Difference between revisions of "CSE 7300 Research Seminar"

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* '''Theme: AI for Health'''
 
* '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
 
* '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
−
* '''Semester''': Fall 2020
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* '''Semester''': '''Fall 2024'''
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* '''Time''': Thursday at 4pm-4:50pm
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* '''Time''': Wednesday at 1 PM
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* '''Location''': Virtual
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* '''Location''': McKelvey 1030
 +
* '''[http://www.cse.wustl.edu/~lu/talks/seminar_guidelines.pdf Guidelines]''':  
 +
* '''Recommended sources:''' NeurIPS ([http://nips.cc/]), ICML ([http://icml.cc/]), AAAI ([http://www.aaai.org/]), SIGKDD ([http://www.kdd.org/]), IJCAI ([http://www.ijcai.org/]), IMWUT ([http://dl.acm.org/journal/imwut]), HEALTH ([http://dl.acm.org/journal/health]), Digital Medicine ([http://www.nature.com/npjdigitalmed/]), Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201]), NEJM AI ([https://ai.nejm.org/])
  
 +
==Presentation Schedule==
  
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=== ---ML for Health ---===
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=== ---Sep 11 ---===
 +
Ziqi
  
−
* NeurIPS ([http://nips.cc/])
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Gawlikowski, J., Tassi, C.R.N., Ali, M. et al. A survey of uncertainty in deep neural networks. Artif Intell Rev 56 (Suppl 1), 1513–1589 (2023). [https://doi.org/10.1007/s10462-023-10562-9]
−
* ICML ([http://icml.cc/])
 
−
* AAAI ([http://www.aaai.org/])
 
−
* SIGKDD ([http://www.kdd.org/])
 
−
* IJCAI ([http://www.ijcai.org/])
 
−
* IMWUT ([http://dl.acm.org/journal/imwut])
 
−
* Digital Medicine ([http://www.nature.com/npjdigitalmed/])
 
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* HEALTH ([http://dl.acm.org/journal/health])
 
−
* Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201])
 
  
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=== ---Cyber Physical Systems ---===
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=== ---Sep 18 ---===
 +
Daoyi
  
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* SenSys ([http://sensys.acm.org])
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Hüyük, A., Wei, Q., Curth, A. and van der Schaar, M., 2024. Defining Expertise: Applications to Treatment Effect Estimation. arXiv preprint arXiv:2403.00694. [https://openreview.net/pdf?id=1YPfmglNRU]
−
* IPSN ([http://ipsn.acm.org])
 
−
* RTSS ([http://www.rtss.org/])
 
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* RTAS ([http://www.rtas.org/])
 
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* ICCPS ([http://www.iccps.org])
 
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* Wireless Health ([http://mobihealth.name/])
 
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* MobiCom ([https://sigmobile.org/mobicom/2019/])
 
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* MobiSys ([http://www.sigmobile.org/mobisys/2019/])
 
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* Sigcomm ([http://conferences.sigcomm.org/sigcomm/2019/])
 
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* NSDI ([https://www.usenix.org/conference/nsdi19])
 
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* SOSP ([https://www.sigops.org/])
 
−
* OSDI ([https://www.usenix.org/conference/osdi18/])
 
  
 +
=== ---Sep 25 ---===
 +
Jason
  
 +
=== ---Oct 02 ---===
 +
Ben
  
−
=== ---Oct 1 ---===
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=== ---Oct 09 ---===
 +
Claire
  
−
Jingwen
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=== ---Oct 16 ---===
 +
Wenyu
  
−
Paper: Goldstein, Orpaz, et al. "Target-Focused Feature Selection Using Uncertainty Measurements in Healthcare Data." ACM Transactions on Computing for Healthcare 1.3 (2020): 1-17. [https://dl.acm.org/doi/10.1145/3383685]
+
=== ---Oct 23 ---===
 +
Di
  
−
=== ---Oct 8 ---===
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=== ---Oct 30 ---===
 +
Behrooz
  
−
Ruixuan
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=== ---Nov 06 ---===
 +
Prince
  
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Wiens, Jenna, John Guttag, and Eric Horvitz. "A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-specific predictions." Journal of the American Medical Informatics Association 21.4 (2014): 699-706.
+
=== ---Nov 13 ---===
−
[https://academic.oup.com/jamia/article/21/4/699/761441]
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Zichen
−
 
 
−
=== ---Oct 15 ---===
 
−
 
 
−
Hanyang
 
−
 
 
−
Bianchi, Filippo Maria, et al. "Learning representations of multivariate time series with missing data." Pattern Recognition 96 (2019): 106973.https://arxiv.org/abs/1805.03473
 
−
 
 
−
AAAI’20, A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. https://arxiv.org/abs/2002.12359
 
−
 
 
−
=== ---Oct 22 ---===
 
−
 
 
−
Cancel (SIGMETRICS/IoTDI/RTAS)
 
−
 
 
−
=== ---Oct 29 ---===
 
−
 
 
−
Liang
 
−
 
 
−
Paper: Mangaokar, Neal, Jiameng Pu, Parantapa Bhattacharya, Chandan K. Reddy, and Bimal Viswanath. "Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models." [https://people.cs.vt.edu/vbimal/publications/jekyll-eurosp20.pdf]
 
−
 
 
−
=== ---Nov 5---===
 
−
 
 
−
Bing
 
−
 
 
−
=== ---Nov 12---===
 
−
 
 
−
Haoran
 
−
 
 
−
=== ---Nov 19---===
 
−
 
 
−
Dingwen
 
−
 
 
−
=== ---Nov 26---===
 
−
 
 
−
Liang
 
−
 
 
−
=== ---Dec 3---===
 
−
 
 
−
Jingwen
 
−
 
 
−
=== ---Dec 10---===
 
−
 
 
−
Hangyang
 
−
 
 
−
=== ---Dec 17---===
 
−
 
 
−
Bing
 
  
 +
=== ---Nov 20 ---===
 +
Peiqi
  
 +
=== ---Nov 27 ---===
 +
Thanksgiving
  
  
 
==Previous Semesters==
 
==Previous Semesters==
 +
* [[Seminar Spring 2024|Spring 2024]]
 +
* [[Seminar Fall 2023|Fall 2023]]
 +
* [[Seminar Spring 2023|Spring 2023]]
 +
* [[Seminar Fall 2022|Fall 2022]]
 +
* [[Seminar Summer 2022|Summer 2022]]
 +
* [[Seminar Spring 2022|Spring 2022]]
 +
* [[Seminar Fall 2021|Fall 2021]]
 +
* [[Seminar Summer 2021|Summer 2021]]
 +
* [[Seminar Spring 2021|Spring 2021]]
 +
* [[Seminar Fall 2020|Fall 2020]]
 +
* [[Seminar Summer 2020|Summer 2020]]
 
* [[Seminar Spring 2020|Spring 2020]]
 
* [[Seminar Spring 2020|Spring 2020]]
 
* [[Seminar Fall 2019|Fall 2019]]
 
* [[Seminar Fall 2019|Fall 2019]]

Revision as of 19:06, 18 September 2024

  • Theme: AI for Health
  • Instructor: Prof. Chenyang Lu
  • Semester: Fall 2024
  • Time: Wednesday at 1 PM
  • Location: McKelvey 1030
  • Guidelines:
  • Recommended sources: NeurIPS ([1]), ICML ([2]), AAAI ([3]), SIGKDD ([4]), IJCAI ([5]), IMWUT ([6]), HEALTH ([7]), Digital Medicine ([8]), Lancet Digital Health ([9]), NEJM AI ([10])

Presentation Schedule

---Sep 11 ---

Ziqi

Gawlikowski, J., Tassi, C.R.N., Ali, M. et al. A survey of uncertainty in deep neural networks. Artif Intell Rev 56 (Suppl 1), 1513–1589 (2023). [11]

---Sep 18 ---

Daoyi

Hüyük, A., Wei, Q., Curth, A. and van der Schaar, M., 2024. Defining Expertise: Applications to Treatment Effect Estimation. arXiv preprint arXiv:2403.00694. [12]

---Sep 25 ---

Jason

---Oct 02 ---

Ben

---Oct 09 ---

Claire

---Oct 16 ---

Wenyu

---Oct 23 ---

Di

---Oct 30 ---

Behrooz

---Nov 06 ---

Prince

---Nov 13 ---

Zichen

---Nov 20 ---

Peiqi

---Nov 27 ---

Thanksgiving


Previous Semesters

Previous Lab Meetings

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