How to Stand out at Conferences
Short version
Martina Umlauft
2026-07-31, Group Seminar, AAU
NES, Smart Grids Group
Improve Your Talks
Improve Your Talks! How to stand out at Conferences
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We all hate THIS
Yawn…
ZZZzz
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How about THIS ?
Boring boring boring
Boring boring boring
Boring boring boring
Hard to read….
boring boring
gibberish…
Need. to. �check. email…
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You, at 15:00�
Would you want� to listen to your talk?
Yawn…
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2nd Screen Effect
This is my talk…
@....
Partial attention
is now a thing
……
….
…
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So….
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…what is a Talk,�Anyway?
�Type
Audience
You
perfect talk
Conference
Institute / Thesis
Lecture (series)
Project demo
Motivational …
Confident�Extrovert�
Nervous�Introvert�
Style …
Interested�Bored, Tired�Knowledge ?
Important
Hostile�…
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Today's Talk
�Type
Audience
You
perfect talk
Conference 20 – 30min
Institute / Thesis
Lecture (series)
Project demo
Motivational
Confident�Extrovert
�Nervous�Introvert
Exercises
above average talk
Typically:� Exhausted
Capabilities
cognitive
visual
Make it easy�& enjoyable
slides
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How good do you need to be?
Above average �is GOOD ENOUGH
Many talks are bad
You do NOT need to be uber brilliant to stand out
Economic trade-off
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STARTING THE TALK
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Typical Talk – Title Page
DO give credit but
Make it short & sweet!
Application of the Foobar Algorithm in the Baz System
Author 1 Name, Company, Country�Author 2 Name, University, Country�Author 3 Name, Laboratory, Country
Research Project so-and-so�Financed by XYZ under Grant Number 1234-678Y
Conference Name�Date & Place
You have just been introduced
Info is in the conference program
LOGO
LOGO
LOGO
LOGO
LOGO
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Outline
Same slide in 90% of talks!
B.O.R.I.N.G.TM
20 – 30 min talk needs no map
Outline of my Talk
Outline
= Map to the talk
NEVER
waste attention
Picture © Everaldo Coelho and YellowIcon, LGPL
ATTENTION
KILLER
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Beginning of Your Talk
2mins
You have
Why should I listen to this talk?
What is the problem?
Why is it an interesting problem?
OR
Here's a novel solution
Hydrargyrum, PD
30s
5s
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Example
Simulation needs many runs
Currently no realistic node position generators
Too few real-world setups
Our XY system can �generate many setups based on 1 target
Generated setups are similar to the target
Problem
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My problem description
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My "map"
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MAIN PART
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Main Part
Pictures © National Cancer Institute/NIH; Renee Comet, PD
Do NOT try to include everything!
Your Paper
Your Talk
The beef
all the details
Check out our�delicious NEW
The ad for the beef
general idea, make hungry
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Main Part
Tell the story:
what's the idea behind the algorithm / maths
Do use metaphors, pictures & examples
Do use meaningful animation
Avoid bullet slides
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Bullet Slides
DEATH by�PowerPoint
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Bullet Slides
Example
© Andor Akos, gemeinfrei
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The European Hamster, lat. Cricetus cricetus
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European Hamster, Cricetus cricetus
Protected – don't disturb!
Don't feed – attracts rats!
Property mgmt – green areas
Register sightings:
www.univie.ac.at/ziesel_hamster�
NABU Niederösterreich,�NABU Burgenland
Found an injured hamster ? � 🕿 MA 60: +43 1 4000-8060
ca. 30cm, 500g
© Martina Umlauft
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HUMAN �PERCEPTUAL �CAPABILITIES
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Visual Capabilities – Fonts
NO serif fonts
NOT italic
NO fancy fonts
NOT all like this
Arial
Calibri
Prokyon
Bold
+ Size
Italic: sparingly
N
Serifs:
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Visual Capabilities – Contrast
Dark background
Dark background
+ contrast�+ bold
Dark background
Light Background
Avoid medium backgrounds
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Visual Capabilities – Color & Contrast
Strongest Contrast
b/w
Light Blue
badly perceived
Light Yellows
badly rendered�on projectors
Strong Color
Strong Color
+1 size
bold
Dark Yellow Orange
+1 size
bold
Darker Blue
+1 size
bold
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Visual Capabilities – Color Use
Calm
Active
Good
Bad
cold
warm
Money (US)
attention
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Visual Capabilities – Color Perception
Red/green blindness
8% men
0.8% women
Technical conferences are male dominated!
Picture © Dan-yell, cc-by-sa
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Auditory Capabilities
Often the sound system
will be the limit!
19000 Hz
17000 Hz
16000 Hz
15000 Hz
12000 Hz
< 20 yrs
< 24 yrs
< 30 yrs
< 40 yrs
< 50 yrs
Peter Niemayer, cc-by-sa
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Mental-Visual Capabilities – Clutter
Topic 1
Topic 3
Topic 2
Topic 5
Topic 4
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Clutter – IMPROVED
Topic A1
Topic A2
Topic B1
Topic B2
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Clutter – IMPROVED 2
Topic A1
Topic A2
Topic B1
Topic B2
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Bullet Slides – Grouping Topics
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Bullet Slides – Grouping Topics – IMPROVED
Topic 1
Topic 2
Separation by whitespace
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Aligning on a Grid
© Andor Akos, gemeinfrei
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Framed Boxes – Example – Clean Look �
Natural language
Pseudo code
Mathematical�formulation
Diagram
NOTATIONS
Differential equation
Control theory
Network model
GLOBAL
State machine, workflow
Tree
Artificial neural network
Policy
LOCAL
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Framed Boxes – Example 2 – too Many�
Modeling
Library
Optimization
Code generation
Deployment
Monitoring
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Your PC vs Projector
60cm away
High Contrast
Strong Colors
BIG
Far away
Low Contrast
Washed-out Colors
small
→ "Wheee" Test
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"Wheee" Test
High Contrast
Far away
Low Contrast
Wheee!
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EXAMPLES
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Performance of our Algorithm
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Algorithm Performance
Data 2
Data 3
Data 1
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Algorithm Performance
Data 2
Data 3
Data 1
foobar gain
Improvement
Algo 1: at least 95% (from 83%)
Algo 2: up to 96% (from 80%)
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Performance of our Algorithm
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Algorithm Performance
Data 2
Data 3
Data 1
foobar gain
Improvement
Algo 1: at least 95% (from 83%)
Algo 2: up to 96% (from 80%)
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WiFi Measurements
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WiFi Measurements
WiFi Measurements
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WiFi Measurements
WiFi Measurements
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Spiderino with other Swarm Robotics �Platforms
E-puck
Kilobot
Colias
Spiderino
Robot | Cost ($) | Motion | Autonomy (h) |
Kilobot | 120 | vibration | 3-24 |
E-puck | 840 | wheel | 1-10 |
Colias | 41 | wheel | 1-3 |
Jasmine | 100 | wheel | 1-2 |
Spiderino | 80 | legs | 4-20 |
Jasmine
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Spiderino vs. other �Swarm Robotics Platforms
E-puck
Kilobot
Colias
Spiderino
Jasmine
Cost ($) | 120 | 840 | 41 | 100 | 80 |
Motion | Vibration | Wheel | Wheel | Wheel | Legs |
Autonomy (h) | 3-24 | 1-10 | 1-3 | 1-2 | 4-20 |
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Spiderino for Educational Purposes
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Spiderino for Educational Purposes
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Algorithm – Example
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Algorithm – Example – IMPROVED
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Example – Vertical Diagram
UAV
UGV
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Example – Vertical Diagram – IMPROVED
UAV
UGV
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Equation Example
Where�h … inhomogeneity measure
d … node density
mNNB … mean nearest neighbor distance
sNNB … sdev nearest neighbor distance
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Equation Example – IMPROVED
inhomogeneity measure
node density
mean nearest�neighbor distance
sdev nearest�neighbor distance
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Many thanks �to the original �slide creators!
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GIVING THE TALK
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Today's Talk
�Type
Audience
You
Conference
20 – 30min
Confident�Extrovert
�Nervous�Introvert
Exercises
Typically:� Exhausted
Make it easy�& enjoyable
Capabilities
cognitive
visual
✔
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You – Nervous?
Everybody is nervous
They can't revoke your paper if you botch it
Enthusiastic fake it until you make it
Competent big, tall, strong, deep voice
You want to appear
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Posture – Competent Look
This will also help your voice
Lower abs
Train
Latissimus
Hamstring
Hip flexor
Stretch
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Prepare according to YOUR style
Practice a lot / not
Use slide notes / cue cards
Learn by heart:
Singing lessons
Language class
super helpful!
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Just Before
During Talk
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Still Nervous?
Calm down
Ride the adrenaline
2 schools of thought
I'm so excited to be here !!
I'm calm and can do it
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END PAGE DESIGN
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How NOT to design an End Page
THANK YOU!
QUESTIONS?
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What to PUT on an End Page
Application of the Foobar Algorithm in the Baz System
Corresponding Author�University, @email, �https://web_address
Author 2 Name, University
Author 3 Name, University
Research Project so-and-so�Financed by XYZ under Grant Number 1234-678Y
Conference Name, Date & Place
LOGO
LOGO
LOGO
LOGO
LOGO
THANK YOU! QUESTIONS?
Title, where, when
Mark as End
Corresponding author with all contact info, maybe a QR code
Non-corresponding authors
Mandatory project info: financing institutions,
partner companies,�a certain size can be required
White space for separation
Corporate Identity may be mandatory
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CONCLUSION
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REMEMBER
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�Type
Audience
You
Think of THEM
perfect talk
above average talk
Audience
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�Type
Audience
You
Give talks you would want to hear
Think of THEM
perfect talk
above average talk
Audience
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Improve Your Talks
How to Stand out at Conferences, AAU, 2026-07-31�Short version
Martina Umlauft umlauft@lakeside-labs.at
https://mumlauft.blogspot.com/p/giving-good-talks.html
Improved slides make conferences
BETTER for everyone – DO IT
Thank You! – Questions?
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APPENDIX
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Online Resources – Presentations
Simon Peyton Jones: How to give a good research talk�http://research.microsoft.com/en-us/um/people/simonpj/papers/giving-a-talk/giving-a-talk.htm
Garr Reynolds: Presentation Tips�http://www.garrreynolds.com/preso-tips/
Nancy Duarte: Resonate (free online version)�http://www.duarte.com/blog/free-multimedia-version-of-resonate/
Amy Cuddy: Your body language shapes who you are�http://www.ted.com/talks/amy_cuddy_your_body_language_shapes_who_you_are
Main inspiration for this talk
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Online Resources – Graphs & Data Viz
Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm�https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002128#pbio.1002128.s007
Chartable Blog�https://blog.datawrapper.de/�https://blog.datawrapper.de/colors/�https://blog.datawrapper.de/line-charts/
The R Graph Gallery�https://www.r-graph-gallery.com/
Gnuplotting - Create scientific plots using gnuplot�http://www.gnuplotting.org/
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Online Resources – Color Blindness
Coloring for Colorblindness, David Nichols�https://davidmathlogic.com/colorblind/#%23D81B60-%231E88E5-%23FFC107-%23004D40
Color Brewer 2.0 (helps to choose colors)�http://colorbrewer2.org
Color Palettes for Color Blindness�http://mkweb.bcgsc.ca/colorblind/
Coblis – Color Blindness Simulator�https://www.color-blindness.com/coblis-color-blindness-simulator/
Color Oracle – Downloadable Color Blindness Simulator�https://colororacle.org/
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Books
Traci Nathans-Kelly, Christine G. Nicometo�Slide Rules: Design, Build, and Archive Presentations in the Engineering and Technical Fields (IEEE, 2014)
Garr Reynolds�Presentation Zen
Nancy Duarte�slide:ology
Roger C. Parker's�One-Minute Designer
Melanie Robbins�The 5 Second Rule
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Books
Thomas Rahlf�Datenvisualisierung mit R: 111 Beispiele
Cole Nussbaumer Knaflic�Storytelling with Data: A Data Visualization Guide for Business Professionals
Stephen Few�Show Me the Numbers: Designing Tables and Graphs to Enlighten
Dona M. Wong�The Wall Street Journal Guide to Information Graphics: The Dos and Don'ts of Presenting Data, Facts, and Figures
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Picture Credits
Map icon: Everaldo Coelho and YellowIcon, LGPL�http://commons.wikimedia.org/wiki/File:Crystal_Clear_app_starthere.png
Stopwatch photo: Hydrargyrum, Public Domain�http://commons.wikimedia.org/wiki/File:Stopwatch2.jpg
Cheeseburger photo: National Cancer Institute/NIH; Renee Comet, Public Domain�http://en.wikipedia.org/wiki/File:Cheeseburger.png
Head with ideas drawing: Andor Akos, gemeinfrei�http://de.wikipedia.org/wiki/Datei:Otto_Merkt_von_Akos.jpg
Color blindness test drawing: Dan-yell, cc-by-sa�http://de.wikipedia.org/wiki/Datei:Ishihara-Test.svg
QR-Code Example: Immanuel Giel, cc-by-sa�http://de.wikipedia.org/wiki/Datei:QRCode.png
Ear photo: Peter Niemayer, cc-by-sa�http://de.wikipedia.org/w/index.php?title=Datei:Ohr2.jpg&filetimestamp=20041213112440&
All other unsigned drawings © Martina Umlauft
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