Advice on Creative Thinking, Research, Writing and Speaking

The educational objectives of a Ph.D. program

Pursuing Ph.D. is to develop the following skills:

• Life-long self-learning capability
  • Technologies change very quickly.  Moreover, in your whole career life, you may need to change your technical areas multiple times.  Hence, you need to be able to learn new technologies by yourself (since no one is there to teach you after your graduation), and quickly catch up with the new technologies; otherwise, you may not be able to survive in the technical world.
• Thinking capability
  • Independent thinking capability
    • Independent thinking means that one should have his/her own views.  
  • Critical thinking capability
    • Critical thinking means that one should relentlessly attack the existing work/theory from all possible angles.  Attack its limitations and weaknesses or even tend to disprove the theory.   Unless the theory is completely justified, do not accept the theory.  After identifying the weaknesses of the theory, he/she is ready to think creatively. 
  • Creative thinking capability
    • Creative thinking means that one makes efforts to produce something which does not exist in the literature (e.g., insights, simpler proofs, new theorems).  
• Logical reasoning
  • Deductive reasoning:
    • reasoning from the general to the special;
    • can be trained by learning how to prove mathematical results (theorems, inequalities, etc.)
  • Inductive reasoning:
    • reasoning from the special to the general;
    • need to be able to identify the key common patterns in the observed phenomena;
    • there could be infinite number of possible patterns;
    • how to identify meaningful patterns is hard;
    • this is similar to knowledge discovery from a huge amount of data (a.k.a. data mining).
  • Abductive reasoning or plausible reasoning:
    • Plausible reasoning is a capability of identifying the hidden factors that cause the observed phenomena.
    • Plausible reasoning is crucial in knowledge discovery.
• Capability of doing independent and innovative research
• Writing skill, including writing journal/conference papers and proposals for grants
• Communication skill (able to make your ideas clear to others)
• Oral presentation skill (able to give a good talk and attract people's attention)
• Networking skill (good at socializing with professionals, government agencies and industry sponsors)
• Extras:
  • leadership
  • skill of managing a team
  • being a visionary

Useful links:

• Tips for PhD study http://www.ece.ncsu.edu/netwis/Phd_tips.php

Creative Thinking

• Types of thinking
  • Forward thinking (deductive)
  • Reverse thinking (inductive)
    • Given a problem, come up with various methods to solve it (need brainstorming)
    • Analogy: Given the peak of a mountain, try to find a path from the foot of the mountain to reach the peak.
    • Think about whether the problem is ill-posed; if so, reformulate the problem.
  • Vertical thinking:
  • Lateral thinking: multidisciplinary, cross multiple areas

  Vertical thinking	Lateral thinking
  Looking for the right approach	Looking for as many approaches as possible
  Rightness	Richness
  Proceeds if there is a direction	Proceeds to generate direction
  Is analytical	Is provocative (brainstorming)
  Is sequential	Can make jumps
  One must be correct at every step	One does not have to be correct at every step
  Uses negative to block off certain pathways	There is no negative
  Excludes what is irrelevant	Welcomes chance intrusions
  Fixed categories/labels	Labels may change
  Explores most likely paths	Explores least likely paths
  Is a finite process	Is a probabilistic process

   

• References:
  • Creativity and Creative Thinking
  • George Polya, ``Mathematical discovery: on understanding, learning, and teaching problem solving,'' New York: Wiley, 1981. 
  • George Polya, ``How to solve it : a new aspect of mathematical method,'' 2d ed., Princeton, N.J. : Princeton University Press, 1973.
  • George Polya, ``Mathematics and plausible reasoning,'' Princeton, N.J.: Princeton University Press, 1954. 
  • Associative learning and thinking,  Jack Deal.
  • Diane F. Halpern, "Thought and Knowledge: An Introduction to Critical Thinking," Lawrence Erlbaum Associates; 4th edition (July, 2002), ISBN: 0805839666.

Writing and Publishing

• Technical Writing on Henning Schulzrinne's web.
• Hints and common mistakes on Henning Schulzrinne's web.
• Criteria for Judging IEEE Prize Paper Awards, by IEEE Paper Awards Committee 
• How to Organize your Thesis, by John W. Chinneck.
• Advice to Authors of Extended Abstracts, by William Pugh.
• Hints on good mathematical writing, by David Goss
• A primer on mathematical writing, by Steven L. Kleiman
• How To Have Your Abstract Rejected, by van Leunen and Lipton.
• An Evaluation of the Ninth SOSP Submissions, or, How (and How Not) to Write a Good Systems Paper by Roy Levin and David D. Redell
• How to Get a Paper Accepted at OOPSLA, by Alan Snyder.
  • Includes comments from an OOPSLA program committee.
• Advice for 1996 POPL submissions
• How to write a white paper
• 4 levels of excellence in writing and the corresponding training
  • Level 1: Grammar
    • Features: There should be no grammatical errors.
    • Training: Develop grammar-awareness through intensive practice.
  • Level 2: Coherence and logic flow 
    • Features: Logic flow should be smooth.  There should be no jump in the presentation flow.
    • Training: Learn how to create flow between sentences, how to make transitions between paragraphs, how to present your thinking process.  Start from things known to things unknown.  The lower level where the writing starts, the better.  Begin at the beginning.  Don't start from the middle, with an assumption that the reader knows the beginning. A common fault of a writer is to assume that the reader has much knowledge about the subject to be addressed.
    • Keywords: coherence, cohesion, connection, transition, flow, evolution of thought, fluency
  • Level 3: Rhetoric and diversity in vocabulary and expressions
    • Features: Grace, elegance, giving an enjoyable reading.
    • Training: Build vocabulary and learn rhetoric through reading articles that are well-written.
  • Level 4: Achieving the objective (marketing, convincing the reader, selling your ideas, etc)
    • Features: conciseness, giving compelling reasons, persuasiveness, and clarity.
    • Training: Develop skills to make a persuasive, concise, logical and clear presentation.  The paper is expected to make compelling reading.
• Organization of a grant proposal   (writing a grant proposal is quite different from writing a technical paper)
  1. Introduction
     1. What problem?
     2. What approach?
     3. Advantages of the approach
     4. Potential impact of the proposed work
  2. Be concise; can cite your own paper for further details.  Reviewers do not have much time to read detailed descriptions in the proposal.
  3. Apply the old approach (developed in your thesis) to new problems, which are significant and interesting.
  4. Related work
• References:
  • J. M. Williams, "Style: ten lessons in clarity and grace," 7th ed., Longman, 2003.
  • T. N. Huckin and L. A. Olsen, "Technical writing and professional communication for nonnative speakers of English," 2nd ed., McGraw-Hill, 1991.
  • Effective communication: tips on technical writing [pdf]
    Malvar, H.S.
    IEEE Signal Processing Magazine, Volume: 25,  Issue: 3, Page(s): 129-132,    Date: May 2008
     

Research Skills

• Some good habits
  • Write a note in HTML after meeting with the advisor  
  • Write a report in HTML or Latex every week so that you can see your progress made.  The report describes what the problems are and how you approach the problems.   The report will become a journal/conference paper later.
  • Write down the problems you have encountered.  Use the techniques in the book of "How to solve it" to deal with it.  Approaches include
    • Simplifying the problem (solve the simpler problem first, then solve harder ones)
    • Divide and conquer 
    • Approximation
    • Find lower/upper bounds
    • Randomization
    • Removing dependence between events
• How can you judge your simulation results are correct, instead of results of buggy programs?
  • Use rough analysis to get approximation or lower/upper bound and check your simulation results are feasible.
    • For example, a linear program may not have analytical (close-form) solution.  However, when you remove some constraints, the new linear program may admit a close-form solution.  The objective value corresponding to this  solution can be used as a lower or upper bound for the objective function of the original linear program.
  • Use numerical analysis to get rough results to compare with the simulation results.
  • Simplify the constraints so that you can can rough analytical results to compare with the simulation results.
• On the other hand, analytical results also need validation by simulations.
• Minimize the critical path by appropriately allocating resources among nodes.   Sometimes, you solve one problem but create another problem.   What is the right tradeoff?   A smart design is to shift the burden in a right way, e.g., shifting the burden from memory to processor so as to minimize the delay.
• Graduate Study in the Computer and Mathematical Sciences: A Survival Manual, by Dianne O'Leary
• How to be a Good Graduate Student/Advisor, by Marie desJardins
• A Letter to Research Students, by Duane A. Bailey
• How to do Research in the MIT AI Lab, ed. David Chapman
• The IUCS Graduate Student Survival Guide.
  • Includes Survival Skills for Graduate Women
  • and The Assistant Professor's Guide to the Galaxy.
• "A Stroke of Genius: Striving for Greatness in All You Do" by Richard Hamming [pdf]

Speaking

A good talk is the one that can make the ideas presented crystal clear to the audience.

Tips:

1. If you lose your audience in the first two minutes, you will lose them in the whole talk.   So the first two minutes is very important and is called honey-moon period.   You should try every effort to attract their attention.   Use simple language (and figures) to show 
   • what the problem is,
   • what the motivation of your research is, and
   • why it is an interesting research issue.
2. The structure of your talk may be completely different from your paper.   In your paper, 
   • you can assume every reader is an expert in your area; 
   • you can assume that a reader can go back and forth through your paper (like having a large brain memory); 
   • you may make claims by referring to other publications;
   • you can use many techniques (e.g., use footnote and refer to later sections or appendix) to improve a reader's understanding;   
   • you can write 30 pages and cite 50 references to present your work.

   But in a talk, 

   • you need to adapt the level of the content to your targeted audience; 
   • you should assume they can only remember a few previous slides up to the slide that you are currently presenting (since they may not be familiar with your area), so you may need to repeat some contents when necessary; 
   • you need to provide concrete and convincing evidences in the talk since people may not accept/understand your claims (e.g., "other methods are complex but my method is simple" needs convincing justification).  So lots of effort is needed to find/construct such concrete and convincing evidences to justify your claims, when you prepare your slides.
   • you may not be able to put all related material together in one slide; so you may need to use words like "defined later", "described later" or "explained later" when new concepts appear in the slide but there is no space to describe them.  
   • you only have a limited time (say, 30 minutes) to present your work; you need to make sure all important information about your work appears in the slides; the content should not be superficial (since you need to show depth to impress the audience) and cannot be too thorough (otherwise you don't have enough time to present them).   You need to try every effort to strike a balance between these two competing objectives.
3. You talk is like telling a story; a story about how you explored the problem.  You need to use plausible/inductive reasoning, rather than deductive reasoning (directly present the final results).   The presentation  flow should be natural and logical to the audience who is not familiar with your work.   Presenting your thinking behind your work or your design philosophy would be very helpful for the audience to understand your work.
4. Do not jump in your presentation.   Make the presentation-flow smooth.  Every sentence/figure appeared in your slides should be followed easily by your targeted audience.   Then after the talk, your work will be crystal clear to the audience.
5. Every claim needs justification or reference.
6. If you can provide intuition while presenting theory precisely, it is a good talk.
7. Whenever presenting a plot, do not forget to describe what the x-axis and y-axis are.

A Top-Down Approach to Presenting Mathematical Theorems

1. Present the basic idea and sketch the proof. (Motivate the audience.)
2. Present the formal idea and the complete/rigorous proof.   If the proof is too complicated, only show an incomplete proof and leave the rigorous proof as a self-study reading.
3. Look back.   Provide the intuition about the theorem.   Indicate the possible impact/applications of the theorem.

Common problems that an unseasoned speaker may have:

• Some assumptions are not given.
• Some notations are not well explained.  Too many notations could confuse the audience.
• The level of the content is not accessible to those who are not familiar with your area. (The speaker may need to adapt the level/emphasis during the talk.)
• The slides do not follow logically.
• There are thought-jumps in the presentation.
• Lack examples.   Or the examples are not simple or not easily understandable.
• Key points are not emphasized adequately.  The time spent on each slide should be somehow proportional to its importance in the whole
  presentation.
• Do not know how to handle questions appropriately.  People may ask unexpected questions.   For example, people may ask you what if you change your assumption; how to apply your approach to another (unexpected) situation; how to solve a new problem.  The questions may get out of the focus of your talk and an unseasoned speaker may get lost in the questions.
  • Be polite but stick to the focus of your talk.
  • If you have a ready solution, tell the questioner.   If not, you could point out possible directions and then get back to your topic. 
  • To answer "what if you change your assumptions", you may say: "changing the assumptions  may result in different results and it may require intensive study.  I do not have a ready answer."

Advanced techniques:

• Create suspense to raise the curiosity of the audience. 
• Use stress and intonation to emphasize the key points. 
• Produce captivating presentation by visual aids (coloring, animation, videos, images, figures, etc.), which help guide the attention of viewers and effectively get across your message.
• Use jokes/anecdotes to relax the audience and make your talk an enjoyable experience.

Useful links:

• How to Give a Good Research Talk, by Simon Peyton Jones et al.
• How to Present a Paper in Theoretical Computer Science, by Ian Parberry.

Teaching Development

• Richard Felder's Home Page, RESOURCES IN SCIENCE AND ENGINEERING EDUCATION
   

Career Development

• Attributes of an excellent instructor
• Networking on the Network by Phil Agre
• Thomas Hull, Michael A. Jones, and Diana M. Thomas, Interviewing for a job in academia, Notices of the American Mathematical Society, November 1998, pages 1353-1357. Emphasizes the questions you should have ready answers to. http://www.ams.org/notices/199810/comm-hull.pdf
• Mary Corbin Sies, Academic job interview advice. A professor's advice based on experience. http://www.otal.umd.edu/~sies/jobadvice.html
  Plus more questions: http://www.otal.umd.edu/~sies/jobquess.html
• Adviser, Teacher, Role Model, Friend: On Being a Mentor to Students in Science and Engineering, National Academy Press, 1997. So you'll know what good advising is. http://www.nap.edu/readingroom/books/mentor/
• Computer Science Faculty and Research Positions
• The Young Scientists' Network
• CRA Committee on the Status of Women in Research
  • Includes a Graduate School Information Kit for Women in Computer Science and Engineering
  • and the Distributed Mentor Project for female undergraduates.
• ACM SIGMOD academic careers information
  • Includes transcripts from the Workshop on Academic Careers for Women.

Job hunting advice for scientists

• Peter S. Fiske, "Put Your Science to Work: The Take-Charge Career Guide for Scientists," American Geophysical Union (December 1, 2000)

Related Topics and Resources

• Information resources for graduate students by Jennifer Myers.
• A Guide for New Referees in Theoretical Computer Science, by Ian Parberry.
• On Being A Scientist: Responsible Conduct In Research, from the National Academy of Sciences
• Papers on women in computer science.
  • Includes Why Are There So Few Female Computer Scientists?, by Ellen Spertus.
• Study, Research, and Writing Skills web page from the American Communication Association.
• Information for current and prospective graduate students by Timothy Finin.
• A Guide for Applying to Graduate Schools by Piroz Mohseni.
• Ivan Sutherland, "Technology and Courage," in CMU Computer Science: A 25th Anniversary Commemorative, ed. Richard F. Rashid. ACM Press, 1991.
• Alan Jay Smith, "The task of the referee," IEEE Computer, April 1990, pp. 65-71.
• Free software for creating tables in Latex:  http://www.g32.org/latable/

Dissertation Advice

• Dissertation News, published by The Association for Support of Graduate Students.
• Resources for dissertation research (gopher)
• How to cope with "burnout", by Andreas Gehmeyr.
• How to Complete and Survive a Doctoral Dissertation, by David Sternberg. St. Martin's Press, New York. ISBN 0-312-39606-6
• How to Get Control of Your Time and Your Life, by Alan Lakein. Signet Books. ISBN 0-451-16772-4
• Procrastination: Why you do it, what to do about it, by Jane Burka and Lenora Yuen. Addison-Wesley. ISBN 0-201-55089-X

Humor

• How to Have a Bad Career in Research/Academia by David Patterson
• Burnout Prevention and Recovery at MIT
• A Dictionary of Useful Research Phrases

Leadership Development

• Leadership Training and Development Outline

Entrepreneurship Development

• Entrepreneurship, Entrepreneur, Enterprise