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==Schedule==
==Schedule==
* '''Apr. 20, 16:00ct''': Introduction meeting  
* '''Apr. 20, 16:00ct''': Introduction meeting  
* '''TBA''' : Deadline for registration
* '''Jun. 22, 2017''' : Deadline for registration
* '''TBA''' : Presentations
* '''Jun. 29, 2017''' : Presentations
* '''September. 30, 2017, 23:59''': Deadline for submission of report (should be sent to the topic advisor!)
* '''September. 30, 2017, 23:59''': Deadline for submission of report (should be sent to the topic advisor!)


== Topics ==
== Topics ==
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|-
|-
| '''Deep into Google Translate'''   
| '''Deep into Google Translate (assigned to Monisha Khurana)'''   
This study is to provide a comprehensive study of one of the Google products - Google translate and aim to understand the technologies behind it.
This study is to provide a comprehensive study of one of the Google products - Google translate and aim to understand the technologies behind it.
| [http://www.net.informatik.uni-goettingen.de/people/Hong_Huang Hong Huang]
| [http://www.net.informatik.uni-goettingen.de/people/Hong_Huang Hong Huang]
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| [http://science.sciencemag.org/content/350/6264/1073][http://www.sciencedirect.com/science/article/pii/S0378873314000033]
| [http://science.sciencemag.org/content/350/6264/1073][http://www.sciencedirect.com/science/article/pii/S0378873314000033]
|-
|-
|'''An overview on deep learning framework'''
|'''An overview on deep learning framework (assigned to Fangxi Deng)'''
In this work, you will be asked to do a survey on all popular deep learning framework either in academe or industry, like tensorflow, caffe and so on. You shall elaborate their shortcomings and advantages.
In this work, you will be asked to do a survey on all popular deep learning framework either in academe or industry, like tensorflow, caffe and so on. You shall elaborate their shortcomings and advantages.
|[http://www.net.informatik.uni-goettingen.de/people/Hong_Huang Hong Huang]
|[http://www.net.informatik.uni-goettingen.de/people/Hong_Huang Hong Huang]
|[https://deeplearning4j.org/compare-dl4j-torch7-pylearn]
|[https://deeplearning4j.org/compare-dl4j-torch7-pylearn]
|-
|-
| '''Industrie 4.0: Networking prospective and challenges'''   
| '''Industrie 4.0: Networking prospective and challenges (Assigned to Hailiang Li)'''   
Germany is targeting reach Industry 4.0 stage in factories. You should survey all requirements from networking prospective and the main challenges.
Germany is targeting reach Industry 4.0 stage in factories. You should survey all requirements from networking prospective and the main challenges.
'''NOTE:'''This topic could be a good entry for master project and thesis later.  
'''NOTE:'''This topic could be a good entry for master project and thesis later.  
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|[http://www.cryptovest.co.uk/resources/Bitcoin%20paper%20Original.pdf][https://www.usenix.org/system/files/login/articles/03_meiklejohn-online.pdf]
|[http://www.cryptovest.co.uk/resources/Bitcoin%20paper%20Original.pdf][https://www.usenix.org/system/files/login/articles/03_meiklejohn-online.pdf]
|-
|-
| '''Legacy devices support in SDN controllers'''
| '''Legacy devices support in SDN controllers (Assigned to Ankita Bajpai)'''
'''NOTE:''' This topic could be a good entry for master project and thesis later.  
'''NOTE:''' This topic could be a good entry for master project and thesis later.  
Supporting legacy network is an active research area in SDN. You should survey all techniques used up to date to solve this problem. Details may be provided later.  
Supporting legacy network is an active research area in SDN. You should survey all techniques used up to date to solve this problem. Details may be provided later.  
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|-
|-
| '''Google QUIC'''
| '''Google QUIC'''
QUIC is an experimental transport layer network protocol designed by Jim Roskind at Google, initially implemented in 2012. Investigate QUIC in detail and conduct some simple experiments to compare QUIC with TCP. The experiments should be designed by the student himself/herself.
QUIC is an experimental transport layer network protocol designed by Jim Roskind at Google, initially implemented in 2012. Investigate QUIC in detail and compare QUIC with TCP and TCP variants.
| [http://www.net.informatik.uni-goettingen.de/people/enhuan_dong Enhuan Dong]
| [http://www.net.informatik.uni-goettingen.de/people/enhuan_dong Enhuan Dong]
|[https://en.wikipedia.org/wiki/QUIC][https://docs.google.com/document/d/1RNHkx_VvKWyWg6Lr8SZ-saqsQx7rFV-ev2jRFUoVD34/edit][https://datatracker.ietf.org/wg/quic/about/][https://github.com/google/proto-quic][https://groups.google.com/a/chromium.org/forum/#!topic/proto-quic/CioG51ecKB8]
|[https://en.wikipedia.org/wiki/QUIC][https://docs.google.com/document/d/1RNHkx_VvKWyWg6Lr8SZ-saqsQx7rFV-ev2jRFUoVD34/edit][https://datatracker.ietf.org/wg/quic/about/][https://github.com/google/proto-quic][https://groups.google.com/a/chromium.org/forum/#!topic/proto-quic/CioG51ecKB8]
|-
|-
| '''Google TCP BBR'''
| '''Google TCP BBR'''
TCP BBR is developed by Google. Investigate BBR in detail and conduct some simple experiments to compare BBR with TCP Cubic.The experiments should be designed by the student himself/herself.
TCP BBR is developed by Google. Investigate BBR in detail and compare TCP BBR with TCP and TCP variants.
| [http://www.net.informatik.uni-goettingen.de/people/enhuan_dong Enhuan Dong]
| [http://www.net.informatik.uni-goettingen.de/people/enhuan_dong Enhuan Dong]
|[http://queue.acm.org/detail.cfm?id=3022184][https://github.com/google/bbr][https://groups.google.com/forum/#!forum/bbr-dev]
|[http://queue.acm.org/detail.cfm?id=3022184][https://github.com/google/bbr][https://groups.google.com/forum/#!forum/bbr-dev]
|-
|-
| '''Commercial usage of Multipath TCP'''
| '''Commercial usage of Multipath TCP （assigned to Mojtaba Shabani）'''
MultiPath TCP (MPTCP) is an emerging extension for TCP and it is under discussion in IETF now. Study  MPTCP protocol including architecture, data transmission, default congestion control, etc. Investigate how MPTCP is used in companies.   
MultiPath TCP (MPTCP) is an emerging extension for TCP and it is under discussion in IETF now. Study  MPTCP protocol including architecture, data transmission, default congestion control, etc. Investigate how MPTCP is used in companies.   
| [https://www.net.informatik.uni-goettingen.de/people/enhuan_dong Enhuan Dong]
| [https://www.net.informatik.uni-goettingen.de/people/enhuan_dong Enhuan Dong]
| [https://tools.ietf.org/html/rfc6824][http://link.springer.com/chapter/10.1007%2F978-3-642-20757-0_35][https://www.usenix.org/conference/nsdi12/technical-sessions/presentation/raiciu][http://dl.acm.org/citation.cfm?id=2342476][http://dl.acm.org/citation.cfm?id=2631977][https://www.usenix.org/legacy/event/nsdi11/tech/full_papers/Wischik.pdf][http://blog.multipath-tcp.org/blog/html/2015/12/25/commercial_usage_of_multipath_tcp.html]
| [https://tools.ietf.org/html/rfc6824][http://link.springer.com/chapter/10.1007%2F978-3-642-20757-0_35][https://www.usenix.org/conference/nsdi12/technical-sessions/presentation/raiciu][http://dl.acm.org/citation.cfm?id=2342476][http://dl.acm.org/citation.cfm?id=2631977][https://www.usenix.org/legacy/event/nsdi11/tech/full_papers/Wischik.pdf][http://blog.multipath-tcp.org/blog/html/2015/12/25/commercial_usage_of_multipath_tcp.html]
|-
|-
| '''Traffic Data Analysis'''
| '''Traffic Data Analysis （assigned to Michael Debono)'''
Great amount of traffic data are generated everyday from private cars, subway, taxi and buses, etc. Traffic data analysis is of great help to understand the patterns of people mobility, transport planning, urban management and policymaking. And it is also an interesting way to learn some basic knowledge about big data and machine learning.
Great amount of traffic data are generated everyday from private cars, subway, taxi and buses, etc. Traffic data analysis is of great help to understand the patterns of people mobility, transport planning, urban management and policymaking. And it is also an interesting way to learn some basic knowledge about big data and machine learning.
| [https://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding]
| [Shichang Ding --  shichang.ding@informatik.uni-goettingen.de]
| [http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149222][https://pdfs.semanticscholar.org/7d15/0a9390d569750978d9abcee4524f1974961f.pdf]
| [http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149222][https://pdfs.semanticscholar.org/7d15/0a9390d569750978d9abcee4524f1974961f.pdf]
|-
|-
| '''Robo advisors and AI'''
| '''Robo advisors and AI'''
A robo-advisor (robo-adviser) is an online wealth management service that provides automated, algorithm-based portfolio management advice without the use of human financial planners. Robo-advisor is one of new examples which show how AI begin to take place of human beings in high-end service like finance, laws, education and even research. Beside gaining basic knowledge about AI, it is also a good way to understand how AI change our future work markets.
A robo-advisor (robo-adviser) is an online wealth management service that provides automated, algorithm-based portfolio management advice without the use of human financial planners. Robo-advisor is one of new examples which show how AI begin to take place of human beings in high-end service like finance, laws, education and even research. Beside gaining basic knowledge about AI, it is also a good way to understand how AI change our future work markets.
| [https://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding]
| [Shichang Ding --  shichang.ding@informatik.uni-goettingen.de]
| [http://onlinepresent.org/proceedings/vol141_2016/21.pdf]
| [http://onlinepresent.org/proceedings/vol141_2016/21.pdf]
|-
|-
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|-
|-
| '''Large-Scale Mobile Traffic Analysis - A Survey'''   
| '''Large-Scale Mobile Traffic Analysis - A Survey (Assigned to Mian Athar Naqash)'''   
This study is to provide a comprehensive study of large-scale mobile traffic analysis. You should survey the related work about this topic and focus on some classical research work. You also need to give your own opinion on the topic.
This study is to provide a comprehensive study of large-scale mobile traffic analysis. You should survey the related work about this topic and focus on some classical research work. You also need to give your own opinion on the topic.
| [http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao]
| [http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao]
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|-
|-
| '''Recommendations in Location-based Social Networks - A Survey'''   
| '''Recommendations in Location-based Social Networks - A Survey (Assigned to Hussain Nauman)'''   
This study is to provide a comprehensive study of recommendations in Location-based Social Networks. You should survey the related work about this topic and focus on some classical research work. You also need to give your own opinion on the topic.
This study is to provide a comprehensive study of recommendations in Location-based Social Networks. You should survey the related work about this topic and focus on some classical research work. You also need to give your own opinion on the topic.
| [http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao]
| [http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao]
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|-
|-
|'''ICN - Information Centric Networking'''
|'''ICN - Information Centric Networking (Assigned to Wazed Ali)'''  


Content Centric Networking (CCN) is a new ambitious proposal to replace the IP protocol. A better and faster content distribution, improved privacy, integrated cryptography and easy P2P communication are among the key elements of this architecture. On the other hand problems like efficiency and scalability of the name-based routing, support of existing application and new ones and the possibility to actually deploy this technology are still open and actively discussed, making CCN one of the most active research field in networking.  
Content Centric Networking (CCN) is a new ambitious proposal to replace the IP protocol. A better and faster content distribution, improved privacy, integrated cryptography and easy P2P communication are among the key elements of this architecture. On the other hand problems like efficiency and scalability of the name-based routing, support of existing application and new ones and the possibility to actually deploy this technology are still open and actively discussed, making CCN one of the most active research field in networking.  
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|-
|-
|-
| '''Learning from Imbalanced Data'''
| '''Learning from Imbalanced Data''' (assigned to Christoph Rauterberg)
When building and training classifiers for classification problems, one commonly encountered problem is that of imbalanced data. For instance, in the case of a binary classifier, this means that one class is hugely overrepresented in the data available. Training classifiers for this kind of datasets has been a problem for some time. In this work, your task is to i) precisely introduce the imbalanced data problem, ii) discuss the state of the art of approaches for mitigating this problem (both from the perspective of learning algorithms and data manipulation techniques) and iii) find out what issues still remain open until today. Note that this topic requires a background in data science, and in particular in classification algorithms. Also, this topic requires a comparatively high reading effort.
When building and training classifiers for classification problems, one commonly encountered problem is that of imbalanced data. For instance, in the case of a binary classifier, this means that one class is hugely overrepresented in the data available. Training classifiers for this kind of datasets has been a problem for some time. In this work, your task is to i) precisely introduce the imbalanced data problem, ii) discuss the state of the art of approaches for mitigating this problem (both from the perspective of learning algorithms and data manipulation techniques) and iii) find out what issues still remain open until today. Note that this topic requires a background in data science, and in particular in classification algorithms. Also, this topic requires a comparatively high reading effort.
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ]
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ]
| [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5128907&tag=1]
| [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5128907&tag=1]
|-
|-
| '''Deep Learning and its (possible) flaws'''
| '''Deep Learning and its (possible) flaws''' (assigned to Sven Voigt)
One recent trend in machine learning is 'deep learning', where neural networks are employed for solving a wide range of problems. One prominent example of such problems is image classification. While neural networks are in fact delivering sometimes great results, they may also have some weak spots. In this work, your task is to i) make yourself familiar with neural networks, ii) discuss the state-of-the-art in image classification, and iii) to investigate some possible flaws in neural networks. Note that for this topic a background in data science, and in particular in classification algorithms, is strongly recommended. Also, this topic requires a comparatively high reading effort.
One recent trend in machine learning is 'deep learning', where neural networks are employed for solving a wide range of problems. One prominent example of such problems is image classification. While neural networks are in fact delivering sometimes great results, they may also have some weak spots. In this work, your task is to i) make yourself familiar with neural networks, ii) discuss the state-of-the-art in image classification, and iii) to investigate some possible flaws in neural networks. Note that for this topic a background in data science, and in particular in classification algorithms, is strongly recommended. Also, this topic requires a comparatively high reading effort.
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ]
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ]
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|-
|-
| '''How do self-driving cars work?'''   
| '''How do self-driving cars work?'''   
The topic title is pretty self-explanatory :)
The topic title is pretty self-explanatory :) (however, you need to understand the math behind it to some extent).
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ]
| [https://www.net.informatik.uni-goettingen.de/people/David_Koll David Koll ]
| [http://cs.stanford.edu/people/teichman/papers/iv2011.pdf]
| [http://cs.stanford.edu/people/teichman/papers/iv2011.pdf]
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| [https://pdfs.semanticscholar.org/e682/85544e01b2075d8d5fe65569232a3de840cc.pdf] [http://web.cs.ucla.edu/classes/fall03/cs218/paper/pgmcc.pdf] [http://conferences2.sigcomm.org/acm-icn/2016/proceedings/p11-chen.pdf]
| [https://pdfs.semanticscholar.org/e682/85544e01b2075d8d5fe65569232a3de840cc.pdf] [http://web.cs.ucla.edu/classes/fall03/cs218/paper/pgmcc.pdf] [http://conferences2.sigcomm.org/acm-icn/2016/proceedings/p11-chen.pdf]
|-
|-
| '''Adaptive Video Streaming'''   
| '''Adaptive Video Streaming (assigned to Nikolaj Kopp)'''   
Today's Internet is a heterogeneous networking environment. In such an environment, resources available to multimedia applications vary. To adapt to the changes in network conditions, both networking techniques and application layer techniques have been proposed. The study must give an overview of the different techniques proposed and some real use-case scenarios (ever heard about a company named Netflix??)
Today's Internet is a heterogeneous networking environment. In such an environment, resources available to multimedia applications vary. To adapt to the changes in network conditions, both networking techniques and application layer techniques have been proposed. The study must give an overview of the different techniques proposed and some real use-case scenarios (ever heard about a company named Netflix??)
| [https://www.net.informatik.uni-goettingen.de/people/jacopo_de%20benedetto Jacopo De Benedetto ]
| [https://www.net.informatik.uni-goettingen.de/people/jacopo_de%20benedetto Jacopo De Benedetto ]
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| [http://www.net.informatik.uni-goettingen.de/people/abhinandan%20s_prasad Abhinandan S Prasad]
| [http://www.net.informatik.uni-goettingen.de/people/abhinandan%20s_prasad Abhinandan S Prasad]
| [https://en.wikipedia.org/wiki/Prediction_market][http://www.nature.com/news/the-power-of-prediction-markets-1.20820][https://dash.harvard.edu/handle/1/5027266]
| [https://en.wikipedia.org/wiki/Prediction_market][http://www.nature.com/news/the-power-of-prediction-markets-1.20820][https://dash.harvard.edu/handle/1/5027266]
|-
| '''Privacy-Aware Platform for Personal Data (Assigned to Alireza) '''
Take a look at the open IoT platforms and provde a summary of the differences, similarities and vision.
| [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Mayutan Arumaithurai]
| Take a look at Fiware, Sophia, Crystal and other open platforms
|-
| '''Edge Computing for Internet of Things (Assigned to Andrea Melina) '''
A study of the various edge computing solutions that exist for IoT
| [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Mayutan Arumaithurai]
| Take a look at Amazon Lambda, Amazon IoT, Amazon greengrass and solutions by other companies
|-
| '''Brief Introduction to High Performance Computing Acceleration (assigned to DOAN Ho Anh Triet)'''
The aim of this work is to take a look at HPC and study their similarities, differences, pros and cons
| [http://www.net.informatik.uni-goettingen.de/people/mayutan_arumaithurai Mayutan Arumaithurai]
| Take a look at recent papers in well known conferences/workshops.
|-
|-
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