Technology startup founder and researcher on machine learning & natural language processing
- I am currently running a New York based technology startup on knowledge extraction from big data using machine learning and natural language processing techniques. Previously, I worked at Bridgewater Associates (Elemental Cognition) and IBM Research both as a researcher. Prior to joining IBM, I received Ph.D on artificial intelligence at the University of Massachusetts at Amherst. I also did internship at Microsoft research (2009), IBM research (2008), and eBay research (2007) on search engine, ranking and sentiment analysis.
- Email: changwangnk AT gmail.com
- Machine Learning (Manifold Learning, Transfer Learning, Representation Learning and Deep Learning);
- Application of Machine Learning in Natural Language Processing (NLP), Data Mining and Information Retrieval (IR)
- Knowledge graphs on finance, science & technology
- Ph.D. Department of Computer Science. University of Massachusetts, Amherst
- MS. Department of Computer Science. Nankai University.
- BS. Department of Computer Science. Nankai University.
- 2018.03-Now: Co-Founder of FMeasure Inc. (explainable AI and knowledge graph for finance)
- We track and analyze financial data (company filings, earning calls, financials, patents, papers, trademarks, news, social media, recent investment activities, funding rounds and acquisitions, etc) in real-time, and integrate all such data in a large financial knowledge graph. Leveraging this knowledge graph and a set of built-in natural language processing and machine learning components, we deliver results with explanations for a number of tricky financial tasks like acquirer recommendation, market research report generation and technology investing.
- 2018.05-Now: Founder of www.paperdigest.org. (sci-tech knowledge graph and text analysis platform for scientific literature)
- Lead a team to develop and manage https://www.paperdigest.org, a science-technology knowledge graph and text analysis platform for scientific literature tracking, search and summarization. We currently track ~250 research areas from the following subjects: Biology, Computer Science, EE and System Science, Finance, Health Science, Math, Physics, and Statistics, and maintain a science-technology knowledge graph constructed from more than 100M documents. Four major services are offered to users: daily paper digest, conference digest, real-time topic tracking and search (paper, patent, grant, expert). Several features we offer are unique: (1) Our system automatically produces a one sentence summary for every new paper added to our system to help readers quickly decide if a paper is worth reading or not; (2) Our paper search service returns results with related papers, patents and grants such that people can quickly check if a similar idea has already been published, patented or funded. We also provide expert lookup, co-author lookup and patent lawyer search services.
- 2015.03-2018.03: Researcher at Elemental Cognition within Bridgewater Associates
- 2010.08-2015.03: Research Staff Member at IBM Research (T. J. Watson)
- As one of the original IBM Watson team members, built the Jeopardy! winning machine – IBM Watson System. I focused on relation extraction and statistical knowledgebase (KB) construction components.
- 2004.09-2010.08: RA/TA for Department of Computer Science, University of Massachusetts, Amherst
- 2009: Summer Intern at Microsoft Research (Cambridge)- IR Group: Ranking, Retrieval on Click Graph (10M distinct queries), Relevance Feedback.
- 2008: Summer Intern at IBM Research (T. J. Watson)– Deep Question Answering with ‘Jeopardy!’ Team.
- 2007: Summer Intern at eBay Research (San Jose)– Topic Modeling, Sentiment Mining
- 2003.1-2004.08: RA for Department of Computer Science and Engineering, University of Nebraska, Lincoln:
- SVM, Kernel methods and their applications in biology
- 2002.07-2002.12: Working on ROLAP Based Data Warehouse for Yonyou.
- 1999.07-2002.07: RA/TA for Department of Computer Science, Nankai University: Machine Learning and its application in Bioinformatics.
- Chang Wang, Liangliang Cao, James Fan Building Joint Spaces for Relation Extraction The 25th International Joint Conference on Artificial Intelligence (IJCAI 2016).
- Chang Wang, Liangliang Cao, Bowen Zhou Medical Synonym Extraction with Concept Space Models The 24th International Joint Conference on Artificial Intelligence (IJCAI 2015).
- Chang Wang, James Fan Medical Relation Extraction with Manifold Models The 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014).
- Chang Wang, Sridhar Mahadevan Manifold Alignment Preserving Global Geometry The 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013).
- Chang Wang, Sridhar Mahadevan Multisscale Manifold Learning The 27th Conference on Artificial Intelligence (AAAI 2013).
- Bonan Min, Ralph Grishman, Li Wan, Chang Wang, David Gondek Distant Supervision for Relation Extraction with an Incomplete Knowledge Base. The 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2013)
- Chang Wang, Aditya A. Kalyanpur, James Fan, Bran Boguraev, David Gondek Relation Extraction and Scoring in DeepQA. IBM Journal of Research and Development. (IBM R&D 2012). Special Issue on Watson in Jeopardy!,
- Chang Wang, James Fan, Aditya A. Kalyanpur, David Gondek Relation Extraction with Relation Topics. The 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP 2011).
- Chang Wang, Sridhar Mahadevan Jointly Learning Data-Dependent Label and Locality-Preserving Projections. The 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011).
- Chang Wang, Emine Yilmaz, Martin Szummer Relevance Feedback Exploiting Query-specific Document Manifolds The 20th ACM Conference on Information and Knowledge Management (CIKM2011).
- Chang Wang, Sridhar Mahadevan Heterogeneous Domain Adaptation using Manifold Alignment. The 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011).
- Chang Wang A Geometric Framework For Transfer Learning Using Manifold Alignment. PhD Thesis (Sep 2010).
- Chang Wang, Sridhar Mahadevan Manifold Alignment without Correspondence. The 21st International Joint Conference on Artificial Intelligence (IJCAI 2009).
- Chang Wang, Sridhar Mahadevan Multiscale Analysis of Document Corpora Based on Diffusion Models. The 21st International Joint Conference on Artificial Intelligence (IJCAI 2009).
- Chang Wang, Sridhar Mahadevan A General Framework for Manifold Alignment. AAAI Fall Symposium on Manifold Learning and its Applications, 2009. (AAAI FS 2009)
- Chang Wang, Sridhar Mahadevan Manifold Alignment using Procrustes Analysis. The 25th International Conference on Machine Learning (ICML 2008). pages 1120-1127, Helsinki, Finland, July 2008.
- Jeff Johns, Sridhar Mahadevan, Chang Wang Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization. The 22nd AAAI Conference on Artificial Intelligence (AAAI 2007).
- Sridhar Mahadevan, Sarah Osentoski, Jeff Johns, Kimberly Ferguson, and Chang Wang Learning to Plan using Harmonic Analysis of Diffusion Models. The 17th International Conference on Automated Planning and Scheduling (ICAPS 2007)
- Chang Wang, Stephen Scott New kernels for Protein Motif Discovery and Function Classification. The 22nd International Conference on Machine Learning (ICML 2005). pages 945-952, Bonn, Germany, August 2005.
- Chang Wang, Stephen Scott, Qingping Tao, Dmitri E. Fomenko, Vadim N. Gladyshev New Techniques for Generation and Analysis of Evolutionary Trees. In 2004 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, pages 283-289, Las Vegas, 2004.
- Chang Wang, Stephen Scott, Jun Zhang, Qingping Tao, Dmitri E. Fomenko, Vadim N. GladyshevA Study in Modeling Low-Conservation Protein Superfamilies. Technical Report UNL-CSE-2004-0003, University of Nebraska 2004
- Chang Wang, Zengqiang Chen, Zhuzhi Yuan K-Means Clustering Based on Genetic Algorithm. Journal of Computer Science. 2003. 2
- Chang Wang, Zengqiang Chen, Zhuzhi Yuan Method of Online Analytical Processing on Nucleotide Sequences Database. Journal of Computer Science. 2003. 3
- Chang Wang, Zengqiang Chen, Zhuzhi Yuan Clustering of Amino Acid Sequences based on K-Medoids Method. Journal of Computer Engineering. 2003. 8
- Chang Wang Genetic Algorithm Based Data Mining for Bioinformatics. Thesis for Master Degree. Nankai University. 2002
- Chang Wang Theory of Adaptive Test Based on Computational Intelligence. Journal of Education Technology. 2001. 2
- Chang Wang Recognition of Chinese Manuscript Characters based on Computational Intelligence. Thesis for Bachelor Degree. Nankai University. 1999
Reviewer for the following journals and conferences:
- Journal of Machine Learning Research (JMLR)
- Journal of Artificial Intelligence Research (JAIR)
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- IEEE Transactions on Image Processing (IIP)
- IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
- ACM Transactions on Information Systems (TOIS)
- Artificial Intelligence (AIJ)
- Transactions of the Association for Computational Linguistics (TACL)
- The VLDB Journal (VLDB)
- Information Retrieval Journal
- Journal of Computer Science and Technology (JCST)
- Journal of Web Semantics (JWS)
- International Journal of Computer Vision (IJCV)
- Pattern Recognition (PR)
- Neuro Computing
- ACM SIGMOD Conference (SIGMOD)
- Annual Meeting of the Association for Computational Linguistics (ACL)
- The Conference on Empirical Methods on Natural Language Processing Conference (EMNLP)
- The Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)
- AAAI Conference on Artificial Intelligence (AAAI), etc