Difference between revisions of "CSE730x Research Seminar"

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* '''Instructor:''' [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
 
* '''Instructor:''' [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
* '''Time: Thursday at 10am-12pm, Location: Jolley 224'''
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* '''Time: Thursday at 4pm-4:50pm, Location: Jolley 431'''
* '''Google group:''' [http://groups.google.com/group/wu-systems-seminar google group]
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* '''Google group:''' [https://groups.google.com/forum/#!forum/wustlmlseminar group for machine learning seminar]
  
 
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This seminar examines machine learning by studying seminal papers and recent research results. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants. The theme of this semester's seminar is '''Machine Learning for Health'''. We will read and discuss papers from recent major conferences on machine learning, data mining, and AI related to healthcare.  These conferences include:
This seminar examines fundamental and emerging concepts in concurrency and distribution by studying seminal papers and recent research results.  Broad topics of interest include models of concurrency, mobile computing, parallel architectures, sensor networks, distributed algorithms, and specialized protocols. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants.
 
 
 
The theme of this semester's seminar is Wireless Sensor Networks. We will read and discuss papers from recent major conferences on mobile, wireless, and sensor networks and systems.  These conferences include:
 
  
 
* SenSys ([http://sensys.acm.org])
 
* SenSys ([http://sensys.acm.org])
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* RTAS ([http://www.rtas.org/])
 
* RTAS ([http://www.rtas.org/])
 
* ICCPS ([http://www.iccps.org])
 
* ICCPS ([http://www.iccps.org])
* Wireless Health ([http://www.wirelesshealth2013.org/])
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* Wireless Health ([http://mobihealth.name/])
* MobiCom ([http://www.sigmobile.org/mobicom/2013/])
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* MobiCom ([https://sigmobile.org/mobicom/2019/])
* MobiSys ([http://www.sigmobile.org/mobisys/2013/])
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* MobiSys ([http://www.sigmobile.org/mobisys/2019/])
* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2013/])
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* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2019/])
* NSDI ([https://www.usenix.org/conference/nsdi14])
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* NSDI ([https://www.usenix.org/conference/nsdi19])
* SOSP ([http://http://sigops.org/sosp/sosp13/])
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* SOSP ([https://www.sigops.org/])
* OSDI ([https://www.usenix.org/conference/osdi14/])
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* OSDI ([https://www.usenix.org/conference/osdi18/])
  
  
=== ---August 24 ---===
 
  
'''Seminar -Xiaoling'''
 
  
'''Lab Meeting -Dee'''
 
  
=== ---August 31 ---===
 
  
'''Seminar -Chao'''
 
  
Khandeparkar, Kedar, Krithi Ramamritham, and Rajeev Gupta. "QoS-Driven Data Processing Algorithms for Smart Electric Grids." ACM Transactions on Cyber-Physical Systems 1.3 (2017): 14. [http://dl.acm.org/citation.cfm?id=3047410 link]
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==Previous Semesters==
 
 
'''Lab Meeting -Chong'''
 
 
 
=== ---September 7 ---===
 
 
 
'''Seminar -Haoran'''
 
 
 
Jyothi, S. A., Curino, C., Menache, I., Narayanamurthy, S. M., Tumanov, A., Yaniv, J., ... & Rao, S. (2016, November). Morpheus: Towards Automated SLOs for Enterprise Clusters. In OSDI (pp. 117-134). [https://www.usenix.org/system/files/conference/osdi16/osdi16-jyothi.pdf paper]
 
 
 
'''Lab Meeting -Yehan'''
 
 
 
=== ---September 14 ---===
 
 
 
'''Seminar -Dingwen'''
 
 
 
Rui Wang, Weichen Wang, Min S. H. Aung, Dror Ben-Zeev, Rachel Brian, Andrew T. Campbell, Tanzeem Choudhury, Marta Hauser, John Kane, Emily A. Scherer, Megan Walsh. "Predicting Symptom Trajectories of Schizophrenia using Mobile Sensing." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 1 Issue 3, September 2017, Article No. 110
 
[https://dl.acm.org/citation.cfm?id=3130976 link]
 
 
 
'''Lab Meeting -Xin'''
 
 
 
=== ---September 21 ---===
 
 
 
'''Seminar -Ruixuan'''
 
 
 
Parisi, Federico, Gianluigi Ferrari, Alessio Baricich, Marco D'Innocenzo, Carlo Cisari, and Alessandro Mauro. "Accurate gait analysis in post-stroke patients using a single inertial measurement unit." In Wearable and Implantable Body Sensor Networks (BSN), 2016 IEEE 13th International Conference on, pp. 335-340. IEEE, 2016.
 
[http://ieeexplore.ieee.org/abstract/document/7516284/ link]
 
 
 
'''Lab Meeting -Dee'''
 
 
 
=== ---September 28 ---===
 
 
 
'''Seminar -Dee'''
 
 
 
Practice Talk
 
 
 
'''Lab Meeting -Chao'''
 
 
 
=== --October 5 ---===
 
 
 
'''Seminar -Yehan'''
 
 
 
Park, P., Di Marco, P., & Johansson, K. H. (2017). Cross-Layer Optimization for Industrial Control Applications Using Wireless Sensor and Actuator Mesh Networks. IEEE Transactions on Industrial Electronics, 64(4), 3250-3259. [http://ieeexplore.ieee.org/abstract/document/7755835/ paper]
 
 
 
'''Lab Meeting -Xiaoling'''
 
 
 
=== --October 12 ---===
 
  
'''Seminar -Dee'''
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* [[Seminar Fall 2019|Fall 2019]]
 
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* [[Seminar Summer 2019|Summer 2019]]
'''Lab Meeting -Haoran'''
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* [[Seminar Spring 2019|Spring 2019]]
 
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* [[Seminar Fall 2018|Fall 2018]]
=== --October 19 ---===
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* [[Seminar Summer 2018|Summer 2018]]
 
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* [[Seminar Spring 2018|Spring 2018]]
'''Seminar -Xin'''
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* [[Seminar Fall 2017|Fall 2017]]
 
 
'''Lab Meeting -Dingwen'''
 
 
 
=== --October 26 ---===
 
 
 
'''Seminar -Chong'''
 
 
 
'''Lab Meeting -Ruixuan'''
 
 
 
 
 
=== --November 2 ---===
 
 
 
'''Seminar -Xiaoling'''
 
 
 
'''Lab Meeting -Yehan'''
 
 
 
==Previous Semesters==
 
 
* [[Seminar Summer 2017|Summer 2017]]
 
* [[Seminar Summer 2017|Summer 2017]]
 
* [[Seminar Spring 2017|Spring 2017]]
 
* [[Seminar Spring 2017|Spring 2017]]
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==Previous Lab Meetings==
 
==Previous Lab Meetings==
 +
* [[Labmeeting Spring 2020|Spring 2020]]
 
* [[Labmeeting Fall 2014|Fall 2014]]
 
* [[Labmeeting Fall 2014|Fall 2014]]
 
* [[Labmeeting Summer 2014|Summer 2014]]
 
* [[Labmeeting Summer 2014|Summer 2014]]
 
* [[Labmeeting Spring 2014|Spring 2014]]
 
* [[Labmeeting Spring 2014|Spring 2014]]

Latest revision as of 21:49, 9 January 2020

This seminar examines machine learning by studying seminal papers and recent research results. Each semester, the seminar emphasizes different themes reflecting the current research interests of the participants. The theme of this semester's seminar is Machine Learning for Health. We will read and discuss papers from recent major conferences on machine learning, data mining, and AI related to healthcare. These conferences include:




Previous Semesters

Previous Lab Meetings