austin, Texas 78712-1757 Education 2005 Doctor of Philosophy,

More information

ScienceDirect. A Framework for Clustering Cardiac Patient s Records Using Unsupervised Learning Techniques

ScienceDirect. A Framework for Clustering Cardiac Patient s Records Using Unsupervised Learning Techniques Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 98 (2016 ) 368 373 The 6th International Conference on Current and Future Trends of Information and Communication Technologies

More information

Computational Data Analysis Techniques In Economics And Finance

Computational Data Analysis Techniques In Economics And Finance Computational Data Analysis Techniques In Economics And Finance If searched for a ebook Computational Data Analysis Techniques in Economics and Finance in pdf format, in that case you come on to correct

More information