This document provides guidance on how to conduct research. It discusses what research is, different knowledge sources, and a seven step process for successful research: defining the research question, gathering information, forming a hypothesis, implementation/analysis, organizing results, communicating results, and revising. It also covers defining a good research question, reading papers, organizing references, and the nonlinear nature of research. The overall document serves as a guide for students and researchers on how to effectively plan and execute a research project.
9. What is Research?
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Search for knowledge, or as any systematic investigation, with an open mind,
to establish novel facts, usually using a scientific method. [Wikipedia]
10. What is Research?
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Studious inquiry or examination; especially : investigation or experimentation
aimed at the discovery and interpretation of facts, revision of accepted
theories or laws in the light of new facts, or practical application of such new
or revised theories or laws [Merriam-Webster Collegiate Dictionary, Tenth
Edition]
Search for knowledge, or as any systematic investigation, with an open mind,
to establish novel facts, usually using a scientific method. [Wikipedia]
11. What is Research?
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Studious inquiry or examination; especially : investigation or experimentation
aimed at the discovery and interpretation of facts, revision of accepted
theories or laws in the light of new facts, or practical application of such new
or revised theories or laws [Merriam-Webster Collegiate Dictionary, Tenth
Edition]
Search for knowledge, or as any systematic investigation, with an open mind,
to establish novel facts, usually using a scientific method. [Wikipedia]
Research is an organized and systematic way of finding answers to questions
13. In Computer Science Context
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Discovery of new knowledge of computing through
mathematical analysis, modeling, and experimental
evaluation of algorithms and computer software.
16. Why Do Research?
• To contribute to knowledge
• To satisfy intellectual curiosity
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17. Why Do Research?
• To contribute to knowledge
• To satisfy intellectual curiosity
• For enjoyment you derive from posing your
own problems and solving them
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18. Why Do Research?
• To contribute to knowledge
• To satisfy intellectual curiosity
• For enjoyment you derive from posing your
own problems and solving them
• To help career growth (Promotion & Tenure)
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19. Why Do Research?
• To contribute to knowledge
• To satisfy intellectual curiosity
• For enjoyment you derive from posing your
own problems and solving them
• To help career growth (Promotion & Tenure)
• To see places and meet interesting people
from all over the world at subsidized expenses
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21. Knowledge Sources or Ways of
Knowing
• Intuition: Takes forms such as belief, faith, intuition, etc. Based on
feelings rather than hard, cold "facts.“
• In research we often use this knowledge source for coming up with an
initial idea for research
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22. Knowledge Sources or Ways of
Knowing
• Intuition: Takes forms such as belief, faith, intuition, etc. Based on
feelings rather than hard, cold "facts.“
• In research we often use this knowledge source for coming up with an
initial idea for research
• Authority: Information received from experts, books, etc. Its strength
depends on the strength of these sources.
• We use this kind of source for literature review
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23. Knowledge Sources or Ways of
Knowing
• Intuition: Takes forms such as belief, faith, intuition, etc. Based on
feelings rather than hard, cold "facts.“
• In research we often use this knowledge source for coming up with an
initial idea for research
• Authority: Information received from experts, books, etc. Its strength
depends on the strength of these sources.
• We use this kind of source for literature review
• Logic: Gained by reasoning
• We rely on this when analyzing/modifying/improving an algorithm
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24. Knowledge Sources or Ways of
Knowing
• Intuition: Takes forms such as belief, faith, intuition, etc. Based on
feelings rather than hard, cold "facts.“
• In research we often use this knowledge source for coming up with an
initial idea for research
• Authority: Information received from experts, books, etc. Its strength
depends on the strength of these sources.
• We use this kind of source for literature review
• Logic: Gained by reasoning
• We rely on this when analyzing/modifying/improving an algorithm
• Empirical: Based on demonstrable, objective facts ,determined through
observation and/or experimentation.
• Used when we want to study the behavior of a complex piece of software
or the accuracy of an algorithm using benchmark data sets.
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26. Seven Steps to Successful Research
• Defining the Research Question
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27. Seven Steps to Successful Research
• Defining the Research Question
• Information Gathering
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28. Seven Steps to Successful Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
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29. Seven Steps to Successful Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
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30. Seven Steps to Successful Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
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31. Seven Steps to Successful Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
• Writing and Communicating Results
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32. Seven Steps to Successful Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
• Writing and Communicating Results
• Revising, Resubmitting, and Publication
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33. Nonlinear Nature of Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
• Writing and Communicating Results
• Revising, Resubmitting, and Publication
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34. Nonlinear Nature of Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
• Writing and Communicating Results
• Revising, Resubmitting, and Publication
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35. Nonlinear Nature of Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
• Writing and Communicating Results
• Revising, Resubmitting, and Publication
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36. Nonlinear Nature of Research
• Defining the Research Question
• Information Gathering
• Forming a Hypothesis/Algorithm Outline
• Implementation/Simulation/Analysis
• Organizing and Interpreting Results
• Writing and Communicating Results
• Revising, Resubmitting, and Publication
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38. Defining the Research Question
• What subfield of CS/IT interests me?
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39. Defining the Research Question
• What subfield of CS/IT interests me?
• Within the subfield, what interests me more?
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40. Defining the Research Question
• What subfield of CS/IT interests me?
• Within the subfield, what interests me more?
• What is my chief strength?
– Mathematical abstraction
– Implementation/Experimentation
– Problem solving
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41. Defining the Research Question
• What subfield of CS/IT interests me?
• Within the subfield, what interests me more?
• What is my chief strength?
– Mathematical abstraction
– Implementation/Experimentation
– Problem solving
• What would be the outcome?
– A better model
– A better algorithm
– A new application
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44. Defining the Research Question
• Is the topic timely?
• Does it have potential for further
research/jobs?
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45. Defining the Research Question
• Is the topic timely?
• Does it have potential for further
research/jobs?
• Are there good prior works to build upon?
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46. Defining the Research Question
• Is the topic timely?
• Does it have potential for further
research/jobs?
• Are there good prior works to build upon?
• How big is the research community?
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47. Defining the Research Question
• Is the topic timely?
• Does it have potential for further
research/jobs?
• Are there good prior works to build upon?
• How big is the research community?
• Who are the major players?
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50. Information Gathering
• Locating prior published work
– Make sure to check the homepages of prominent
active researchers for their most recent work
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51. Information Gathering
• Locating prior published work
– Make sure to check the homepages of prominent
active researchers for their most recent work
– Use ACM/IEEE digital libraries, Google and
CiteSeer to locate important papers
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52. Information Gathering
• Locating prior published work
– Make sure to check the homepages of prominent
active researchers for their most recent work
– Use ACM/IEEE digital libraries, Google and
CiteSeer to locate important papers
– Make sure to look through the recent proceedings
of the prestigious conferences in your area
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53. Information Gathering
• Locating prior published work
– Make sure to check the homepages of prominent
active researchers for their most recent work
– Use ACM/IEEE digital libraries, Google and
CiteSeer to locate important papers
– Make sure to look through the recent proceedings
of the prestigious conferences in your area
– Try to locate review papers of your’s and related
fields
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55. Reading Papers
• Do paper reading in two or three
passes. Ignore the technical
details in the first pass
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56. Reading Papers
• Do paper reading in two or three
passes. Ignore the technical
details in the first pass
• Generally, reading the abstract,
introduction, and summary and
conclusion sections is good
enough to determine whether a
given paper should be read in
detail or not.
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57. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
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58. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
– What is the research problem the paper attempts to
address?
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59. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
– What is the research problem the paper attempts to
address?
– What is the motivation of the research work?
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60. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
– What is the research problem the paper attempts to
address?
– What is the motivation of the research work?
– Is the research work attempting to overcome the
weaknesses of existing approaches?
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61. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
– What is the research problem the paper attempts to
address?
– What is the motivation of the research work?
– Is the research work attempting to overcome the
weaknesses of existing approaches?
– What is new in this paper?
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62. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
– What is the research problem the paper attempts to
address?
– What is the motivation of the research work?
– Is the research work attempting to overcome the
weaknesses of existing approaches?
– What is new in this paper?
– How are the research claims substantiated?
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63. First Pass of Reading
• The first pass reading should be done to answer
the following questions:
– What is the research problem the paper attempts to
address?
– What is the motivation of the research work?
– Is the research work attempting to overcome the
weaknesses of existing approaches?
– What is new in this paper?
– How are the research claims substantiated?
– Conclusions and pointers to future work
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64. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
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65. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
– What is the core of the research problem addressed in the
paper?
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66. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
– What is the core of the research problem addressed in the
paper?
– Are there some alternative approaches to address the
research problem?
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67. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
– What is the core of the research problem addressed in the
paper?
– Are there some alternative approaches to address the
research problem?
– Are there some good arguments to be made against the
assumptions/approach taken by the authors?
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68. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
– What is the core of the research problem addressed in the
paper?
– Are there some alternative approaches to address the
research problem?
– Are there some good arguments to be made against the
assumptions/approach taken by the authors?
– How can the research results be improved?
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69. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
– What is the core of the research problem addressed in the
paper?
– Are there some alternative approaches to address the
research problem?
– Are there some good arguments to be made against the
assumptions/approach taken by the authors?
– How can the research results be improved?
– Can the research results be applied to another context?
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70. What to Take Away from a Paper after
Reading
• Once you have read a paper in depth, try to answer
the following questions to yourself:
– What is the core of the research problem addressed in the
paper?
– Are there some alternative approaches to address the
research problem?
– Are there some good arguments to be made against the
assumptions/approach taken by the authors?
– How can the research results be improved?
– Can the research results be applied to another context?
– Are there some gaps in the work?
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81. Forming a Hypothesis/Algorithm
Outline
• Develop an outline of your solution
– If possible, work through simple scenarios
• Think about complexity. Is your solution going to
scale well?
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82. Forming a Hypothesis/Algorithm
Outline
• Develop an outline of your solution
– If possible, work through simple scenarios
• Think about complexity. Is your solution going to
scale well?
• What is the chief strength of your solution?
– This will be your main selling point in your papers
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83. Forming a Hypothesis/Algorithm
Outline
• Develop an outline of your solution
– If possible, work through simple scenarios
• Think about complexity. Is your solution going to
scale well?
• What is the chief strength of your solution?
– This will be your main selling point in your papers
• Weaknesses of your solution?
– Any major weakness is likely to hinder your paper. So
avoid any major weakness by reformulating or
reworking your solution
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85. Some Pointers on Developing a
Solution
• Try to map your problem into a framework
with known approaches for solutions
– Optimization
– Graph theory
– Probabilistic
– Divide and conquer
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86. Some Pointers on Developing a
Solution
• Try to map your problem into a framework
with known approaches for solutions
– Optimization
– Graph theory
– Probabilistic
– Divide and conquer
• Strive for simplicity and avoid complex
solutions
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87. Some Pointers on Developing a
Solution
• Try to map your problem into a framework
with known approaches for solutions
– Optimization
– Graph theory
– Probabilistic
– Divide and conquer
• Strive for simplicity and avoid complex
solutions
• Sit on your solution for few days and then
come back to it
– This helps in locating weaknesses/flaws
that generally get overlooked in the
initial excitement
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90. Implementation/Simulation/Analysis
• Test your implementation/simulation with test
cases of known results to ensure there are no
bugs/mistakes
• Whenever possible, use the platform or the
environment popular in your area of research
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91. Implementation/Simulation/Analysis
• Test your implementation/simulation with test
cases of known results to ensure there are no
bugs/mistakes
• Whenever possible, use the platform or the
environment popular in your area of research
• Make sure to perform comparative study with
standard datasets or benchmarks
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93. Organizing and Interpreting Results
• It is not enough to just present the results. You must
do a careful analysis to show that the results justify
your solution
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94. Organizing and Interpreting Results
• It is not enough to just present the results. You must
do a careful analysis to show that the results justify
your solution
• If there are some parameters in your solution, then
make sure that you have results for a range of
parameter values to infer a trend
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95. Organizing and Interpreting Results
• It is not enough to just present the results. You must
do a careful analysis to show that the results justify
your solution
• If there are some parameters in your solution, then
make sure that you have results for a range of
parameter values to infer a trend
• Make sure your graphs are labeled properly. Do not
overcrowd graphs by putting too much information
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97. Writing and Communicating Results
• Select some papers from your field as model papers and use
them as guides to write your paper
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98. Writing and Communicating Results
• Select some papers from your field as model papers and use
them as guides to write your paper
• Use your own words and phrases. Use quote marks if you are
using sentences from other papers.
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99. Writing and Communicating Results
• Select some papers from your field as model papers and use
them as guides to write your paper
• Use your own words and phrases. Use quote marks if you are
using sentences from other papers.
• Go over your writing several times. Generally writing
consumes 50% of the research effort.
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100. Writing and Communicating Results
• Select some papers from your field as model papers and use
them as guides to write your paper
• Use your own words and phrases. Use quote marks if you are
using sentences from other papers.
• Go over your writing several times. Generally writing
consumes 50% of the research effort.
• Don’t worry about the length of the initial draft. Make sure
you don’t miss any point. It is much easier to trim a paper
later on to meet the length requirements.
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102. Some Useful Tips for Paper Writing
• Begin by preparing an outline of your paper by
noting down the important points you want to
cover in each section of your manuscript
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103. Some Useful Tips for Paper Writing
• Begin by preparing an outline of your paper by
noting down the important points you want to
cover in each section of your manuscript
• Remember, you are trying to “sell” your work to
reviewers who will determine the fate of your
paper. Make a compelling case in the introduction
section of your paper because by the time a
reviewer has finished this section, she has already
made an initial decision about whether to accept
or reject the paper. She will read the rest of the
paper looking for evidence to support her decision.
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104. Some Useful Tips for Paper Writing
• Begin by preparing an outline of your paper by noting down the
important points you want to cover in each section of your
manuscript
• Remember, you are trying to “sell” your work to reviewers who will
determine the fate of your paper. Make a compelling case in the
introduction section of your paper because by the time a reviewer
has finished this section, she has already made an initial decision
about whether to accept or reject the paper. She will read the rest
of the paper looking for evidence to support her decision.
• The introduction section must have:
– What is the problem? Why is it interesting and important?
Weaknesses of the previous proposed solutions? How does the
proposed solution overcomes all or some of the limitations of the
existing approaches? What are the key components of the suggested
approach and results?
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106. More Tips for Paper Writing
• Read some well-known works on writing and
communication:
– The Elements of Style (Fourth
Edition), William Strunk Jr., E.B. White, Roger
Angell, Longman.
– Handbook of Technical Writing (Ninth
Edition), Gerald J. Alred, Charles T.
Brusaw, and Walter E. Oilu, St. Martin’s Press
– Use active voice and simple, clear, direct
phrasing
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107. More Tips for Paper Writing
• Read some well-known works on writing and
communication:
– The Elements of Style (Fourth Edition), William
Strunk Jr., E.B. White, Roger Angell, Longman.
– Handbook of Technical Writing (Ninth Edition),
Gerald J. Alred, Charles T. Brusaw, and Walter E.
Oilu, St. Martin’s Press
– Use active voice and simple, clear, direct phrasing
• Avoid value judgments. Give the facts and let the
readers judge.
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108. More Tips for Paper Writing
• Read some well-known works on writing and communication:
– The Elements of Style (Fourth Edition), William Strunk Jr.,
E.B. White, Roger Angell, Longman.
– Handbook of Technical Writing (Ninth Edition), Gerald J.
Alred, Charles T. Brusaw, and Walter E. Oilu, St. Martin’s
Press
– Use active voice and simple, clear, direct phrasing
• Avoid value judgments. Give the facts and let the readers judge.
• Run a spell checker and have someone who is particular about
grammar read your paper
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109. More Tips for Paper Writing
• Read some well-known works on writing and communication:
– The Elements of Style (Fourth Edition), William Strunk Jr.,
E.B. White, Roger Angell, Longman.
– Handbook of Technical Writing (Ninth Edition), Gerald J.
Alred, Charles T. Brusaw, and Walter E. Oilu, St. Martin’s
Press
– Use active voice and simple, clear, direct phrasing
• Avoid value judgments. Give the facts and let the readers judge.
• Run a spell checker and have someone who is particular about
grammar read your paper
• Make sure to acknowledge the persons/organizations who have
helped you in your research
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112. Revising, Resubmitting, and
Publication
• A paper is rarely accepted as it is. So be prepared for one or
more revisions of your manuscript.
• The best outcome you can hope is “Accept with a minor
Revision.” Celebrate it because it is rare.
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113. Revising, Resubmitting, and
Publication
• A paper is rarely accepted as it is. So be prepared for one or
more revisions of your manuscript.
• The best outcome you can hope is “Accept with a minor
Revision.” Celebrate it because it is rare.
• Pay careful attention to the comments/suggestions of the
reviewers. Try to incorporate them as much as possible and
revise your paper for resubmission.
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114. Revising, Resubmitting, and
Publication
• A paper is rarely accepted as it is. So be prepared for one or
more revisions of your manuscript.
• The best outcome you can hope is “Accept with a minor
Revision.” Celebrate it because it is rare.
• Pay careful attention to the comments/suggestions of the
reviewers. Try to incorporate them as much as possible and
revise your paper for resubmission.
• Include a cover letter thanking the reviewers and explaining
point by point how you have accommodated most of their
concerns
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115. Revising, Resubmitting, and
Publication
• A paper is rarely accepted as it is. So be prepared for one or
more revisions of your manuscript.
• The best outcome you can hope is “Accept with a minor
Revision.” Celebrate it because it is rare.
• Pay careful attention to the comments/suggestions of the
reviewers. Try to incorporate them as much as possible and
revise your paper for resubmission.
• Include a cover letter thanking the reviewers and explaining
point by point how you have accommodated most of their
concerns
• In the event your paper is not accepted at your publication
of first choice, don’t lose heart. Browse through next tier
list of publications and submit there.
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117. Making Technical Presentations
• Three main elements of a technical
presentation
– Organization
– Visual aids
– Delivery and style
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118. Making Technical Presentations
• Three main elements of a technical
presentation
– Organization
– Visual aids
– Delivery and style
• Before you prepare your presentation
– Prepare an outline
– Think about your audience and their background
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119. Some Tips on Presentations
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120. Some Tips on Presentations
• Never read from slides or from your notes. Prepare by
practicing as many times as you can
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121. Some Tips on Presentations
• Never read from slides or from your notes. Prepare by
practicing as many times as you can
• Check out the room and the equipment beforehand
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122. Some Tips on Presentations
• Never read from slides or from your notes. Prepare by
practicing as many times as you can
• Check out the room and the equipment beforehand
• Be confident. Remember, you are the foremost expert on your
own research
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123. Some Tips on Presentations
• Never read from slides or from your notes. Prepare by
practicing as many times as you can
• Check out the room and the equipment beforehand
• Be confident. Remember, you are the foremost expert on your
own research
• Speak clearly and loud enough. Modulate your voice
Look at your audience and make eye contact.
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124. Some Tips on Presentations
• Never read from slides or from your notes. Prepare by
practicing as many times as you can
• Check out the room and the equipment beforehand
• Be confident. Remember, you are the foremost expert on your
own research
• Speak clearly and loud enough. Modulate your voice
Look at your audience and make eye contact.
• Watch for audience’s non-verbal feedback and adjust your
delivery
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125. Some Tips on Presentations
• Never read from slides or from your notes. Prepare by
practicing as many times as you can
• Check out the room and the equipment beforehand
• Be confident. Remember, you are the foremost expert on your
own research
• Speak clearly and loud enough. Modulate your voice
Look at your audience and make eye contact.
• Watch for audience’s non-verbal feedback and adjust your
delivery
• Always carry a backup presentation file on a USB or through
email/cloud
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128. Writing Grant Proposals
• Choose a problem/idea you wish
to pursue
• Prepare a brief concept paper
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129. Writing Grant Proposals
• Choose a problem/idea you wish to
pursue
• Prepare a brief concept paper
• Identify the potential funding
sources
– NSF/NIH/DOE/DHS
– Foundations and industry consortia, e.g.
EPRI
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130. Writing Grant Proposals
• Choose a problem/idea you wish to
pursue
• Prepare a brief concept paper
• Identify the potential funding sources
– NSF/NIH/DOE/DHS
– Foundations and industry consortia, e.g.
EPRI
• Contact the program officers and discuss
your idea with them
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132. What Should be in a Proposal?
• It should answer the following questions:
– What are you going to do?
– Why is it important to do?
– Novelty of your approach and expected contributions
– Your unique qualifications to do the project
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133. What Should be in a Proposal?
• It should answer the following questions:
– What are you going to do?
– Why is it important to do?
– Novelty of your approach and expected contributions
– Your unique qualifications to do the project
• Most funding agencies have templates for different
kinds of proposals, follow the pertinent template
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134. What Should be in a Proposal?
• It should answer the following questions:
– What are you going to do?
– Why is it important to do?
– Novelty of your approach and expected contributions
– Your unique qualifications to do the project
• Most funding agencies have templates for different
kinds of proposals, follow the pertinent template
• Stay within the page limits and strictly follow the
guidelines for submission
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135. What Should be in a Proposal?
• It should answer the following questions:
– What are you going to do?
– Why is it important to do?
– Novelty of your approach and expected contributions
– Your unique qualifications to do the project
• Most funding agencies have templates for different
kinds of proposals, follow the pertinent template
• Stay within the page limits and strictly follow the
guidelines for submission
• Seek help from your sponsored research office for
preparing budget
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137. Ethics in CS Research
• Authorship and the order of listing
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138. Ethics in CS Research
• Authorship and the order of listing
• Plagiarism
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139. Ethics in CS Research
• Authorship and the order of listing
• Plagiarism
• Multiple submissions
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140. Ethics in CS Research
• Authorship and the order of listing
• Plagiarism
• Multiple submissions
• Data fudging and fabrication
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141. Ethics in CS Research
• Authorship and the order of listing
• Plagiarism
• Multiple submissions
• Data fudging and fabrication
• Conflict of interest
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143. Authorship and Listing Order
• Each person listed as an author should have
made direct and substantial contribution to
the work. All listed authors must be prepared
to accept full responsibility for the content of
the research article.
–David Baltimore (Nobel laureate) case
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144. Authorship and Listing Order
• Each person listed as an author should have made direct
and substantial contribution to the work. All listed authors
must be prepared to accept full responsibility for the
content of the research article.
– David Baltimore (Nobel laureate) case
• Ordering conventions are discipline/culture specific
– In CS, the ordering generally indicates the relative
contributions of different authors with the first author
having made the most contribution
– In mathematics and theoretical CS research, the names
are generally listed alphabetically
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145. Authorship and Listing Order
• Each person listed as an author should have made direct and substantial
contribution to the work. All listed authors must be prepared to accept full
responsibility for the content of the research article.
– David Baltimore (Nobel laureate) case
• Ordering conventions are discipline/culture specific
– In CS, the ordering generally indicates the relative contributions of
different authors with the first author having made the most
contribution
– In mathematics and theoretical CS research, the names are generally
listed alphabetically
• Acknowledgement
– Include anyone who has made some contribution, for example in
editing, loaning an equipment, providing some financial support
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147. Plagiarism
• The American Heritage Dictionary
(2nd College Ed.) defines plagiarize
as "to take and use as one's own the
writings or ideas of another."
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148. Plagiarism
• The American Heritage Dictionary
(2nd College Ed.) defines plagiarize
as "to take and use as one's own the
writings or ideas of another."
• Always make sure you give proper
credit to your sources and any
verbatim material is used with
quotes
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149. Plagiarism
• The American Heritage Dictionary
(2nd College Ed.) defines plagiarize
as "to take and use as one's own the
writings or ideas of another."
• Always make sure you give proper
credit to your sources and any
verbatim material is used with
quotes
• See IEEE and ACM guidelines
– http://www.acm.org/publications/policies
/plagiarism_policy
http://www.ieee.org/publications_standar
ds/publications/rights/plagiarism.html
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154. Self-Plagiarism
• ACM defines it as the verbatim or near-
verbatim reuse of significant portions of one's
own copyrighted work without citing the
original source.
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155. Self-Plagiarism
• ACM defines it as the verbatim or near-verbatim
reuse of significant portions of one's own
copyrighted work without citing the original
source.
– Self-plagiarism does not apply to publications based
on the author's own previously copyrighted work
(e.g., appearing in a conference proceedings) where
an explicit reference is made to the prior publication.
Such reuse does not require quotation marks to
delineate the reused text but does require that the
source be cited.
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157. Multiple Submissions
• LPUs (Least Publishable Units) are
common although not desirable
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158. Multiple Submissions
• LPUs (Least Publishable Units) are
common although not desirable
• It is okay to have one or two
conference papers and a journal
paper on the same research topic as
long as each paper makes its own
significant contribution
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159. Multiple Submissions
• LPUs (Least Publishable Units) are
common although not desirable
• It is okay to have one or two conference
papers and a journal paper on the same
research topic as long as each paper
makes its own significant contribution
• Never submit the same work to two
places at same time to expedite
publication
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161. Data Fudging and Fabrication
• Avoid temptations to:
– Do data smoothing to remove
irregularities to make the data
appear extremely accurate and
precise
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162. Data Fudging and Fabrication
• Avoid temptations to:
– Do data smoothing to remove
irregularities to make the data
appear extremely accurate and
precise
– Retain only those results that fit
the theory and discarding others
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163. Data Fudging and Fabrication
• Avoid temptations to:
– Do data smoothing to remove
irregularities to make the data appear
extremely accurate and precise
– Retain only those results that fit the
theory and discarding others
– Create/invent some or all of the
research data to substantiate your
research
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164. Conflict of Interest
• Avoid conflict of interest
situations by proper
disclosure. Examples of
conflict of interests
situations are:
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165. Conflict of Interest
• Avoid conflict of interest
situations by proper
disclosure. Examples of
conflict of interests
situations are:
– Reviewing a paper/proposal
of a friend/company where
you have a stake
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166. Conflict of Interest
• Avoid conflict of interest
situations by proper
disclosure. Examples of
conflict of interests
situations are:
– Reviewing a paper/proposal of
a friend/company where you
have a stake
– Writing a book review
published by a friend
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167. Conflict of Interest
• Avoid conflict of interest situations
by proper disclosure. Examples of
conflict of interests situations are:
– Reviewing a paper/proposal of a
friend/company where you have a
stake
– Writing a book review published by a
friend
– Hiring your relatives on funded
projects
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