course participants course announcements about this wiki questionnaires and assignments slides of presentations course schedule related resources Gerhard Fischer Hal Eden Mohammad Al-Mutawa Ashok Basawapatna Lee Becker Jinho Daniel Choi Guy Cobb Holger Dick Nwanua Elumeze Soumya Ghosh Rhonda Hoenigman elided#1 Dan Knights Kyu Han Koh elided#2 Yu-Li Liang Paul David Marshall Keith Maull Jane Kathryn Meyers John Michalakes Michael Wilson Otte Deleted Page Joel Pfeiffer Caleb Timothy Phillips Dola Saha deleted |
1. Your name: - Jinho Choi 2. The intended topic area for your PhD: - Natural Language Processing(NLP); especially in Machine Translation(MT) by semantic structures 3. Most important reason for you personally to get a PhD - It's not about getting a PhD; it's about doing a PhD. I believe what I achieve from my research will be beneficial to the society, and doing a PhD provides me great opportunities to gain knowledge, develop the original ideas, and collaborate with people. Furthermore, I want to be a professor at some time, so I can not only pass what I know to my students but also get fresh ideas from them. 4. Name three computer scientist which YOU consider most important for the field and what you consider their contribution 4.1. Martha Palmer (University of Colorado) - My current advisor at CU. She developed PropBank which brings semantics to syntactic structures in NLP. Many NLP studies such as MT found their limitations from just using syntactic structures and PropBank can take them to another level. 4.2. Mitch Marcus (University of Pennsylvania) - My formal advisor at UPenn. He developed Penn Treebank which now became the beginning point of NLP studying. Most NLP tools use Penn Treebank for their training data and more. 4.3. Michael Collins (MIT) - He is the one developed statistical parser in Wall-Street-Journal corpus. People still try to develop various parsers with better performance, and Collin's parser sets the basis for the research. 5. Name the three most important, professionally relevant books which you have read 5.1. Foundations of Statistical Natural Language Processing by Christopher D. Manning and Hinrich Schütze - If you want to study NLP but lack in either Linguistic or Computer Science background, this is one for you. It covers various topics in NLP including syntactic parsing, semantic role-labeling, word sense disambiguation, etc. 5.2. Machine Learning by Thomas Mitchell - This book is not for beginners; it requires a bit of math background, but explains all kinds of machine learning algorithms very thoroughly. 5.3. Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein - Every computer science student probably has read this book at one point, which shows the value of it. 6. Assuming you will collaborate with researchers and explore ideas outside of CS during your PhD studies — which domains are the most likely candidates for this effort 6.1. Linguists - My research cannot be done without them. 6.2. Psychologists - I'm also interested in Cognitive Science which may possibly help me to develop machine learning techniques. 6.3. Educators - It is important to get feedbacks from my system and apply it to the next work, and I believe educators can help me for that. 7. Briefly characterize your own digital literacy: 7.1. which programming language do you know (mention them in an order of decreasing familiarity) - Java, C++, Python, Pearl, Pascal, Basic 7.2. Describe the top three projects (problem, programming language used, for what) which you have done in the past Project: Importing Korean features to Daniel Bikel's Parser - Language used: Java - Bikel's Parser is a tool that parses natural language to phrasal structure tagged by part-of-speech with some arguments (such as Penn Treebank). One of great features about the parser is that it is language independent; the parser works for English, Chinese, Arabic. I wrote plugins for Korean; analyzed the structural differences between English and Korean and taught the distinctions to the parser. Project: Real-time Automatic Alert System (RAAS) by using GIS - Language used: Java, J2ME, C++, Embedded Visual C++ - Here is the scenario of this system a) A person gets in trouble, and he/she pushes a certain button in a cellphone. b) The phone gets its location from a satellite, and sends its info to the nearest police office. c) The police office finds his/her location in a map, which updates in real-time, and tries to rescue. To do this, we had to collaborate with a telephone company and local police office. Most works were done in Java, and some mobile programming was done in Embedded Visual C++ and J2ME. Design of Educational Feedback System - Language: PHP, MySQL, Moodle - We designed a feedback system that could improve our teaching skills. We tried various Quiz/Exam methods that prevent students from cheating but help them understand materials behind questions better. 7.3. Which are the top three applications that you are familiar with (e.g. Photoshop, Canvas, Dreamweaver, iMovie, ….)? - Will I be too geek to say Terminal, Eclipse, Microsoft Visual Studio? (I do know a bit about Photoshop and iLife) 8. List your three favorite topics that you would like to see discussed in this course! 8.1. Analyzing Operating Systems (MS-Windows, Mac OS, Linux) - I know the debates have gone on more than decades, but I want to hear from computer scientists' views. 8.2. How far are we from Star-wars? (especially about AI and ubiquitous computing) - Is it just a dream or are we getting close? 8.3. What are the pros and cons for collaboration in studying? - In any collaboration, there is a possibility for free-ride, but there are many bright sights as well. How can we maximize the pros and minimize the cons? Last modified 31 August 2007 at 4:09 am by choijd |