Video Streaming: Then, Now, and in the Future

In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.

1. Video Streaming: Then, Now, Future
Christian Timmerer, Professor at AAU, Director at CD Lab ATHENA
Klagenfurt, Austria
June 5, 2024
1
https://www.slideshare.net/christian.timmerer

2. ●Introduction / motivation
●Early days of video streaming + selected projects
●Toward HTTP adaptive streaming + MPEG-DASH
●ATHENA project
●Emerging research topics
Agenda
2

3. Introduction / Motivation
Sources:
* Sandvine Global Internet Phenomena (January 2024).
** Cisco Annual Internet Report (2018–2023) White Paper (March 2020)
3
3
Video streaming is dominating today’s
Internet traffic
●2024*: 68% (fixed) and 64% (mobile)
●Video on-demand: 54% / 57% – Live: 14% / 7%
●Main applications: YouTube, Netflix (>10%),
Tik Tok, Amazon Prime, Disney+ (<10%)
●Video and other applications continue to be of
enormous demand in today’s home, but there will
be significant bandwidth demands with the
application requirements of the future**

4. Multimedia Systems Challenges and Tradeoffs
4
4
Basic figure by Klara Nahrstedt, University of Illinois at Urbana–Champaign, IEEE MIPR 2018

5. Evolution of Video
5
5
Era of streaming
Yuriy Reznik, Christian Timmerer, 20 Years of Streaming in 20 Minutes, Mile-High Video
2020, https://athena.itec.aau.at/2020/11/20-years-of-streaming-in-20-minutes/

6. ●1993: Multicast Backbone (MBONE)
○Virtual multicast network connecting several universities & ISPs
○RTP-based video conferencing tool (vic) is used to stream videos
○1994 Rolling Stones concert – first major event streamed online
●1995: RealAudio, 1997: RealVideo
○First commercially successful mass-scale streaming system
○Proprietary protocols, codecs: PNA, RealAudio, RealVideo
○Worked over UDP, TCP, and HTTP (“cloaking” mode)
○First major broadcast: 1995 Seattle Mariners vs New York
Yankees
●1996: VDOnet, Vivo, NetShow, VXtreme, ...
○Many vendors have competed in streaming space initially
○Vivo & Xing have been acquired by Real, VXtreme by Microsoft
○By 1998, 3 main vendors remained: Real, Microsoft and Apple
●1998: RealSystem G2
○First Adaptive BitRate (ABR) streaming system
Early Streaming Systems
6
6Yuriy Reznik, Christian Timmerer, 20 Years of Streaming in 20 Minutes, Mile-High Video
2020, https://athena.itec.aau.at/2020/11/20-years-of-streaming-in-20-minutes/

7. 1998: RealSystem G2, “SureStream” technology
●First commercially successful Adaptive BitRate (ABR) streaming system
●Encoder: Encoded streams: Player:
●References
○B. Girod, et al, “Scalable codec architectures for Internet video-on-demand,” ACSSC, pp. 357 – 361, 1997.
○G. Conklin, et al, “Video Coding for Streaming Media Delivery on the Internet," TCSVT, 11 (3), pp. 20-34, 2001
○US Patents: 6314466, 6480541, 7075986, 7885340
First ABR Streaming System
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Multi-rate
packaging option
Selection of
streams to include
Panel showing which
stream is selected
Yuriy Reznik, Christian Timmerer, 20 Years of Streaming in 20 Minutes, Mile-High Video
2020, https://athena.itec.aau.at/2020/11/20-years-of-streaming-in-20-minutes/

8. Real Time Streaming Protocol (RTSP) et al., Internet Streaming Media
Alliance (ISMA), 3GPP Packet-Switched Streaming Service (PSS)
Early Streaming Standards
8
8
Server
DESCRIBE rtsp://example.com/mov.test RTSP/1.0
Session Description Protocol
SETUP rtsp://example.com/mov.test/streamID=0 RTSP/1.0
3GPP-Adaptation:url=
“rtsp://example.com/mov.test/streamID=0”;size=20000;target-time=5000
3GPP-Link-Char: url=“rtsp://example.com/mov.test/streamID=0”; GBW=32
RTSP OK
Client
Time (s)
PLAY rtsp://example.com/mov.test RTSP/1.0
RTSP OK
Real-time Transport Protocol
RTCP Reports
Setup Session
Streaming
Client Buffer
Client Buffer
Model

9. ●ADMITS (Adaptation in Distributed Multimedia IT Systems)
Media servers, meta-databases, proxies, routers, clients: which kind
of component can be best used for what kind of adaptation?
●IST-FP6: DANAE (Dynamic and Distributed Adaptation of
scalable multimedia coNtent in a context-Aware Environment)
MPEG-21-based adaptation framework: adaptation decisions –
usage environment – adapting multimedia content
●IST-FP6: ENTHRONE (End-to-End QoS through Integrated
Management of Content, Networks and Terminals)
ENTHRONE Integrated Management Supervisor (EIMS): considers all
stakeholder requirements – end-to-end management solution
ensuring QoS for the end user.
●MPEG-21 Multimedia Framework
Digital Item (Adaptation) – ISO/IEC 21000-7
Selected Projects at ITEC (1)
9
9
2002
-
2004
2004
-
2006
2006
-
2008
A. Vetro and C. Timmerer, "Digital Item Adaptation:
Overview of Standardization and Research Activities," in
IEEE Transactions on Multimedia, vol. 7, no. 3, pp. 418-426,
June 2005, doi: 10.1109/TMM.2005.846795.

10. ●Consumption of multimedia content may also stimulate
other senses
Vision or audition
Olfaction, mechanoreception, equilibrioception,
thermoception, …
●Annotation with metadata providing so-called sensory
effects that steer appropriate devices capable of
rendering these effects
Excursus: Sensory Effects and MPEG-V
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10
MPEG-V Building Blocks
Sensory Effect Description
Language (SEDL)
Sensory Effect Vocabulary
(SEV)
Sensory Effect Metadata
(SEM)
ISO/IEC 23005-3
G. Ghinea, C. Timmerer, W. Lin, and S. R. Gulliver, "Mulsemedia:
State of the Art, Perspectives, and Challenges", ACM Trans.
Multimedia Comput. Commun. Appl. 11, 1s, Article 17
(September 2014), doi:10.1145/2617994.

11. ●ICT-FP7: ALICANTE (Media Ecosystem
Deployment Through Ubiquitous
Content-Aware Network Environments)
Content-aware network processing will allow the
underlying infrastructure to identify, process, and
manipulate media streams and objects in real
time to maximize quality of service and
experience.
●Supports different streaming formats/protocols
RT(S)P, P2P, and HTTP
Selected Projects at ITEC (2)
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M. Grafl, C. Timmerer, et al., "Scalable Media Coding Enabling
Content-Aware Networking," in IEEE MultiMedia, vol. 20, no. 2,
pp. 30-41, April-June 2013, doi: 10.1109/MMUL.2012.57.
2010
-
2013

12. Video Delivery over HTTP/TCP
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○Enables
playback while
still downloading
○Server sends the
file as fast as
possible
Progressive
Download
○Enables seeking
via media indexing
○Server paces
transmission based
on encoding rate
Pseudo
Streaming
○Content is divided
into short-duration
chunks
○Enables live
streaming and ad
insertion
Chunked
Streaming
○Multiple versions
of the content are
created
○Enables to adapt
to network and
device conditions
Adaptive
Streaming

13. Progressive Download
13
13
HTTP Request
HTTP Response
Playback starts only after there
is several seconds of data in the
playback buffer
Download will continue as fast as
possible
Fetched content will be wasted if
the viewer clicks away
Can seek only throughout the
fetched content
Bing Wang, Jim Kurose, Prashant Shenoy, and Don Towsley. 2004. Multimedia streaming via TCP: an analytic performance study .
ACM International Conference on Multimedia (MM'04). DOI:https://doi.org/10.1145/1027527.1027735
“TCP generally provides good
streaming performance when
the achievable TCP
throughput is roughly twice
the media bitrate, with only a
few seconds of startup delay”

14. 14
14

15. Streaming is cooler, more viewer friendly
15
15
Playback starts when there
is just few seconds of data
Download rate will match the encoding
bitrate and downloading pauses if the
player pauses → Less waste
Can seek to anywhere in
the entire content
L. De Cicco, S. Mascolo. An Experimental Investigation of the Akamai Adaptive Video Streaming. in Proc of USAB
2010, special session Interactive Multimedia Applications (WIMA), Klagenfurt, Austria, 3-4 November 2010, LCNS 6389,
pp. 447-464, Springer-Verlag, doi:10.1007/978-3-642-16607-5
Implements “pseudo streaming”
and mimics RTSP-style streaming
but via HTTP.

16. HTTP Adaptive Streaming 101
Adaptation logic is within the
client, not normatively specified
by a standard, subject to
research and development
16
16
Client

17. Bitrate Adaptation Schemes
17
17
Bitrate
Adaptation
Schemes
Client-based
Adaptation
Bandwidth
-based
Buffer-
based
Mixed
adaptation
Proprietary
solutions
MDP-based
Server-based
Adaptation
Network-
assisted
Adaptation
Hybrid
Adaptation
SDN-based
Server and
network-
assisted
A. Bentaleb, B. Taani, A. C. Begen, C. Timmerer and R. Zimmermann, "A Survey on Bitrate Adaptation Schemes for
Streaming Media Over HTTP, " in IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 562-585, Firstquarter 2019.
doi: 10.1109/COMST.2018.2862938

18. MPD
Period id = 1
start = 0 s
Period id = 3
start = 300 s
Period id = 4
start = 850 s
Period id = 2
start = 100 s
Splicing of arbitrary
content like ads
MPEG DASH Data Model (ISO/IEC 23009-1)
Period id = 2
start = 100 s
Adaptation Set 0
subtitle turkish
Adaptation Set 2
audio english
Adaptation Set 3
audio german
Adaptation Set 1
video
Selection of
components/tracks
Adaptation Set 1
BaseURL=http://abr.rocks.com/
Representation 2
Rate = 1 Mbps
Representation 4
Rate = 3 Mbps
Representation 1
Rate = 500 Kbps
Representation 3
Rate = 2 Mbps
Selection of
representations
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18
Representation 3
Rate = 2 Mbps
Resolution = 720p
Segment Info
Duration = 10 s
Template:
3/$Number$.mp4
Well-defined
media format
Segment Access
Initialization
Segment
http://abr.rocks.com/3/0.mp4
Media Segment 1
start = 0 s
http://abr.rocks.com/3/1.mp4
Media Segment 2
start = 10 s
http://abr.rocks.com/3/2.mp4
Chunks with
addresses and timing

19. 19
19

20. “Application-oriented basic research” to address current and future research
and deployment challenges of HAS and emerging streaming methods
ATHENA – Adaptive Streaming over HTTP and
Emerging Networked Multimedia Services
Content ProvisioningContent DeliveryContent Consumption
End-to-End Aspects
●Video encoding for HAS
●Quality-aware encoding
●Learning-based encoding
●Multi-codec HAS
●Edge computing
●Information CDN/SDN ⇿clients
●Netw. assistance for/by clients
●Utility evaluation
●Bitrate adaptation schemes
●Playback improvements
●Context and user awareness
●Quality of Experience (QoE) studies
●Application/transport layer enhancements
●Quality of Experience (QoE) models
●Low-latency HAS
●Learning-based HAS
https://athena.itec.aau.at/
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Funding:
Hermann Hellwagner, Advances in Edge-Based and In-Network Media
Processing for Adaptive Video Streaming, Keynote at IEEE MIPR’23, Singapore.
Related
FFG-funded
projects:
AdvUHD-DASH,
PROMETHEUS,
APOLLO, GAIA

21. Problem Statement / Basic Idea for Live Streaming
●Static bitrate ladder
Pre-defined bitrate/resolution pairs for all contents
●Per-title encoding
Optimize bitrate ladder based on the content
●UHD / HFR content
Increase of spatial and temporal resolutions
●Live (is Life)[* Opus, 1985]
Perceptual-based bitrate/resolution/framerate
prediction algorithm based on content complexity
Video Complexity Analysis (1)
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21
VoD
Live
* … https://www.youtube.com/watch?v=pATX-lV0VFk

22. State of the Art: ITU-T Spatial Information / Temporal Information (SI/TI)
●The correlation with ground truth spatial and temporal complexity is low
Video Complexity Analysis (2)
22
22
Sobel Filter

23. Video Complexity Analyzer (VCA)
●VCA introduces DCT-based spatial-temporal complexity features
●Spatial complexity correlation has increased, but temporal complexity
remains low
Video Complexity Analysis (3)
23
23Vignesh V Menon, Christian Feldmann, Hadi Amirpour, Mohammad Ghanbari, and Christian Timmerer. 2022.
VCA: video complexity analyzer. In Proceedings of the 13th ACM Multimedia Systems Conference (MMSys '22). Association for
Computing Machinery, New York, NY, USA, 259–264. https://athena.itec.aau.at/2022/04/vca-video-complexity-analyzer/

24. Enhanced Video Complexity Analyzer (EVCA)
●EVCA refines the definition of the temporal complexity feature
●Temporal complexity correlation has increased
Video Complexity Analysis (4)
24
24H. Amirpour, M. Ghasempour, L. Qu, W. Hamidouche, and C. Timmerer. 2024. EVCA: Enhanced Video Complexity
Analyzer. In Proceedings of the 15th ACM Multimedia Systems Conference (MMSys '24). Association for
Computing Machinery, New York, NY, USA, 285–291. https://doi.org/10.1145/3625468.3652171

25. Deep Video Complexity Analyzer (DeepVCA)
Video Complexity Analysis (5)
25
25
H. Amirpour, K. Schoeffmann, M. Ghanbari and C. Timmerer, "DeepVCA: Deep Video Complexity Analyzer,"
in IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2024.3382366.
https://athena.itec.aau.at/2024/04/ieee-tcsvt-deepvca-deep-video-complexity-analyzer/

26. E-WISH: A policy driven ABR Algorithm
26
Energy Cost
+ \
[Data Cost]
Data Cost
Total Cost = ɑ
Segment bitrate
Throughput
[Buffer Cost]
Buffer Cost
+ β
Download time
Buffer occupancy
[Quality Cost]
Quality Cost
+ ɣ
Video quality
Distortion
Instability
Bitrate, Resolution, FPS (↑)
M. Nguyen, E. Çetinkaya, H. Hellwagner and C. Timmerer, "WISH: User-centric Bitrate Adaptation for
HTTP Adaptive Streaming on Mobile Devices," 2021 IEEE 23rd International Workshop on Multimedia
Signal Processing (MMSP), doi: 10.1109/MMSP53017.2021.9733605
Technology Transfer

27. E-WISH: An Energy-aware ABR Algorithm
27
[Data Cost] [Quality Cost][Buffer Cost] [Energy Cost]
Data Cost Buffer Cost Quality Cost Energy Cost
Total Cost = ɑ + β + ɣ + \
Segment bitrate
Throughput
Download time
Buffer occupancy
Video quality
Distortion
Instability
Bitrate, Resolution, FPS
M. Nguyen, E. Çetinkaya, H. Hellwagner and C. Timmerer, "WISH: User-centric Bitrate Adaptation for
HTTP Adaptive Streaming on Mobile Devices," 2021 IEEE 23rd International Workshop on Multimedia
Signal Processing (MMSP), doi: 10.1109/MMSP53017.2021.9733605
D.Lorenzi, M. Nguyen, F. Tashtarian, and C. Timmerer, “E-WISH: An Energy-aware ABR Algorithm For
Green HTTP Adaptive Video Streaming”, 3rd ACM Mile-High Video Conference (MHV '24),
https://doi.org/10.1145/3638036.3640802

28. Live Video Streaming Pipeline
28
LIVE
Origin Server
(Encoding & Packaging)
Live Camera PlayerCDN Server
manifest.mpd
Bitrate Resolution
5 Mbps 1920x1080
2.8 Mbps 1280x720
1.1 Mbps 960x540
System Admin
Bitrate
Ladder
HTTP Request
HTTP Response
Manifest includes representations:
different versions of the content optimized for various
playback conditions, e.g., different bitrates and resolutions
Tashtarian et al., "ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming", 21st USENIX
Symposium on Networked Systems Design and Implementation (NSDI 24), Santa Clara, CA, 2024
●Fixed bitrate ladder
○Content-aware, e.g., Netflix’s per-title encoding
○Context-aware, e.g., [Lebreton and Yamagishi 2023]
○Agnostic of the content and context (proprietary)

29. ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming
Select representations
with bitrates that closely
match the desired bitrates
Players
Advertise a large
number of
representations
Encoded
segments
CDN
Server
Mega-Manifest
29
Origin Server
OTL
Process requests
and video qualities
and determine OTL
LIVE
Live
Camera
Utilize the OTL
OTL: Optimized Temporary Ladder
Tashtarian et al., "ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming", 21st USENIX
Symposium on Networked Systems Design and Implementation (NSDI 24), Santa Clara, CA, 2024

30. Quality of Experience (QoE) ...
●“... is the degree of delight or annoyance of the user of an application or service.
It results from the fulfillment of his or her expectations with respect to the utility and / or
enjoyment of the application or service in the light of the user’s personality and current state.”
1)
●… can be easily extended to various domains, e.g., immersive media experiences .
2)
30
30
1)
P. Le Callet, S. Möller, A. Perkis, et al. QUALINET White Paper on
Definitions of Quality of Experience. European Network on Quality of
Experience in Multimedia Systems and Services (COST Action IC 1003). 2012.
2)
A. Perkis, C. Timmerer, et al. 2020. QUALINET White Paper on Definitions
of Immersive Media Experience (IMEx). arXiv:2007.07032 [cs.MM]
3)
J. van der Hooft, T. Wauters, F. De Turck, C. Timmerer, and H. Hellwagner.
“Towards 6DoF HTTP Adaptive Streaming Through Point Cloud
Compression”. 27th ACM Int’l. Conf. on Multimedia (MM'19). Oct. 2019.
4)
J. van der Hooft, M. T. Vega, C. Timmerer, A. C. Begen, F. De Turck and R.
Schatz, "Objective and Subjective QoE Evaluation for Adaptive Point
Cloud Streaming," 2020 Twelfth International Conference on Quality of
Multimedia Experience (QoMEX), Athlone, Ireland, 2020.
3) 4)
2010 - 2014 - now

31. Immersive Video Delivery:
From Omnidirectional Video to Holography
31
31J. v. d. Hooft, H. Amirpour, M. Torres Vega, Y. Sanchez, R. Schatz; T. Schierl, C. Timmerer, "A Tutorial on
Immersive Video Delivery: From Omnidirectional Video to Holography," in in IEEE Communications
Surveys & Tutorials, vol. 25, no. 2, pp. 1336-1375, Secondquarter 2023, doi: 10.1109/COMST.2023.3263252.
●3DoF Omnidirectional Video
●6DoF Volumetric Video
●6DoF Imagery Video

32. NeRV: Neural Representations for Videos, NeurIPS 2021
Deep Learning-Based Video Coding: A Review and a
Case Study, ACM CSUR 2020
●Video Coding
Learned video coding / E2E deep video coding
Future of Video Streaming
32
32
An End-to-End Learning Framework for Video
Compression, TPAMI 2021
●Video Streaming
DeepStream: Video Streaming Enhancements
using Compressed Deep Neural Networks
Deep learning-based video coding
Neural implicit representation for videos
DeepStream: TCSVT 2022
Generative AI for video streaming

33. ATHENA team
Samira Afzal, Hadi Amirpour, Jesús Aguilar Armijo, Emanuele Artioli, Christian Bauer, Alexis Boniface, Ekrem
Çetinkaya, Reza Ebrahimi, Alireza Erfanian, Reza Farahani, Mohammad Ghanbari (late), Milad Ghanbari,
Mohammad Ghasempour, Selina Zoë Haack, Hermann Hellwagner, Manuel Hoi, Andreas Kogler, Gregor Lammer,
Armin Lachini, David Langmeier, Sandro Linder, Daniele Lorenzi, Vignesh V Menon, Minh Nguyen, Engin Orhan,
Lingfeng Qu, Jameson Steiner, Nina Stiller, Babak Taraghi, Farzad Tashtarian, Yuan Yuan, Yiying Wei
(Inter-)National Collaborators (selection)
●Prof. Ali C. Begen, Ozyegin University, Turkey
●Prof. Filip De Turck, Ghent University – imec, Belgium
●Dr. Jeroen van der Hooft, Ghent University – imec, Belgium
●Dr. Maria Torres Vega, Ghent University – imec, Belgium
●Dr. Raimund Schatz, AIT Austrian Institute of Technology, Austria
●Prof. Roger Zimmermann, NUS, Singapore
●Dr. Abdelhak Bentaleb, Concordia University, Canada
●Prof. Christine Guillemot, INRIA, Rennes, France
●Prof. Patrick Le Callet, Polytech Nantes-Institut Universitaire de France, France
●Prof. Junchen Jiang, University of Chicago, USA
●Dr. Sergey Gorinsky, IMDEA, Spain
Acknowledgments
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https://athena.itec.aau.at/

34. Co-Authors (2003-2023; cf. FODOK)
Abdelhak Bentaleb, Adam T. Lindsay, Adam Wieckowski, Adithyan Ilangovan, Adlen Ksentini, Ahmed Mehaoua, Alan Bertoni, Alberto Leon Martin, Alessandro Floris, Alex
Chernilov, Ali C. Begen, Alireza Erfanian, Amy Reibman, Anastasia Henkel, Anastasios Kourtis, Anatoliy Zabrovskiy, Andrea Detti, Andreas Hutter, Andreas Sackl, Andreas Schorr,
Andrew Perkis, Anne-Lore Mevel, Anthony Vetro, Antonio Pinto, Armin Trattnig, Arthur Lugmayr, Asim Hameed, Aytac Azgin, Babak Taraghi, Barnabás Takacs, Barry Crabtree,
Bayan Taani, Benjamin Bross, Benjamin Rainer, Bernd Girod, Bernhard Feiten, Brahim Allan, Bruno Gardlo, Carsten Griwodz, Cathrine Lamy-Bergot, Cedric Westphal, Chris
Needham, Christian Feldmann, Christian Keimel, Christian R. Helmrich, Christian Raffelsberger, Christian Sieber, Christine Guillemot, Christopher Müller, Cise Midoglu, Claudio
Alberti, Costas Troulos, Cyril Concolato, Daniel Corujo, Daniel Gatica-Perez, Daniel Hoelbling-Inzko, Daniel Negru, Daniel Posch, Daniel Silhavy, Daniel Weinberger, Daniele
Lorenzi, Daniele Renzi, Darragh Egan, David Wortley, Davide Rogai, Deepak Chaudhary, Detlev Marpe, Devillers Sylvain, Dietmar Jannach, Doncel V. Rodriguez, Dragi Kimovski,
Ekrem Cetinkaya, Emanuele Quacchio, Emre Karsli, Eric Delfosse, et al., Eugen Borcoci, Eva Cheng, Evangelos Pallis, Evgeny Kuzmin, Evgeny Petrov, Fabrizio S. Rovati, Fan
Chen, Farzad Tashtarian, Fernando López, Fernando Pereira, Filip De Turck, Filippo Chiariglione, Francesc Sanahuja, Franz J. Hauck, Gabriel Panis, Gabriele Panis, Gabriella
Olmo, George Gardikis, George Xilouris, Gheorghita Ghinea, Giovanni Cordara, Gülnaziye Bingöl, Hadi Amirpour, Haichao Yao, Hamid Hadian, Hannaneh Barahouei Pasandi,
Haral Kosch, Harald Kosch, Harilaos. Koumaras, Harold Vincent Poor, He Xu, Hemanth Kumar Ravuri, Henrique Guilhon de Castro, Hermann Hellwagner, Hongjie He, Hui Lu, Ian
Burnett, Ingo KofIer, Ingo Wolf, Ioannis Kompatsiaris, Irene Viola, Ismail Djama, Jaime Delgado, Jean Gelissen, Jean Le Feuvre, Jean-Charles Point, Jeroen van der Hooft, Jesus
Aguilar Armijo, Jianping Wang, Jim Hurley, Jingwen Zhu, Joachim Seidl, Johannes Jaborning, Johannes Liegl, John Barrett, John R. Smith, Jonathan Ishmael, Joost Geurts, Jörg
Heuer, Jörg Pöcher, Jose Martínez, Karel Fliegel, Karsten Grüneberg, Karsten Müller, Katharina Gassner, Keith Mitchell, Klaus Leopold, Klaus Schöffmann, Laszlo Szobonya,
Leonardo Peroni, Li Fang, Lingfeng Qu, Lu Yu, Luca Celetto, Luigi Atzori, Mamadou Sidibé, Marco Mattavelli, Maria Teresa Andrade, Maria Torres Vega, Marie-Jose Montpetit,
Mario Graf, Mario Taschwer, Marius Preda, Mark Stuart, Markus Waltl, Marta Larson, Martin Hahn, Martin Prangl, Martin Smole, Mathias Wien, Matteo Maiero, Matthias Hirth,
Matthias Klusch, May Lim, Michael Eberhard, Michael Grafl, Michael Mackay, Michael Ransburg, Miguel Gómez, Mike Buckham, Minh Nguyen, Mohammad Ghanbari, Mohammad
Hosseini, Mohammad Shojafar, Muawiyath Shujau, Myriam Amielh, Nakisa Shams, Narciso García, Narges Mehran, Negin Ghamsarian, Niall Murray, Nikos Zotos, Ningxiong Mao,
Ozgu Alay, Pablo Cesar, Pascal Frossard, Patrick Kapahnke, Patrick Le Callet, Pavel Korshunov, Pedro Carvalho, Pedro Souto, Peng Chen, Peter De Neve, Peter Lederer,
Peyman Sheikholharam Mashhadi, Philippe Hanhart, Phuoc Tran-Gia, Prajit T Rajendran, Prateek Agrawal, Radu Aurel Prodan, Raimund Schatz, Ralf Terlutter, Reinhard Grandl,
Reyhane Falanji, Reza Farahani, Reza Saeedinia, Reza Shokri Kalan, Ricardo Petrocco, Richard Marsh, Rik Van de Walle, Robby De Sutter, Roger Zimmermann, Roland
Kersche, Roland Mathá, Rongrong Ni, S. Omid Fatemi, Saad Harous, Sam Dutton, Sam Van Damme, Samira Afzal, Sandro Linder, Sean Brennan, Selina Zoe Haack, Serge
Lerouge, Sergey Gorinsky, Shivi Vats, Simone Ferlin-Reiter, Simone Milani, Simone Porcu, Stefan Lederer, Stefan Mangold, Stefan Petscharnig, Stefan Pham, Stefano Battista,
Stephen Davis, Stephen Gulliver, Steve Lerouge, Robby De Sutter, Sylvain Devillers, Tamer Nadeem, Teodora Guenkova-Luy, Theodore Zahariadis, Thomas DeMartini, Thomas
Frank, Thomas Gottron, Thomas Schierl, Thomas Stockhammer, Thomas Zinner, Tibor Szkaliczki, Tim Stevens, Tim Wauters, Tobias Hossfeld, Tommaso Melodia, Toufik Ahmed,
Touradj Ebrahimi, Vaios Koumaras, Venkata Phani Kumar Malladi, Victor Doncel, Vignesh Menon, Vishu Madaan, Vladislav Kashanskii, Wael Cherif, Weisi Lin, Wen Ji, Wenwu
Zhu, Will Shucheng Liu, Xiaoqi Cao, Xuemei Zhou, Yael Lapid, Yago Sanchez, Yaning Liu, Yao Zhao, Yaolin Yang, Yuan Yuan, Yuansong Qiao, Zahra Najafabadi Samani,
Zhengdao Zhan, Zhu Li
Acknowledgments
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34

35. Current Staff at ITEC
Afzal Samira, Amirpour Hadi, Artioli Emanuele, Azimi Ourimi Zoha, Bauer Christian, Farahani
Reza, Ghasempour Mohammad, Harshina Kseniia, Hellwagner Hermann, Hoi Manuel Elias,
Horvath Kurt Klaus, Isak Selina, Kimovski Dragi, Lachini Armin, Lorenzi Daniele, Lux Mathias,
Nasirihaghighi Sahar, Prodan Radu Aurel, Qureshi Kamran, Rader Martin, Schniz Felix,
Schöffmann Klaus, Seyeddizaji Seyedehhaleh, Tashtarian Farzad, Tuček Tom, Uitz Sebastian,
Vats Shivi, Wei Yiying, Gliesche Anna Julia, Letter Margit, Messner Rudolf, Steinbacher
Martina, Taschwer Mario, Kowatsch Paul, Leitinger Claudia, Leopold Mario, Strobl Magdalena
+ Alumni: https://itec.aau.at/alumni/
Acknowledgments
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36. Thank you for your attention
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