• B.A. in Mathematics (cum laude), Cornell University, USA, May 2001
• M.A. in Mathematics, University of California, Los Angeles (UCLA), USA, December 2002
• Ph.D. in Mathematics, University of California, Los Angeles (UCLA), USA, June 2006

• 2009 Best Teaching Award, Sirindhorn International Institute of Technology.
• The Robert Sorgenfrey Distinguished Teaching Assistant Award 2005. Department of Mathematics. UCLA, CA.
• The Cranson W. and Edna B. Shelly Award for Excellence in Undergraduate Research in Astronomy 1999-2000, Cornell University, NY.
• Full DPST Scholarship, (Development and Promotion for Science and Technology) from the Royal Thai Government, 1996-2006.

Algebraic topology, Cryptography, Intelligent User Interface (IUI), and Machine learning

Algebraic Topology is a branch of mathematics which uses tools from abstract algebra to study topological spaces. The basic goal is to find algebraic invariants that classify topological spaces up to homeomorphism. The word “Topology” comes from the Greek words “topos”, which means place, and “logos”, which means study. Topology is the study of the properties of spaces that are invariant (preserved) under deformations, twisting, and stretching. It is often said that a topologist is a person who cannot tell the difference between their doughnut and their coffee mug, since each can be continuously deformed to the other (each is a solid sphere with one handle).

Cryptography can be summarized at a high level as the theory and practice of controlling information. Simple examples of its applications can be found in many places in modern society-perhaps the most prominent is that of securing electronic commerce. Branches of cryptography touch many areas of mathematics and computer science, including algebra, number theory, combinatorics and complexity theory, to name a few.

Intelligent User Interface (IUI) is a study on the development of human-machine interfaces that work naturally to the users, as well as improve the efficiency and effectiveness of the interaction. The goal of IUI is basically fulfilled by applying various techniques from Artificial Intelligence, Machine Learning, and Statistics, such as knowledge representation and reasoning, user modeling, gesture recognition, natural language processing, etc.

Machine Learning is a field of study that focuses on automatically constructing models from a set of collected examples. The obtained model can be used to predict the properties of the data found in the future. For example, a credit card company may need a model to predict if a payment made through their credit card is fraud or not. Manually constructing a model takes huge efforts and it may miss some fraudulent behaviors. Machine Learning helps reduce the required efforts, and wisely utilize a large amount of collected data.

• 2008-Present: SIIT.
• September 2006-2008: Assistant Professor in Residence, Department of Mathematics, University of Connecticut.
• June 2006-August 2006: Lecturer, Department of Mathematics, UCLA.
• January 2006-June 2006: Teaching Instructor, Department of Mathematics, UCLA.
• September 2005-January 2006: Teaching Assistant Consultant, Department of Mathematics, UCLA.
• July 2004 -August 2005: Teaching Assistant, Department of Mathematics, UCLA.
• January 2003-June 2004: Teaching Assistant, Astronomy Department, UCLA.
• July 1999-May 2001: Astronomy Research Assistant, Astronomy Department, Cornell University.

Selected Invited Talks

• Topological Theory of Fixed and Periodic Points -TTFPP 2007, Bedlewo Poland,July 22-28, 2007.
• AMS Special Session on Fixed Point Theory, Dynamics, and Group Theory, Joint Mathematics Meetings, New Orleans, Louisiana, January 5-8, 2007.

Publications

• A study and analysis of users’ one-handed thumb typing behaviors on smartphones (with Piyoros Tungthamthiti and Cholwich Nattee), Proceedings of the International Conference on Information and Communication Technology for Embedded Systems (ICICTES 2013) [CD-ROM], Samutsongkhram, Thailand, January 24-26, 2013, 49-53.
• Interior fixed points of unit-sphere-preserving Euclidean maps (with Robert F. Brown; Catherine Lee; and Sompong Dhompongsa), Fixed Point Theory and Applications, Vol. 2012, Article ID. 183 (2012) 8 p.
• Governing shifted characters of Thai input method for smartphones (with Piyoros Tungthamthiti and Cholwich Nattee), Proceedings of the 6th International Conference on Soft Computing and Intelligent Systems, and the 13th International Symposium on Advanced Intelligent Systems (SCIS-ISIS 2012) [CD-ROM], Kobe, Japan, November 20-24, 2012, 1584-1589.
• A preliminary report on applying density function for positive and unlabeled learning on text categorization (with Cholwich Nattee and Masayuki Numao), Proceedings of The First ASIAN Conference on Information Systems (ACIS 2012) [CD-ROM] , Siem Reap, Cambodia, December 6-8, 2012, 384-387.
• An acronym-based candidate generation technique for virtual keyboard on smartphone: a preliminary report (with Cholwich Nattee), Proceedings of The First ASIAN Conference on Information Systems (ACIS 2012) [CD-ROM] , Siem Reap, Cambodia, December 6-8, 2012, 348-351.
• Nielsen theory and some selected applications to differential and integral equations; a brief survey, Journal of Nonlinear Analysis and Optimization, Vol. 2 (2011) No. 1, 19-24.
• Insights regarding the usefulness of partial notes in mathematics courses (with F. Cardetti and M. C. Orgnero), Journal of the Scholarship of Teaching and Learning, Vol. 10 (2010) No. 1, 80-92.
• Fixed points of maps of a nonaspherical wedge, (with S. Kim, R. F. Brown, A. Ericksen, and K. Merrill), Fixed Point Theory and Applications, Vol. 2009, Article ID 531037 (2009) 18 p.
• Estimating Nielsen number on wedge product spaces (with S. Kim), Fixed Point Theory and Applications, Vol. 2007.
• An algorithm for calculating the mod H Reidemeister trace of some maps of surfaces with boundary, Ph.D thesis UCLA, 2006.
• Two-distance preserving functions (with R. Connelly), Contributions in Algebra and Geometry, Vol. 43 (2002) No. 2, 557-564.