Transcript No Slide Title

HOW TO GET A PH.D.: Methods and Practical
Hints
Aarne Mämmelä 16.9.2003
VTT ELEKTRONIIKKA
HOW TO GET A PH.D.
Methods and Practical Hints
Dr. AARNE MÄMMELÄ
Research Professor (VTT), Docent (HUT)
VTT ELECTRONICS
Kaitoväylä 1, P.O. Box 1100, FIN-90571 Oulu, Finland
Email: [email protected], http://www.vtt.fi/ele
Tel. 08-5512111, 08-5512482 (direct), 040-5762963 (GSM)
Fax 08-5512320
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CONTENTS OF THE COURSE
• Lectures 16.9., 23.9., 30.9. and 7.10.
• Exam 7.11.
• lectures and M. Davis, Scientific Papers and
Presentations, Academic Press, 1997, 296 pp.
• Course work
• proposal for requirements 8.12.2003, feedback
31.12.2003
• final report 30.9.2004
• Tutor system
• details during the last lecture
• Grades: failed, passed, passed with honors
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COURSE WORK
Three alternatives according to the student’s background
as agreed individually with the student:
1) Review of the literature
2) A proposal for a Ph.D. thesis including a review of
literature
3) Scientific publication plus a proposal for a Ph.D. thesis
and a review of literature.
Final report about 10-20 pages. More detailed instructions
on the course page
(http://www.infotech.oulu.fi/GraduateSchool/ICourses/to_
phd_2003.html).
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PROGRAM
I Session 16.9.2003 at 2-5 pm
1. Aarne Mämmelä, Research Methods: From Problem and
Hypothesis to Experiments
2. Tapio Seppänen, Characteristics of a Researcher
II Session 23.9.2003 at 2-5 pm
3. Aarne Mämmelä, Literature Reviews: Existing Knowledge from
Data Bases
4. Pekka Heinonen, Industrial Experiences on Ph.D. Students
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PROGRAM
III Session 30.9.2003 at 2-5 pm
5. Erkki Oja, Experiences of a Senior Researcher
6. Olli Silven, Peer Review Process: the Task of a Referee
7. Jani Mäntyjärvi, Experiences about Preparing a Doctoral Thesis
IV Session 7.10.2003 at 2-5 pm
8. Aarne Mämmelä, Final Result: a Scientific Publication
9. Kari Leppälä, Theory of Science for Engineers
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RESEARCH METHODS:
From Problem and Hypothesis to Experiments
Idea
Literature review
Problem and
hypotheses
Experiments/
analysis
System
(prototype)
Theory/paper
(new knowledge)
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OUTLINE
•
•
•
•
•
•
Introduction
Learning process
History
Basic problems
Research methods
Conclusions
• Appendices
• References
• Bibliography
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JOURNEY OF EXPLORATION: COLUMBUS
• Problem: a new way to India, competing hypotheses: Spain and
Portugal, map, funding
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KNOWLEDGE AND LITERATURE
Researchers
Editor
Peer review
Literature (knowledge)
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EXAMPLE LANDMARK PAPER
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SOME DEFINITIONS
• Research: Careful study or investigation to discover new knowledge
 basic research (no specific application in mind)
 applied research (ideas into operational form)
• Development: Systematic use of the existing knowledge
• Note. Research and development are closely related. In research a
prototype is often developed.
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LEARNING PROCESS
How do students learn?
• Professors try to teach principles first and applications later (if
ever).
• It is easiest to start from simple examples (= induction, “words and
example sentences”).
• General principles are emphasized later to really master the
subject (= deduction, “grammar”).
• It is helpful to know at least some simple principles in the
beginning.
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HOW DOES A RESEARCHER WORK?
1. Make always notes in a notebook (day book)
2. Make plans for the future all the time (outlines, roadmaps)
3. Discuss, ask questions and argue (criticism)
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THE NEW WORLD OF MR TOMPKINS
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ANALOGIES IMPROVE CREATIVITY
LENGTH
FURNITURE (WEIGHT)
HEIGHT
REMOVAL VAN
TIME
BIT (ENERGY)
BANDWIDTH
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TIME SLOT
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COMMUNICATIONS IMPROVE CREATIVITY
Other researchers
Encouragement, criticism
YOURSELF
Landmark
Advisor
Paper
Oral communications
Written communications
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CLASSIFICATION (REDUCTIONISM) IMPROVE
CREATIVITY
STATIC OR TIMELESS ORDER (TAXONOMY)
System
Subsystem 1
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Subsystem 2
Subsystem 3
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DYNAMIC AND GENERATIVE ORDER
DYNAMIC ORDER (REDUCTIONISM)
Subsystem 1
Subsystem 2
Subsystem 3
GENERATIVE ORDER (HOLISM)
Subsystem 2
Subsystem 1
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Subsystem 3
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BIG ISSUES GUIDING OUR WORK
Systems
engineering
History &
roadmaps
Fundamental
limits
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System models,
relationships,
complexity analysis
Reviews of literature
Physical limits,
optimal systems,
performance analysis
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RESEARCH IDEAS
To find research ideas, use your own intuition/expertise and..
• know the literature, especially original landmark papers (write brief wellorganized summaries)
• do experiments early in your studies, use your colleagues’ experience
• discuss with colleagues and students and teach them (seminars)
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RESEARCH PROPOSAL
• Abstract
• Introduction
• problem and hypothesis
• Review of the literature
• good organization, concept analysis
• Materials and methods
• system requirements, system specifications
• plan for operation, experimental procedures
• analytical and other tools
• Results
• results (for example experimental data) to be expected
• publication and other dissemination of research results
• Discussion and conclusions
• originality, open questions, limitations
• validation, significance, applications
• Time frame, budget
• intermediate objectives
• Bibliography
• list of references
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TIMING OF DOCTORAL THESIS (4 years)
1. Proposal
2. Courses
3. Literature
4. Experiments
5. Reports
6. Papers
7. Thesis
8. Defence
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EXAMPLE: HISTORY OF TELECOMMUNICATIONS
Telegraph
Telephone
Wireless telegraph
Broadcast
Wireless voice
1860
1880
1900
Computers
1920
Computer networks
WLAN
Mobile radio
1940
Mobile cellular
Satellite comms
Radar
1940
Internet
Voiceband modems
Fixed links
Police radio
Satellite navigation
Optical comms
1960
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1980
2000
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FUTURE CELLULAR SYSTEM
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ROADMAP AND VISION OF TELECOMMUNICATIONS (1)
Ad hoc networks
WPAN
Digital broadcast
Mobile DVB
Multicast/unicast
Wireless Internet
Mobile universal
Mobile Internet
Satellite positioning
FWA
Supermacrocells
Mobile 3D voice
Megacells
Multi-sense interaction True virtual reality
Haptic interaction
3D telepresence
Mobile wide-screen
2000
2010
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2020
2030
2040
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ROADMAP AND VISION OF TELECOMMUNICATIONS (2)
Telesocializing?
Worm holes?
Telepathy?
ANSIBLE?
Quantum comms?
Direct MMI?
3000
Intergalactic network?
Teleportation?
Nanobots?
4000
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Time machines?
Holodeck?
5000
Real-time Internet?
6000
7000
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SOME FUNDAMENTAL ENGINEERING PROBLEMS
Sun
Information
Energy
Energy
Nature
Materials
Energy
Information
Products/
Factory
Services
Waste
Waste
People
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People
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FUNDAMENTAL PROBLEMS IN INFORMATION ENGINEERING
Energy
Information
Save/
Display
Distribution
Storage
Processing
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TECHNOLOGY: NATURAL SCIENCE AND ENGINEERING
Technosystem
Ecosystem
Human beings
Society
Organic nature
Humanities
Social science
Energy
Science
Materials/laws
Products/
services
Inorganic nature
Engineering
Waste
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BASIC TYPES OF RESEARCH METHODS
• Observation (Aristotle)
• environment is observed and conclusions are made
• modern use in literature reviews and for example in astronomy
• Analysis or hypothetico-deductive method (Platon, Eucleides)
• a hypothesis (i.e., a conjecture) is made, deduction (i.e., analysis) is
used to find special cases which can be better understood or directly
tested in the experimental method
• in an axiomatic system axioms or postulates are used to deduce
theorems
• Experimental method (Francis Bacon, Galilei, Descartes, Newton):
• the problem is reduced into smaller problems, experiments are made
and induction is used for generalization to find a theory
• most common method in science and engineering when combined
with analysis
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EXPERIMENTS (1)
Analysis
Simulation
Prototype
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EXPERIMENTS (2)
• Mathematical analysis (presentation of formal theory)
• creates best scientific papers
• simple, mathematically tractable problem, must be often linear
(numerical results needed)
• Simulations (empirical research)
• complicated systems can be developed rapidly, but slow to
simulate
• basic idea: lower level blocks are simplified and idealized
(hierarchy)
• key problem: realistic models for the environment (e.g.
channel)
• Prototyping (empirical research)
• more convincing than “pure” simulations, not so flexible, slow
and expensive to develop complicated systems
• environment (channel) simulators still needed
(approximations!), field tests expensive, repeatability?
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LEGENDS (SEE NEXT PAGES)
Analysis
Special
Pyramid
Synthesis
General
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ANALYSIS AND SYNTHESIS
Simple
pendulum
System
- prototype
Analysis
Wire
Synthesis
Parts
- materials
Mass point
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REASONING: INDUCTION AND DEDUCTION
Experimental
l
T
Examples
- statistics
Induction
Theory/law
- knowledge
T
x
x x
x
x
Theoretical
l
Deduction
Assumptions:
- small amplitude
- no friction
Definitions:
g is gravitational
acceleration (9.81 m/s2)
Theory:
T = 2p l / g
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RESEARCH METHODS: GENERAL
T
l
Pendulum
T
x
x x
x x
l
Experiments
System
Examples
Induction
Synthesis
Analysis
Relationships
Parts
Deduction
Theory
T = 2p l / g
Wire
Mass point
Analysis
Special
Synthesis
General
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HOW A SCIENTIST WORKS
Problem:
Explain an object in
nature
Experimental results
Experiments
System
Examples
Induction
Synthesis
Analysis
Parts
Elements
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Relationships
Experience,
analogies
Deduction
Theory
Hypothesis:
Law
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HOW AN ENGINEERING SCIENTIST WORKS
Hypothesis:
Prototype
Experience,
analogies
Problem:
System requirements
System specifications
Experiments
System
Examples
Induction
Synthesis
Analysis
Parts
Components
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Relationships
Experience,
analogies
Deduction
Theory
Hypothesis:
System model
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GENERAL HINTS
• always start from simple models (= induction, “example sentences”)
• use idealizations, black boxes
• example: first scalars instead of matrices
• reduce idealizations step by step
• integrate the ideas into a system model (= deduction, “grammar”)
• consider optimal systems and their approximations
• compare to fundamental limits
• good organization
• block diagrams, graphical examples, hierarchy, modularity,
etc.
• try to find independent (orthogonal) blocks!
• careful testing & documentation (reports, comment lines, etc.)
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HOMEWORK PROBLEMS
• Draw a diagram about the history of engineering (start from wheel,
more detailed diagram since steam engine)
• Draw a diagram about the history of electronics (start from the
electronic tubes)
• Draw a diagram about the history of storage (hint: start from the
invention of writing)
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CONCLUSIONS: RESEARCH PROPOSAL
Abstract
Introduction
• problem and hypothesis
Review of the literature
Materials and methods
Results
Discussion and conclusions
Time frame, budget
Bibliography
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CONCLUSIONS: IMPORTANT TRADE-OFFS
Criticism
Details
Systematic
work
Encouragement
History &
Systems
roadmaps
Creativity
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APPENDICES
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COMMENTS TO ROADMAP AND VISION
• direct MMI refers to a direct wired interface to human brains
• haptic interaction refers to the sense of touch, multi-sense interaction refers to
all the five senses
• holodeck refers to telepresence and virtual reality combined: all involved are in
a virtual environment
• nanobot is a small robot moving in human brains and controlled wirelessly, it
makes wireless direct MMI possible
• telepresence refers to presence in an existing environment for example as a
hologram; it does not need glasses, but it needs a material (for example water
vapor) to which the hologram is projected
• teleportation: the theoretical portation of matter through space by converting it
into energy and then reconverting it at the terminal point
• virtual reality: computer-generated simulation of three-dimensional images of
environment or sequence of events that someone using special equipment
(glasses, dress) may view and interact with a seemingly physical way
• worm hole: a hypothetical space-time tunnel or channel connecting a black
hole with another universe
• quantum communications refers to teleportation of quantum states
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ABBREVIATIONS
•
•
•
•
•
•
•
•
•
•
•
•
•
ANSIBLE = instant delivery of information
BLAST = Bell Labs adaptive space time
DVB = digital video broadcasting
FWA = fixed wireless access
MRC = maximal ratio combining
OFDM = orthogonal frequency division multiplexing
MIMO = multiple input multiple output
MMI = man-machine interface
STC = space-time coding
TCM = trellis-coded modulation
UWB = ultra wideband
WPAN = wireless personal area network
WLAN = wireless local area network
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RESEARCHER AND ORGANIZATION
ROLE OF ORGANIZATION
ROLE OF RESEARCHER
1. History and state of the art
Id ea
2. Vision and roadmap
3. Fundamental principles and
problems
4. Research problems and projects
L iteratu re review
P ro blem an d
h y p o th eses
5. Marketing, recruiting, investing
6. Project plans
7. Research culture and education
E x p erim en ts/
an aly sis
S y stem
(p ro to ty p e)
T h eo ry /p ap er
(n ew k n o w led ge)
8. Integration of results
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SCIENCE
• Science: knowledge ascertained by observation and experiment, critically
tested, systematized, and brought under general principles; a branch of
such knowledge; natural science, systematized knowledge of nature and
the physical world
• Scientific method: a method of research in which a hypothesis is tested
by means of a carefully documented control experiment that can be
repeated by any other researcher
• Information: facts told, heard or discovered about something or
somebody, for example news
• Knowledge: an organized body of information accumulated by mankind or
shared by people in a particular field
• Data: information prepared for or stored by a computer (plural form of
datum, a single piece of information; the word data now usually used with
a singular verb)
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CLASSIFICATION OF SCIENCES
Applied science
(practical)
Ÿ engineering
Ÿ medicine
Ÿ agriculture
Science
(natural world)
Ÿ physics
Ÿ chemistry
Ÿ biology
Formal science
Ÿ mathematics
Ÿ logic
Humanities
(human culture)
Ÿ linguistics (languages)
Ÿ history
Ÿ philosophy
Ÿ art (literature, etc.)
Social science (people within society)
Ÿ anthropology
Ÿ psychology
Ÿ sociology
Ÿ pedagogics
Ÿ economics
Ÿ jurisprudence (science of law)
Ÿ political science
Note. Natural science is usually referred to as “science.”
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CLASSIFICATION OF ENGINEERING
• Technology: the scientific study and use of applied sciences, for example
engineering; application of this to practical tasks in industry
• Engineering: practical application of science and mathematics, as in the
design and construction of machines, vehicles, structures, roads, and
systems
• Industrial engineering
• Civil engineering
• Mechanical engineering
• Chemical engineering
• Electrical engineering: practical application of the theory of
electricity to the construction of machinery, power supplies, etc.
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CLASSIFICATION OF ENGINEERING
• Information engineering: the study or use of electronic equipment,
especially computers, for storing, analyzing, and distributing information of
all kinds, including words, numbers and pictures
• Telecommunications: transmitting information, as words, sounds, or
images, over great distances, in the form of electromagnetic signals
• Electronics: development and application of of devices and systems
involving the flow of electrons in a vacuum, in gaseous media, and in
semiconductors
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HUMANITIES (EXAMPLES)
• Philosophy: general principles of a field of knowledge, divided into
• metaphysics: study of first principles, inc. (i) ontology: nature of
existence and (ii) cosmology: origin and general structure of the
universe
• epistemology or theory of knowledge: origin, nature, methods and
limits of human knowledge, inc. (i) logic: correct or reliable reasoning
and (ii) philosophy of science or theory of science
• axiology or value theory: inc. i) ethics: moral principles, ii)
aesthetics: taste and study of the beauty in nature and art, iii) religion:
the cause, nature and purpose of the universe
• History: study of past events; acts, ideas, or events that will or can shape
the course of the future
• Language: human speech or the written symbols for speech; any set or
system of formalized symbols, signs, sounds, or gestures used or
conceived as a means of communication
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MATHEMATICS
• Mathematics: science dealing with quantities and forms and their
relationships by the use of numbers and symbols
• arithmetic and number theory: theory of numbers
• algebra: generalization and extension of arithmetic, deals with
general statements of relations (most often referred to as functions),
utilizing letters and other symbols to represent quantities in the
description of such relations
• (mathematical) statistics: collecting, classifying and analyzing
information shown in numbers
• trigonometry: relations between the sides and angles of triangles
• analysis: generalization and extension of algebra, study of the
changes of a continuously varying function, differential and integral
calculus and its higher developments, discussion of a problem by
algebra, as opposed to geometry
• geometry: deduction of properties, measurements and relationships
of points, lines, angles, surfaces and figures in space by certain
assumed properties of space
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CLASSIFICATION OF SCIENCES
• Physics: study of matter and energy and the relationships between them
• Chemistry: study of properties of substances both elementary and
compound, and the laws of their combination and action one upon another
• Biology: study of the life and structure of plants and animals
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WHOLE AND ELEMENTS: ANALYSIS AND SYNTHESIS
• analysis: resolving or separating a whole into its elements or component
parts
• synthesis: opposite to analysis, the process of making a whole by putting
together its separate component parts
• reductionism (Descartes): theory that every complex phenomenon can
be explained by analyzing the simplest, most basic physical mechanisms
that are in operation during the phenomenon (in science and engineering
problems are reduced into smaller problems that are studied separately,
see systems analysis)
• holism: opposite to reductionism, theory that whole entities, as
fundamental components of reality, have an existence other than as a
mere sum of their parts (see emergence)
• emergence: property of a whole that cannot even in principle be
explained from the knowledge of the parts and their relationships (it is a
philosophical question whether emergence exists or not for example in
biological systems if all parts and relationships are known)
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SYSTEMS ANALYSIS AND ENGINEERING
• system: a set or arrangement of things so related or connected as to form
a unity or organic whole.
• systems analysis: an engineering technique that breaks down complex
technical, social, etc. problems into basic elements whose interrelations
are evaluated and programmed, with the aid of mathematics, into a
complete and integrated system.
• systems engineering: a branch of engineering using esp. information
theory, computer science, and facts from systems-analysis studies to
design integrated operational systems for specific complexes.
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REASONING: INDUCTION AND DEDUCTION
• induction (scientific induction, Aristotle, Francis Bacon): reasoning from
particular cases to general conclusions
• Bacon’s induction is incomplete and does not necessarily keep the
truth since new information is introduced and some unexpected
phenomena may emerge (Fermat’s complete induction (based on
positive integers) is used in “watertight” mathematical proofs)
• different forms of induction: intuitive, enumerative, eliminative, direct
inference, inverse deduction and analogy (Niiniluoto, 1983)
• in (intertheoretical) reduction the laws of the reduced theory are
derived from that of the reducing theory, for example, Newton’s
mechanics can be reduced to Einstein’s theory of relativity
• deduction (Platon, Eucleides): drawing of a particular truth from a general
truth (opposite to induction and reduction)
• deduction keeps the truth: no new information is introduced, but the
information is revealed with examples
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CREATIVITY: ORDER AND CHAOS
• Creativity is easily lost
• fragmentation and specialization due to reductionism: language
difficulties due to special terminology (new terms formed from
abbreviations)
• paradigms
• Creativity can be improved by
• systems analysis
• interrelations between parts (subsystems) considered in detail
• communications:
• use different reasoning methods: induction, deduction, intuition
• analogies or metaphors form a bridge between different
concepts, for example Newton: apple = moon, Einstein: time =
space, energy = mass
• contrasts, extremes, symmetries, relationships
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HOW TO IMPROVE CREATIVITY
• Generation of ideas
• brainstorming (unrestrained offering of ideas)
• morphological analysis (systematic search for solutions)
• ready-made question lists
• synectics (association, connection between ideas)
• subconscious (“incubation”)
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SYSTEMS ANALYSIS AND ENGINEERING
Analysis, experiments, discussions
Induction, deduction, intuition (analogies)
Systems
Literature:
reviews,
landmarks,
state-of-the art
History
Elements
Vision,
roadmap
Complexity analysis,
energy, size/weight, cost
Concept analysis,
requirements (QoS),
specifications, block
diagrams, hierarchy,
modularity, interfaces,
interrelationships, trade-offs
Fundamental limits,
optimal systems
QoS = Quality of Service
Telecommunication theory, telecommunication electronics
Estimation, information theory, digital electronics, computers
Signals & systems, digital signal processing
Physics, chemistry and biology
Languages, philosophy (theory of science), mathematics
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ALTERNATE TERMINOLOGY
Complexity, case, constraint,
experimental result, measurement
result, particular case, performance,
phenomenon, quality of service,
sample, specification, statistics,
theorem.
Classification, instance, practice,
procedure, process, product,
prototype, service, structure,
organization, taxonomy, whole.
Experiments
System
Examples
Induction
Synthesis
Analysis
Parts
Relationships
Atom, component, consituent, element,
factor, fraction, fragment, ingredient,
material, member, module, particle,
piece, section, segment, unit.
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Deduction
Theory
Abstraction, assumption, axiom,
concept, conjecture, criterion,
definition, explanation, hypothesis,
knowledge, law, logic, paradigm,
philosophy, postulate, premise,
principle, rule, system model, term
(primitive term), thesis, understanding.
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TYPES OF ORDER (CLASSIFICATION)
• static order (timeless order, separate related groups based on some
factor common to each, hierarchical structure, special cases, for
example taxonomy in biology) - Aristotle, Linné
• dynamic order (sequential order, time included, causality,
integration and disintegration, for example ”waterfall” model in
engineering, how a building is built, repaired and finally destroyed,
evolution theory in biology) - Descartes, Newton, Darwin
• generative order (holistic order, more general than static and
dynamic order, time does not have priority, internal interrelations
or dynamics included, for example iterations) - Bohm
• Example. An object floating on a river as a function of time (=
dynamic order), the whole river seen simultaneously, inc. two way
flow in loops (= generative order).
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FUNDAMENTAL LIMITS
Some of the most important fundamental limits (about 1850-1950)
• second law of thermodynamics (Carnot, Clausius)
• absolute zero (Kelvin)
• upper velocity limit (Einstein)
• uncertainty principle (Heisenberg)
• incompleteness theorem (Goedel)
• speed of transmission of intelligence (Nyquist)
• channel coding theorem (Shannon)
Refs.
• Lars Lundheim, “On Shannon and ‘Shannon's Formula’,”
Telektronikk, vol. 98, no. 1-2002, pp. 20-29.
• http://scienceworld.wolfram.com/
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CULTURAL HISTORY
1636
USA
Mayas
Letters
Hieroclyphics
Egypt -1500
-3000
Greek alphabet
Latin letters (-500)
Etruscans 300
-800 -600
Phoenicians
Semites
Greece
Macedonia
300
Europe
Europe
529
Rome
Babylon
900
Rome
1088
1100
Alexandria
415
Arabia
Sumerians
-3200
-2000
Cuneiform writing
-538
-500
1123
India
Numbers (500-876)
China
1200
1280
-1500
Japan
500
-3000
-2000
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1620
1632
1637
-1000
1
1877
1000
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LEGENDS (SEE PREVIOUS PAGE)
Start of ancient science (Thales)
Start of Greek writing
End of ancient science
(Academy closed)
-800 -600
Greece Rome
Influence
(writing)
Influence
(other)
Europe
Europe
529
1088
1620
First university
(Bologna) 1632
1637
1100
Indian-Arabian numbers
to Europe
Arabia
622
Start of modern science
(Bacon, Galilei, Descartes)
1123
Arabian calendar Omar Khayyam dies
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WHY ARE SOME DESIGN PROBLEMS DIFFICULT TO
SOLVE?
• no single evaluation function or optimization criterion that describes the
quality of any proposed solution is available, but a set of evaluation
functions (= requirements specifications) that should be weighted
• the number of solutions in the search space is so large as to forbid an
exhaustive search for the best answer and the iterative methods (by trial
and error) are too slow or unreliable to find the optimum solution
• the possible solutions are so heavily constrained that constructing even
one feasible answer is difficult (reduction is used to simplify the problem
and this adds an additional constraint)
• the evaluation function is noisy or varies with time (need an entire series of
solutions)
• our models may be too simplified so that any result is essentially useless
• some psychological barrier prevents us from discovering a solution
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PROPERTIES OF A GOOD SYSTEM
• good performance
• low complexity (= low energy consumption, size/weight, cost)
• efficient use of existing parts
• modularity and hierarchy with different criteria
• adaptivity and selfremediable
• reconfigurability and flexibility for evolutionary changes
• robustness (parameters may be changed)
• testability
• reasonable redundancy (no breakdown)
• good documentation
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HOW TO START
1. Find a suitable advisor and a good group.
2. Look for a good idea, study literature & discuss, do not reinvent
the wheel.
3. Define the problem, limit the scope, find the right approach and
hypotheses (= possible solutions), write a research proposal.
4. Analyze the system, make experiments (simulations, prototypes)
and discuss the results, use right tools.
5. Write a paper or thesis and listen carefully to comments and be
prepared to argue and defend your claims (opponents try to find
weak points in your reasoning!).
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Advisor is your best friend
Look for a good advisor
• Be there for the length of your project
• Experience on research in the same area (a doctor)
• Pedagogical skills, know the big picture, know literature
• Respected by colleagues, critical, tough methodologist
• Interested in your topic, gives comments, you respect
him/her
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How to keep your advisor?
• Orient your advisor (system model, block diagrams, table
of contents)
• Follow instructions (make notes), but also discuss and
argue
• Make concise progress reports (organize the material,
limit the scope)
• Do not expect ready-made solutions, but ways of thinking
• Advisor needs also credit for his/her work in the form of
publications
• Get into the driver’s seat!
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Why is research important?
• New knowledge is discovered
• Prestige for yourself and for your employer
• Know the state of the art and teach it to your colleagues and customers
• Know the history and see the trends
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Why is research exciting?
•
•
•
•
•
Intellectual pleasure: you learn to know something very deeply.
Thrill: you work like a detective when looking for existing knowledge.
New knowledge: you discover something that did not exist previously.
Prestige: you will become a doctor and an internationally known expert.
Spirit of the scientific community: special research culture, freedom to
think, suspect and criticize authorities, impersonal judgments of
discoveries, integrity (= honesty).
• Unique communication network: you meet the most intelligent people in
the world in your field.
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What a doctoral student should learn?
• Excellent oral and written knowledge of native language and English.
• Know the literature of a specific topic (big picture, history, state of the art,
future trends or roadmaps).
• Know how to discover new knowledge (research methods, theory of
science).
• Publish some original papers and write a thesis (contribution to the
literature).
• Learn to discuss and argue in seminars (public defence).
• Guide master’s students (social and pedagogical skills).
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CURRICULUM VITAE
•
•
•
•
•
•
•
•
•
•
•
•
•
Full names
Date and place of birth
Nationality
Marital status
Address, telephone
Education and training
Present position
Fields of research
Previous professional appointments
Research awards, honours and major grants
Editorial board memberships
Memberships in scientific societies
Other academic and professional merits and activities
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IEEE CODE OF ETHICS (www.ieee.org)
We, the members of the IEEE, in recognition of the importance of our technologies in
affecting the quality of life throughout the world, and in accepting a personal
obligation to our profession, its members and the communities we serve, do hereby
commit ourselves to the highest ethical and professional conduct and agree:
1. to accept responsibility in making engineering decisions consistent with the
safety, health and welfare of the public, and to disclose promptly factors that
might endanger the public or the environment;
2. to avoid real or perceived conflicts of interest whenever possible, and to
disclose them to affected parties when they do exist;
3. to be honest and realistic in stating claims or estimates based on available
data;
4. to reject bribery in all its forms;
5. to improve the understanding of technology, its appropriate application, and
potential consequences;
6. to maintain and improve our technical competence and to undertake
technological tasks for others only if qualified by training or experience, or
after full disclosure of pertinent limitations;
7. to seek, accept, and offer honest criticism of technical work, to acknowledge
and correct errors, and to credit properly the contributions of others;
8. to treat fairly all persons regardless of such factors as race, religion, gender,
disability, age, or national origin;
9. to avoid injuring others, their property, reputation, or employment by false or
malicious action;
10. to assist colleagues and co-workers in their professional development and to
support them in following this code of ethics.
Approved by the IEEE Board of Directors, August 1990
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REFERENCES (1)
• M. Davis, Scientific Papers and Presentations. Academic Press, 1997.
• D. Bohm and F. D. Beat, Science, Order and Creativity. Bantam Books,
1987.
• W. Benis and P. Bierderman, Organizing Genius: The Secrets of Creative
Collaboration. Addison Wesley, 1998.
• E. O. Wilson, Consilience: The Unity of Knowledge. Random House, 1999.
• I. Niiniluoto, Johdatus tieteenfilosofiaan: Käsitteen- ja teorianmuodostus,
3rd ed. Otava, 2002.
• I. Niiniluoto, Tieteellinen päättely ja selittäminen. Otava, 1983.
• R. N. Kostoff, “Science and Technology Roadmaps,” IEEE Transactions on
Engineering Management, vol. 48, pp. 132-143, May 2001.
• R. M. Felder, L.K. Silverman, “Learning and Teaching Styles in Engineering
Education,” Engineering Education, pp. 674-681, April 1988.
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REFERENCES (2)
• S. Haykin, Communication Systems. 4th ed. Wiley, 2001.
• J. G. Proakis, Digital Communications. 4th ed. McGraw-Hill, 2001.
• George Gamow and Russell Stannard, The New World of Mr Tompkins. Cambridge
Univ Press, 1999.
• Carl B. Boyer, A History of Mathematics. Wiley, 2nd revision edition, 1991.
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BIBLIOGRAPHY (1)
(Note. You can look at the table of contents, some additional excerpts, and
editorial and customer reviews at www.bn.com (inc. 8 million books) or
www.amazon.com (inc. 3 million books). For price comparisons, see
www.addall.com. There is also a more extensive list of Internet book
stores.)
History of electronics
• G. W. A. Dummer and E. Davies, Electronic Inventions and Discoveries:
Electronics from Its Earliest Beginnings to the Present Day, 4th ed. Institute
of Physics Pub, 1997, 284 pp.
• W. A. Atherton, From Compass to Computer: A History of Electrical and
Electronics Engineering. San Francisco Press, 1984.
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BIBLIOGRAPHY (2)
History of telecommunications
• Anton Huurdeman, The Worldwide History of Telecommunications. Wiley,
July 2003, 625 pp.
• John Bray, Innovation and the Communications Revolution. IEE, 2002, 336
pp. (A history of telecommunications.)
• Janet Abbate, Inventing the Internet. MIT Press, 2000, 272 pp.
• Christos J. P. Moschovitis, Hilary Poole, Tami Schuyler, and Theresa M.
Senft, History of the Internet: A Chronology, 1843 to the Present. ABC-CLIO,
1999, 312 pp.
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BIBLIOGRAPHY (3)
History of computers
• Georges Ifrah, The Universal History of Computing: From Abacus to the
Quantum Computer. Wiley, 2000, 356 pp.
• Martin Davis, The Universal Computer: The Road from Leibniz to Turing.
W.W. Norton & Company, 2000, 256 pp.
• Paul E. Ceruzzi, A History of Modern Computing. MIT Press, 1998, 408 pp.
• Michael R. Williams, A History of Computing Technology, 2nd ed. WileyIEEE Press, 1997, 440 pp.
• John A. N. Lee, Computer Pioneers. Wiley-IEEE Press, 1995, 816 pp.
• Stan Augarten, Bit by Bit: An Illustrated History of Computers. Houghton
Mifflin Co, 1984, 324 pp.
• Herman H. Goldstine, The Computer: From Pascal to Von Neumann.
Princeton Univ Press, 1972 (reprint 1993), 378 pp.
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BIBLIOGRAPHY (4)
History of science
• Mary Jo Nye (Editor), The Cambridge History of Science: Volume 5, The
Modern Physical and Mathematical Sciences. Cambridge University Press,
2002, 708 pp.
• William H. Cropper, Great Physicists: The Life and Times of Leading
Physicists from Galileo to Hawking. Oxford University Press, 2001, 514 pp.
• Herbert Butterfield, Origins of Modern Science, revised ed. Free Press, 1997,
255 pp.
History of mathematics
• Jeff Suzuki, A History of Mathematics. Prentice Hall, 2002, 832 pp.
• David M. Burton, The History of Mathematics. McGraw Hill College Div,
2002, 752 pp.
• Carl B. Boyer, A History of Mathematics. John Wiley & Sons, 2nd revision
edition, 1991, 736 pp.
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BIBLIOGRAPHY (5)
Fundamental problems (fundamental limits)
• Special Issue on “Limits of Semiconductor Technology.” Proceedings of the
IEEE, vol. 89, March 2001.
• Special Issue on “Fundamental limits in Electrical Engineering.”
Proceedings of the IEEE, vol. 69, February 1981.
• A. K. Dewdney, Beyond Reason: Eight Great Problems that Reveal the Limits
of Science. John Wiley & Sons, January 2004, 240 pp.
• Arthur W. Wiggins and Charles M. Wynn, The Five Biggest Unsolved
Problems in Science. John Wiley & Sons, August 2003, 208 pp.
• John Royden Maddox, What Remains to Be Discovered: Mapping the Secrets
of the Universe, the Origins of Life, and the Future of the Human Race.
Touchstone Books, 1999, 448 pp.
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BIBLIOGRAPHY (6)
Research methods, general
• John Losee, A Historical Introduction to the Philosophy of Science, 4th ed.
Oxford Univ Press, 2001, 314 pp.
• Alexander Rosenberg, The Philosophy of Science: A Contemporary
Introduction. Routledge, 2000, 208 pp.
• Jeffrey C. Leon, Science and Philosophy in the West. Prentice Hall, 1998,
330 pp.
• Barry Gower, Scientific Method: A Historical and Philosophical Introduction.
Routledge, 1997, 288 pp.
• Hugh G. Gauch Jr., Scientific Method in Practice. Cambridge Univ Pr, 2002,
448 pp.
• Ernest O. Doebelin, Engineering Experimentation: Planning, Execution,
Reporting. McGraw-Hill Companies, 1995, 464 pp.
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BIBLIOGRAPHY (7)
Literature reviews
• Robert I. Bergman, Find It Fast: How to Uncover Expert Information on Any
Subject, 5th ed. HarperResource, 2000, 400 pp.
• Chris Hart, Doing a Literature Review: Releasing the Social Science Research
Imagination. Corwin Press, 1999, 230 pp.
Writing instructions, general
• Judith S. Van Alstyne and Merrill D. Tritt, Professional and Technical
Writing Strategies: Communicating in Technology and Science, 5th ed.
Prentice Hall, 2001, 706 pp.
• Elaine P. Maimon and Janice H. Peritz, A Writer's Resource: A Handbook for
Writers and Researchers. McGraw-Hill, 2002, 576 pp.
• James G. Paradis and Muriel L. Zimmerman, The MIT Guide to Science and
Engineering Communication, 2nd ed. MIT Press, 2002, 334 pp.
• Alan G. Gross, Joseph E. Harmon, and Michael S. Reidy, Communicating
Science: The Scientific Article from the 17th Century to the Present. Oxford
University Press, 2002, 280 pp.
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BIBLIOGRAPHY (8)
Dictionaries
• Michael Agnes and David B. Guralnik (Editors-in-Chief), Webster’s New
World College Dictionary, 4th ed. John Wiley & Sons, 2000, 1744 pp. (ISBN
0028631196). (A dictionary of American English, includes 163000 entries,
recommended by Prentice-Hall.)
• Merriam-Webster’s Collegiate Dictionary, 11th ed. Merriam-Webster, 2003,
1664 pp. (ISBN 0877798095). (A dictionary of American English, includes
225000 definitions, recommended by Wiley, available also at www.mw.com, note that you can also listen to the pronunciation.)
• Webster’s Third New International Dictionary, Unabridged, 3rd ed. MerriamWebster, 2003, 2783 pp. (ISBN 0877793026). (A dictionary of American
English, available with a CD-ROM, recommended by Wiley, includes
472000 entries.)
• A. S. Hornby and Sally Wehmeier (Editors), Oxford Advanced Learner’s
Dictionary of Current English, 6th ed. Oxford Univ Press, 2000, 1539 pp. (A
dictionary of British English, available also at www.oup.com/elt/oald.)
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BIBLIOGRAPHY (9)
Other style guides
• Marjorie E. Skillin and Robert Malcolm Gay, Words into Type, 3rd ed.
Prentice Hall, 1974, 547 pp. (ISBN 0139642625). (Includes for example the
English grammar, recommended by Prentice-Hall and Wiley.)
• William Strunk, Jr. and E. B. White, Elements of Style, 4th ed. Macmillan,
1999, 105 pp. (Recommended by Wiley, included on page
www.bartleby.com/141.)
• Ellen Swanson, Mathematics into Type, updated edition. American
Mathematical Society, 1999, 98 pp. (Recommended by Prentice-Hall and
Wiley, explains how mathematical equations should be typed.)
• Chicago Manual of Style, 14th ed. Univ Chicago Press, 1993, 921 pp.
(Instructions for preparation of books, recommended by Prentice-Hall.)
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