1. Vision + Focus + Execution
Meiliu Lu, RVR 5016,
For CSc 209 Fall 2002, 12/03/02

2. Outline Know what is going to happen
Interests – key elements to keep you going
Select a topic – utility vs. innovation, learning, timing
Methodology
Take a look at how others have done
Start and finish yours

3. R. W. Hamming on R & D What can happen  Science
What will happen  engineering & economics
What should happen  morals, ethics and including what society is prepared to accept and reject

4. Richard M. Karp’s 3 Principles on Making Career Decisions
Understand what you are good at and what you like to do, and choose accordingly. In the words of Socrates, “Know thyself.”
Disregard the fashions of the day and search for new areas of research that are about to become important. In the words of the great hockey player and philosopher Wayne Gretzky, “Skate to where the puck is gonna be.”
To find exciting problems, look at the interfaces between disciplines.

5. Research Interests Machine learning applications
Data mining and integration
Courseware Development
Data mining (C Sc 196K)
Bioinformatics Technology (C Sc 212)
Programming Languages (C Sc 136)…

6. What is Data Mining?
Data mining, simulation, and modeling are part of a large process – Knowledge Discovery in Data (KDD)
Finding hidden information in a database
Fit data to a model
Web related data
Business, health, and financial data
Scientific and Engineering

7. Data Mining Algorithms
Objective: fit data to a model
Descriptive
Predictive
Preference – technique to choose the best model
Search – technique to search the data
“Query”

8. Query Examples Database Data mining
Find all credit applications with last name of smith
Identify customers who have purchased more than $10,000 in the last month.
Find all customers who have purchased milk
Data mining
Find all credit applicants who are poor credit risks. (classification)
Identify customers with similar buying habits. (clustering)
Find all item which are frequently purchased with milk. (association rules)

9. Challenges for Knowledge Discovery in Biology– Russ Altman
Bioinformatics is the study of information flow in biology – from genotype to phenotype
Sequence, structure , and function analysis
Challenges:
Computational model of physiology
Design of new computer algorithms
Engineering new biological pathway
Data mining for new science

10. What Challenges Does Biology Offer CS?
Cracking the genome code is complex: prediction methods and models
Amount of data is growing at an exponential rate: data management
Biological data is very complex and interlinked: information systems that allow biologist to seamlessly follow these links without getting lost
Each gene isn’t an independent entity: putting genomic and biochemical data together into models of biochemistry and physiology

11. Extracting Knowledge from Gene Expression Data: A Case Study of Batten Disease – S. M. Lin
Duke University Medical Center proposed a prototype KDD system to enable scientists to analyze the massive microarray data, form hypotheses, and draw insights directly into underlying mechanisms of diseases.
Data  Microarray database  data mining  patterns  human experts  Genomics knowledge base  discoveries

12. Your MS Project Try to make someone happy yourself
people who helped you
people who need help
Start early, keep working, finish on time

13. Sample MS Project 1
Jeffery Lewis, Spring 2001, “Audio Compression for Music Synthesis Using Gaussion Functions and Genetic Algorithms”
Paper published in the proceedings of 3rd International Conference on Information Reuse and Integration. November 2001
Self-selected topic

14. Sample MS Project 2
Yan Xiong, Summer 2002, “A Web-Based Microarray Management System”
Paper published in the 15th International Conference on Computer Applications in Industry and Engineering. November 2002.
Topic introduced at CSC 209 Fall 2001
Improvement: engineering and function

15. Sample MS Project 3
Wen Xia, Fall 2002, “Online Course Management System”
Developed for C Sc 138 and can be adopted for other courses
Topic selected by self (continue development of an existing tool)
More system enhancement can be a new MS project

16. Possible New MS Projects
Any machine learning applications of your choice
Web information management system (improvement or new development)
Easy access
Easy information exchange
Verify, update, and security
Report and visualization

17. Possible New MS Projects (cont.)
Courseware – a collection of examples/case studies/assignments design and implementation – a teaching module with learning outcome requirements
C Sc 196K: data warehousing and data mining
C Sc 212: Bioinformatics algorithms and data integration
C Sc 136: XML, functional and logical Programming languages

18. Writing Report
“MS Thesis and Project Writing Guide” at:
Format, References and Acknowledgement
A useful reference book: “Writing for Computer Science” by Justin Zobel, Springer, 1998.
Game of time and stepping stone

19. Leaders are Visionaries Dr. Ernie Bodai
They have a poorly developed sense of fear
They have no concept of the odds against them
They make the impossible happen