Biography



Qiuyi Wu (吴 秋怡, phonetics: Cho-Yi Wu) is a first-year Ph.D. student in University of Rochester (UR) Department of Biostatistics and Computational Biology. Previously she was a research associate in Argonne National Laboratory (ANL) working with Dr. Julie Bessac and Dr. Jiali Wang on wind model. Before that she was a visiting research fellow in the Statistical and Applied Mathematical Sciences Institute (SAMSI), where she worked closely with Dr. David Banks on Topic Modeling. Currently she is also involved in several research projects in SAMSI Program on Deep Learning. Her previous research project with her Master advisor Dr. Ernest Fokoue is about automatic musical improvisation detection and key learning via Bayesian techniques and text mining. She also completed a research project with Dr. Dhireesha Kudithipudi and Dr. Ernest Fokoue on Reservoir Computing Echo State Networks (ESNs) during the first year of her Master study.

Her CV can be found here.

More details about her research work can also be found here.

Updated on Sep 2, 2019.


Selected Work

Her research interests lie at Bayesian Nonparametrics, Bayesian Decision Theory, Spatial Statistics, ExtremeValue Analysis, Astrostatistics, Text Mining, Social Network Analysis, Agent-based Model, Natural Language Processing, Deep Learning.

Her previous research has involved: (a) the inherent capacity of ensemblelearning, (b) recurrent neural networks on epileptic seizure recognition data, (c) topic modeling techniques for applications such as music mining and political blogs analysis, and (d) emulators/surrogates for storm surge models and uncertainty quantification/ attribution in geostatistics.


Awards

  • Student Travel Award for Big Data Neuroscience Conference, ACNN, 2019
  • SAMSI Travel Award for Deep Learning Opening Workshop, 2019
  • Gold Medal for Best Student Research Award, UP-STAT Conference, 2019
  • Dean’s Ph.D. Fellowship, University of Rochester, 2019-2024
  • ASA Travel Award for IMS/ASA Spring Research Conference, SRC, 2019
  • NC ASA Young Researcher Award, AISC Conference, 2018
  • Gold Medal for Best Student Research Award, UP-STAT Conference, 2018
  • RIT Travel Grant Award, JSM Conference, Vancouver, Canada, 2018
  • Young Scientific Leader Award, UP-STAT Conference, 2017 - 2018
  • Nominee for Student Delegate of College of Science, RIT-COS, 2017
  • Student Scholarship Winners for SAS Global Forum, SAS, 2017
  • RIT Merit scholarship for Graduate Study,  RIT, 2016 - 2018

Publication

Peer-reviewed:

[1] Wu, Q., Fokoue, E., & Kudithipudi, D. (2018). An Ensemble Learning Approach to the Predictive Stability of Echo State Networks. Journal Of Informatics And Mathematical Sciences, 10(1 & 2), 181 - 199. doi: 10.26713/jims.v10i1-2.827 [link]

[2] Wu, Q., Fokoue, E. (2018). Naive Dictionary On Musical Corpora: From Knowledge Representation To Pattern Recognition. arXiv:1811.12802 (Preprint) [link] 

Other: 

[3] Wu, Q. (2018). Statistical Aspects of Music Mining: Naive Dictionary Representation. Thesis. RIT Scholar Works. [link]

[4] Wu, Q., Fokoue, E., & Kudithipudi, D. (2018). On the Statistical Challenges of Echo State Networks and Some Potential Remedies. arXiv:1802.07369 (Preprint) [link]

[5] Wu, Q., Fokoue, E., R. G. A. (2017). Epileptic seizure recognition data set. UC Irvine Machine Learning Repository [link] [code]


Talks

2019:
Joint Statistical Meetings 2019, Denver, Colorado - JSM - [Jul.2019]
Contributed, Exploratory analysis of Hurricane Storm Surge

IMS/ASA Spring Research Conference, Virginia Tech - SRC - [May.2019]
Poster Session, Uncertainty Quantification in Tropical Cyclone Climatology

Statistical Perspectives on Uncertainty Quantification (SPUQ) Workshop - SAMSI - [May.2019]
Poster Session, Exploratory Analysis of Tropical Cyclone Climatology

6th Bayesian, Fiducial, and Frequentist (BFF) Conferences - BFF6 - [Apr.2019]
Poster Session, Bayesian and Unsupervised Machine Learning Machines for Jazz Music Analysis

8th Annual Conference of the UPSTAT New York Chapters of ASA -UPSTAT ASA- [Apr.2019]
Poster Session,Text Mining and Music Mining

2018: 
SAMSI Model Uncertainty Program Storm Surge Working Group - SAMSI [Nov.2018]
Seminar Talk, Initial Exploratory Analysis of Synthetic Storm Tracks

SAMSI Model Uncertainty Program Data Fusion Working Group - SAMSI [Oct.2018]
Seminar Talk, Data Fusion for Music Mining

International Conference on Advances in Interdisciplinary Statistics and Combinatorics - AISC [Oct.2018]
Invited, Machine Learning for Music Mining with LDA Model, SAMSI Academic Session

Data Science Research Group in Rochester Institute of Technology - DSRG [Sep.2018]
Seminar Talk, Statistical Aspects of Music Mining

Cornell Day of Statistics 2018 - Cornell [Sep.2018]
Poster Session, Bayesian and Unsupervised Machine Learning Machines for Jazz Music Analysis

Joint Statistical Meetings 2018 -Vancouver, Canada - JSM [Jul.2018]
Contributed, Bayesian and Unsupervised Machine Learning Machines for Jazz Music Analysis

7th Annual Conference of the UPSTAT New York Chapters of ASA - UPSTAT ASA [Apr.2018]
Contributed, Music Mining In Topic Modeling Approach For Improvisational Learning

Graduate Seminar in Rochester Institute of Technology - RIT [Feb.2018]
Seminar Talk, Topic Modeling with LDA Tutorial

2017:
Graduate Showcase in Neuroscience and Signal Processing Session - RIT [Nov.2017]
Contributed, Statistical Challenges of Echo State Networks

6th Annual Conference of the UPSTAT New York Chapters of ASA - UPSTAT ASA [Apr.2017]
Contributed, Statistical Aspects about Echo State Networks

Using Format