 |
Yuanxun ZhangPhD Candidate in Computer ScienceDepartment of Electrical Engineering and Computer Science University of Missouri at Columbia Email: yzd3b AT mail.missouri.edu |
About Me
- I'm PhD candidate in computer science at University of Missouri - Columbia, advised by Dr. Calyam Prasad. Before that, I worked in Huawei as software engineer.
- I’m interested in the theory and practice of understanding and learning from data to make better decisions or quantifying uncertainty, for solving these problems involving deep learning, machine learning, statistical learning, probabilistic graphical model, inference algorithm, and information retrieval.
News
- 2020/02/02: A paper was accepted by IEEE Sixth International Conference on Big Data Computing Service.
- 2020/01/14: I will start a research intern at JD Digits AI Lab on the NLP project.
- 2018/12/13: I presented my paper at IEEE Big Data 2018 workshop on Conversational Agents and Chatbots with Machine Learning (ChatbotML) in Seattle.
- 2018/11/13: A paper was accepted by IEEE Big Data 2018 workshop on Conversational Agents and Chatbots with Machine Learning (ChatbotML).
Rsearch Projects
Current Projects
- ScholarFinder: Knowledge Embedding using Deep Generative Model
- Embed scholars’ knowledge using the Variational Autoencoder (VAE) based on their publications.
- Design a novel negative sampling scheme to deal with unbalanced labels issue.
- Use pre-trained knowledge embeddings for predicting whether a scholar is suitable for a proposed task or not using DNN model.
- Probabilistic Topic Model for Knowledge Discovery in Scientific Communities
- Implement Python scripts to extract papers’ abstracts from online journal archives.
- Extend Latent Dirichlet Allocation (LDA) model to automatically discover relationships among research tools, research datasets and research topics from large collections of scientific publi- cations, which can guide scientists or researchers to choose suitable tools or datasets for their research.
- Derive the inference algorithm for inferring latent variables of our model using MCMC (Gibbs sampling).
- Design trend analysis algorithm to understand the trend of tools or datasets over years (such as which tools or datasets are more popular at certain years?)
Industry Experience
- 2020/01 - 2020/04: research intern at JD Digits AI Lab on the NLP project.
- 2006/09 - 2013/06: software engineer at Huawei.
Publications
- Zhang, Y., Swathi, S. S, Calyam, P., “Scholarfinder: Knowledge embedding based recom- mendations using a deep generative mode”, In 2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService), 2020.
- Zhang, Y., Calyam, P., Joshi, T., Nair, S., and Xu, D, “Domain-specific Topic Model for Knowledge Discovery through Conversational Agents in Data Intensive Scientific Communities”, IEEE International Workshop on Conversational Agents and Chatbots with Machine Learning (ChatbotML), in conjunction with IEEE Big Data, 2018.
- Dickinson, M., Debroy, S., Calyam, P., Valluripally, S., Zhang, Y., Antequera, R.B., Joshi, T., White, T. and Xu, D, “Multi-cloud Performance and Security Driven Federated Workflow Management”, IEEE Transactions on Cloud Computing, 2018.
- Neupane, R. L., Neely, T., Chettri, N., Vassell, M., Zhang, Y., Calyam, P., and Durairajan, R., “Dolus: Cyber Defense using Pretense against DDoS Attacks in Cloud Platforms”, In Proceedings of the 19th International Conference on Distributed Computing and Networking, 2018.
- Zhang, Y., Calyam, P., Debroy, S. and Nuguri, S.S, “Social Plane for Recommenders in Network Performance Expectation Management”, IEEE Transactions on Network and Service Management, 2017.
- Zhang, Y., Debroy, S., and Calyam, P, “Network-wide anomaly event detection and diagnosis with perfsonar”, IEEE Transactions on Network and Service Management, 2016.
- Zhang, Y., Debroy, S., and Calyam, P, “Network measurement recommendations for performance bottleneck correlation analysis”, In 2016 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), 2016.
- Dickinson, M., Debroy, S., Calyam, P., Valluripally, S., Zhang, Y., Joshi, T. and Xu, D., “End-to-End Security Formalization and Alignment for Federated Workflow Management”, In 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), 2016.
- Liu, Y., Khan, S.M., Wang, J., Rynge, M., Zhang, Y., Zeng, S., Chen, S., dos Santos, J.V.M., Valliyodan, B., Calyam, P.P. and Merchant, N., “PGen: large-scale genomic variations analysis workflow and browser in SoyKB”, In BMC bioinformatics. BioMed Central., 2016.
- Zhang, Y., Calyam, P., Debroy, S., and Sridharan, M., “PCA-based network-wide correlated anomaly event detection and diagnosis”, In 2015 11th International Conference on the Design of Reliable Communication Networks (DRCN) (pp. 149-156), 2016.