Recent Talks
Edward Chang

Keynotes, Invited Talks and Seminars

  1. DeepQ: Advancing Healthcare through AI and VR (keynote), IEEE International Conference on Multimedia Information Retrieval and Processing, Miami, April 2018.
  2. DeepQ: Advancing Healthcare through AI and VR (keynote), XXI Symposium Neuroradiologicum, Taipei, March 2018.
  3. Precision Medicine, TED Talk, December 2017.
  4. Representation Learning on Big and Small Data (invited talk), Math Department, PKU, Beijing, November 2017.
  5. Representation Learning on Big and Small Data (keynote), First Annual Taiwan AI Meeting, Taipei, November 2017.
  6. DeepQ: Advancing Healthcare through AI and VR (keynote), ACM International Conference on Multimedia, Mountain View, October 2017.
  7. Developing AlphaGo to Power Healthcare and Virtual Reality (invited talk), Computer and Information Science, Tsinghua University, Beijing, March, 2017.
  8. Developing AlphaGo to Power Healthcare and Virtual Reality (keynote), The ACM/IEEE 49th International Conference on Microarchitectures, October, 2016.
  9. Developing AlphaGo to Power Healthcare and Virtual Reality (invited talk), Chao Tung University, Asia University, HTC Thinker Forum, June/July, 2016.
  10. Developing AlphaGo to Power Healthcare and Virtual Reality (keynote), The IEEE International Big Multimedia Data Conference, Taipei, April, 2016.
  11. Big Data Analytics for Healthcare (invited lecture), BigDat 2016, Bilbao Spain, February 2016.
  12. Not-So-Big Clinical Data Predictive Analytics (keynote), The 24th International Wireless Optical and Communication Conference, Taipei, October 2015.
  13. Predictive Analytics in Healthcare (panelist), Stanford Data Science Initiative Annual Retreat, Stanford University, October 2015.
  14. Big Data Analytics, Architectures, Algorithms, and Applications (keynote), The IEEE Big Data Congress, Taipei, May 2015.
  15. Signal Fusion and Big Data Analytics on Massive Sensor Data Sets (invited lecture), HKUST, April 2015.
  16. Signal Fusion and Big Data Analytics on Massive Sensor Data Sets (keynote), The IEEE 10th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Singapore, April 2015.
  17. Big Data Analytics, Architectures, Algorithms, and Applications (invited lecture), BigDat 2015, Tarragona Spain, January 2015. (Edward Chang; Lecture #1, Edward Chang; Lecture #2, Simon Wu Lecture #3.)
  18. Data Mining in Big Data Era: Opportunities, Challenges and Practice (panelist), PAKDD, May 2014.
  19. Big Data and Bio Informatics (keynote), The 4th International Symposium on Dynamical Biomarkers for Translational Medicine, Taipei, April 2014.
  20. Making Smartphones Smarter (panelist), ACM MobiSys, Taipei, June 2013.
  21. Mobile Information Management and Retrieval, The Next Frontier (keynote), ASIST 75th Annual Meeting, Baltimore, October 2012.
  22. Mobile Information Management and Retrieval (keynote), International Conference on eMedia, Xining, August 2012.
  23. Large-Scale Multimedia Information Management and Retrieval (keynote), CBMI Annual Workshop, Annery, France, June 2012.
  24. Big Data Analysis, Research Issues (invited talk), China National Academy of Science, May 2012.
  25. From Machine Learning to Human Innovation (distinushed talk), School of Engineering, Lanzhou University, Lanzhou, China, May 2012.
  26. From Machine Learning to Human Innovation (keynote), City U. of HK Media Center Grand Opening, Hong Kong, March 2012.
  27. Mobile Information Management and Retrieval (invited talk), CS Seminar, Taiwan University, January 2012.
  28. Mobile Information Management and Retrieval (keynote), Google Faculty Summit, November 2011.
  29. Mobile Information Management and Retrieval, ICADL (keynote), Tsinghua University, October 2011.
  30. Mobile Information Retrieval, ACM SIGIR (keynote, industry track), 2011.
  31. Search and Social Integration, The 11th International Conference on Web Information System Engineering (keynote), slides, Hong Kong, December 2010.
  32. Developing Next Generation Cyber-Infrastructure for Mobile IT Revolution (keynote), Google Faculty Summit, Shanghai, November 2010.
  33. Processing Web-Scale Multimedia Data (tutorial), ACM International Conference on Multimedia, Florence, October 2010.
  34. Scalable Algorithms and Systems for Mining Massive Datasets, Computer and Information Science, ETH, Zurich, October 2010.
  35. Confucius and "its" Intelligent Disciples (keynote), the 27th National Database Conference, Beijing, October 2010.
  36. Confucius and "its" Intelligent Disciples (invited talk), NCCU, Taipei, Septmber 2010.
  37. A Walk from Mathematical Principles to Innovations in Art and Literature (invited talk), NCCU, Taipei, September 2010.
  38. AdHeat --- A New Influence-based Social Ads Model and its Tera-Scale Algorithms (invited tutorial) MMDS, Stanford University, June 2010.
  39. AdHeat --- A New Influence-based Social Ads Model and its Tera-Scale Algorithms (keynote) UWAP, Hawaii, June 2010.
  40. Large-scale Data Mining and its Applications to Information Retrieval (invited talk), Information and Computer Science Seminar, University of California, Irvine, February 2010.
  41. Confucius and "its" Intelligent Disciples (keynote), the 18th ACM International Conference on Information and Knowledge Management (CIKM), Hong Kong, November 2009.
  42. Parallel Algorithms for Mining Large-scale Data (tutorial), ACM CIKM, November 2009.
  43. Information Extraction Meets Relational Databases (panelist), ACM CIKM, November 2009.
  44. Large-scale Data Mining (invited talk), CS Department Seminar, HKUST, Hong Kong, November 2009.
  45. From Blind to See, Advances in Massive Data Visualization (invited talk), the 7th National Workshop on Machine Learning and Applications, Nanjing, November 2009.
  46. Parallel Algorithms for Mining Large-scale Multimedia Data (tutorial), ACM International Conference on Multimedia, October 2009.
  47. Model-based vs. Data Driven (panelist), ACM International Conference on Multimedia, October 2009.
  48. Parallel Algorithms for Mining Large-scale Multimedia Data (invited lecture), Sino-German Summer School on Multimedia Computing, Tsinghua U, Beijing, September 2009.
  49. Innovation with Science and Humanity (distinguished lecture), New Computer Science Graduate Student Orientation, Tsinghua University, Beijing, September 2009.
  50. Confucius and "its" Intelligent Disciples (keynote), the 5th International Conference on Advanced Data Mining and Applications, Beijing, August 2009.
  51. New Frontier in Large-scale Genome Data Analysis, Genomics Institute, Hong Kong, August 2009.
  52. Innovation with Science and Humanity (invited talk), IEEE 125th Anniversary Student Congress, Singapore, July 2009.
  53. Parallel Algorithms for Mining Large-scale Data (invited tutorial), NSF European Workshop on Mining Massive Datasets (EMMDS), Copenhagen, July 2009.
  54. Distributed Constrained Optimization, (invited talk), HP Labs, Palo Alto, June 2009.
  55. Large-scale Collaborative Filtering (keynote), The 5th AAIM Conference, San Francisco, June 2009.
  56. Large-scale Photo Annotation Using Collective Wisdom of Data and Users (keynote), IEEE International Conference on Multimedia Computing and Systems, Ouarzazate, Morocco, April 2009.
  57. Parallel Algorithms for Mining Large-Scale Data (keynote), Workshop of Modeling, Mining and Managing Evolving Social Networks (in conjunction with ICDE), Shanghai, March 2009.
  58. Large-scale Collaborative Filtering (invited lecture, Andrew Yao's class), Tsinghua University, March 2009.
  59. From Machine Learning to Human Innovation (distinguished lecture), Public Lecture on Mathematics, Hong Kong, Feb. 2009.
  60. Large-scale Machine Learning Algorithm (invited lecture), Symposium of Machine Learning and Bioinformatics, Hong Kong, Feb. 2009.
  61. Large-scale Machine Learning Algorithms (invited talk), National Taiwan University/Academia Sinica, Taipei, December 2008.
  62. Beyond Search---Computational Intelligence for the Web (invited talk), NIPS, Vancouver/Whistler, December 2008.
  63. From Machine Learning to Human Innovation (invited talk), Annual Meeting of Machine Learning and Applications, Nanjing, November 2008.
  64. Large-scale Collaborative Filtering (invited talk), UC Berkeley EECS/Math Seminar, Berkeley, October 2008.
  65. Social Network Open Platform Strategies and Applications (invited talk), CSDN, Shanghai, September 2008.
  66. Organizing Multimedia Data Socially with Scalable Algorithms (keynote), ACM International Conference on Image and Video Retrieval, Niagara Falls, July 2008.
  67. Large-scale Social-Graph Mining, Challenges and Scalable Solutions (invited tutorial), MMDS, Workshop on Algorithms for Modern Massive Data Sets, Stanford University, June 2008.
  68. Rich Media and Web 2.0 (panel moderator), WWW, Beijing, April 2008.
  69. Massive Mining on Social Graphs (keynote), Social Network Data Mining Workshop, WWW, Beijing, April 2008.
  70. Organizing World's Information, Socially (invited talk), Stanford InfoSeminar, Computer Science Department, Stanford University, March 14th, 2008.
  71. Parallel, Combinational Collaborative Filtering (invited talk), HP Labs, Palo Alto, March 2008.
  72. Organizing World's Information, Socially (invited talk), Chinese University Hong Kong, Hong Kong, December 2007.
  73. Media Sharing on Social Networks (keynote), Pacific-rim Multimedia Conference, Hong Kong, December 2007.
  74. Web-scale Multimedia Data Management: Challenges and Remedies (keynote), Visual and Multimedia Digital Libraries, sponsored by European Commission Networks of Excellence, Modena, Italy, September 2007.
  75. Challenges of and Remedies for Large-scale Multimedia Information Retrieval (keynote), CVDB in conjunction with ACM SIGMOD, Beijing, June 2007.
  76. Internet, Past and Future (panel moderator), Internet+ Conference, Beijing, March 2007.
  77. Web 2.0 and Multimedia (keynote), International Conf. on Multimedia Modeling, Singapore, January 2007.
  78. Parallel Support Vector Machines, Google Tech Talk, Mountain View, December 2006.
  79. Unified & Scalable Learning for Multimedia Information Retrieval (keynote), MIR Workshop at ACM MM Conf., Santa Barbara, October 2006.
  80. Web 2.0, Synergy and Challenge (panelist), ACM MM Conf., Santa Barbara, October 2006.
  81. Unified Learning Paradigm and Web Personalization, Google Tech Talk, Mountain View, June 2006.
  82. Fotofiti: Goals, Features, and Research Agenda, Intel Santa Clara, December 2005.
  83. Statistical Foundations for Bridging the Semantic Gap (tutorial), ACM International Conference on Multimedia, Singapore, November 2005.
  84. A Unified Machine Learning Paradigm, Academia Sinica, Taipei, November 2005.
  85. A Unified Machine Learning Framework for Large-Scale Personalized Information Management (invited), The 5th Emerging Information Technology Conference, NTU Taipei, August 2005.
  86. Multimodal Metadata Fusion Using Causal Strength, Microsoft MM post-PC meeting workshop, July 2005.
  87. Distance-function Learning and Spectral Transformation, Microsoft, July 2005.
  88. Mathematics of Perception, Microsoft, June 2005.
  89. Mathematics of Perception, Ask Jeeves, New Jersey, May 2005.
  90. Mathematics of Perception, Google, Mountain View, May 2005.
  91. Mathematics of Perception, Intel, Santa Clara, May 2005.
  92. Mathematics of Perception, NCCU, Taiwan, April 2005.
  93. Parallel Algorithms for Speeding up Key Machine Learning Methods, Intel, Santa Clara, January 2005.
  94. Personal Image Organization and Search, NETAE, Cupertino, California, January 2005.
  95. Event Sensing on Distributed Video-Sensor Networks (keynote), Basenets 2004, in cooperation with ACM/IEEE Conf. on Broadband Networks, San Jose, October 2004.
  96. Modern Machine Learning Theories and Child Learning, CINA, Mountain View, California, July, 2004.
  97. Machine Learning for Information Retrieval, John Hopkins Applied Physics Lab., April, 2004.
  98. Perception-based Image Retrieval, An Interdisciplinary System of Computer Vision, Machine Learning and Databases, UIUC Database Seminar, April 2004.
  99. Video Surveillance and Sensor Networks, NEC Research Lab., March 2004.
  100. Perception-based Image Retrieval, Google, Mountain View, January 2004.
  101. Sfinx: A Multi-sensor Fusion and Mining System, Intel, Santa Clara, January 2004.
  102. Statistical Learning under Extreme Constraints, National University of Singapore, Singapore, December 2003.
  103. Sfinx: A Multi-sensor Fusion and Mining System, IEEE PCM, Singapore, December 2003.
  104. Sequence-data Learning for Video Surveillance, Academic Sinica, Taipei, December 2003.
  105. Statistical Learning under Extreme Constraints, Chaio-Tung University, Hsin-Chu, December 2003.
  106. High-performance Pre-emptible and MEMS-based IOs, IBM Almaden Research Center, San Jose, November 2003.
  107. Statistical Learning for Emerging Bio and Surveillance Applications, ITRI, Hsin-Chu, September 2003.
  108. Statistical Learning for Emerging Bio and Surveillance Applications, National Taiwan U, Taipei, September 2003.
  109. Statistical Learning under Extreme Constraints, Mitsubishi Research Lab., Cambridge, August 2003.
  110. Statistical Learning Methods for Visual Information Retrieval, IEEE Image Processing Conference (ICIP), Barcelona, August 2003.
  111. Statistical Learning for Visual Information Analysis and Retrieval (tutorial), IEEE International Conference on Multimedia, Baltimore, July 2003.
  112. Project SFINX - Multi-sensor Fusion and Mining, IBM T.J. Watson Workshop on Multimedia, New York, June 2003.
  113. Statistical Learning Methods for Emerging Database Applications (plenary tutorial), DASFAA, Kyoto University, Kyoto, March 2003.
  114. Statistical Learning Methods for Emerging Database Applications, Academic Sinica, Taipei, March 2003.
  115. Multimedia Indexing: Promises and Problems, Panel, IEEE International Conference on Multimedia, Lausanne, Switzerland, August 2002.
  116. Research Issues in Multimedia Databases, Research Seminar, UCLA, August 2002.
  117. PBIR Overview, MixedGrill, Santa Barbara, July 2002.
  118. Statistical Learning under Extreme Constraints, ITRI (Industrial Technology Research Institute) Seminar, Taiwan, May 2002.
  119. Learning and Measuring Perceptual Similarity, ICASSP Special Session in Statistical Learning Methods, Orlando, May 2002.
  120. Interactive TV Infrastructures, SONY Research, San Jose, April 2002.
  121. Dynamic Partial Function --- A Perceptual Distance Function for Measuring Similarity, Digital Library Seminar, Computer Science, UC Berkeley, Feb. 2002.
  122. Multimedia Data Mining, HP Data Mining Lab., Palo Alto, January 2002.
  123. Measuring and Learning Perceptual Similarity, HP Media Management Lab., Palo Alto, December 2001.
  124. Measuring and Learning Perceptual Similarity, CS Seminar, UCLA, October 2001
  125. Measuring and Learning Perceptual Similarity, NSF Workshop, INRIA-Rocquencourt, France, September 2001.
  126. Learning Query Concepts via Intelligent Sampling, IBM Almaden Research Center, September 2001.
  127. Learning Query Concepts via Intelligent Sampling, IBM T.J. Watson Research Center, New York, August 2001.
  128. Perception-based Image Retrieval, SONY Music, San Franscisco, June 2001.
  129. Personalizable Interactive Digital VCR, SONY Research, April 2001.
  130. On Managing Continuous Media Data, Compaq Western Research Lab, Palo Alto, September 2000.
  131. Personalizable Interactive Digital VCR, IBM T.J. Watson, February 2000.
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