Jiazhao Li 李佳钊
About Me
I am currently a Research Associate in NLP4Health Group supervised by Prof.V.G.Vinod Vydiswaran at University of Michigan. I am interested in NLP, IR and CV models and applications in health-care domain. I am applying Ph.D programs related with NLP.
ResumeUniversity of Michigan
NLP, IR, CV
jiazhaol AT umich DOT edu
Shenyang, China
Video
This is one interesting HCI game I designed using computer vision. Thank my teammates, we got hightest score in EECS 442
Research and Project
Prescription Transcription using Machine Translation
Aug 2019 - Current
Electronic Transcription of Prescriptions (ETP) in health care has been suggested to have positive impact for prescribing process in safety, quality, efficiency for both prescribers and pharmacists. We are trying to use Deep learning method to automatically transcripe prescription to pharmacy instructions. More details in following paper.
How about Avengers: Endgame? Movie revenue prediction with hierarchical model[5]
Jan 2019 - Apr 2019
We found movie revenue followed two Gaussion Distrubution: High revenue and Low revenue. Based on this obeservation, we trained High-low binary Random Forest Classifier (RFC performed best) based on labels from Gaussion Mixture Model (GMM) clustering. After classification, we trained movie Gradient Boosting Regression (GBR performed best) separately and using Back-off strategy to solving cold start problem. We also tested generalization of our classification + regression model on Europe Soccer Players.
Identify Medication Relations from Clinical Narratives[4]
Nov 2018 - Mar 2019
Identifying medication relations between drugs and associated attributes automatically from clinical narratives can help develop advanced tools for decision support. We investigate the strengths of neural network models to identify eight medication relations. We find that relation extraction is sensitive to complexity of data patterns as well as model capacity. Our results show that Bi-LSTM models achieved an overall F1 score of 0.892 on eight tasks, outperforming SVM and CNN models.
Video Segments Retrieval System based on Attentive Convolutionsl Neural Network[3]
Sep 2018 - Dec 2018
Traditional methods simply relay on manual hash tags, title and description of video compared with free text query, which suffers from high bias and low accuracy. We proposed a novel video segments retrieval system based on architecture Attentive Convolutional Nerual Network (ACNN), achieving state-of-the-art performance on TACoS dataset.
Baby blues: Analyzing Facebook and health forums on Pregnancy[2]
Aug 2018 - Sep 2018
In the study, we systematically analyzed questions posted on pregnancy forums by young mothers and contrasted it to a unique dataset of Facebook posts by expecting adolescent women. Distribution of themes across these platforms showed significant differences on roles played by the two platforms. We concluded that Facebook is chosen as a self-expression place to seek emotional support while health forum served as professional information provider.
PageRank++: European Soccer Team Ranking Prediction[1]
Jan 2018 - Apr 2018
Prediction of soccer competition results is always an atractive topic. However, traditional ranking method, Network ofNetworks (NoN), can only capture the similarity between playersor teams rather than the win-lose relationship. Broadly used method Deep Neural Network (DNN) cannot converge within limited dataset. In this work, we proposed a graph-based method PageRank++ to predict the rank of teams in a league. Our algorithm converges faster without using large dataset compared with DNN and higher accuracy compared with baselines, Naive Rank and Naive PageRank.
Work Experience
Research Associate @ Michigan Medicine 
July 2019 - Current
I am responsible for research project in Machine Translation / Simplification in Health Care domain and techinical part User study Web application developing. More details and writings in Research above. My work is supervised by Prof Vinod.
Research Assistant @ Michigan Medicine
Aug 2018 - May 2019
I did research projects about Topic Model on social medias, Deep Learning Models on clinical notes. More details and writings in Research above. My work was supervised by Prof. Vinod.
Grader @ Michigan Engineering 
Jan 2019 - Apr 2019
I was grader of lecture EECS 498 Information Retrieval and Web Search taught by Prof. Rada Mihalcea. Main resposiblity is to grade codes and reports.
Education
University of Michigan
Sep 2017 - May 2019
Ann Arbor, MI, USA
Master Electrical & Computer Engineering
GPA: 3.856/4.00
Nankai University
Sep 2013 - Jun 2017
Tianjin, China
B.S Electrical Engineering
GPA: 88/100