I am currently a Ph.D. Student in the Department of Computer Science at the University of Virginia, supervised by Professor Aidong Zhang. My research interests are in the general areas of machine learning and data mining, with an emphasis on developing novel techniques to build trustworthy learning systems that are explainable, robust, private, and fair. I am also interested in designing effective machine learning and data mining algorithms to deal with complex data with both strong empirical performance and theoretical guarantees.

News

• 05/2022: One paper is accepted by KDD 2022.
• 12/2021: One paper is accepted by AAAI 2022.
• 11/2021: One paper is accepted by ACM TKDD.
• 10/2021: Selected as one of the Rising Stars in Data Science at UChicago.
• 09/2021: One paper is accepted by SenSys 2021.
• 09/2021: Invited to serve as a PC member for The Web Conference 2022.
• 08/2021: Selected as one of the Rising Stars in EECS at MIT.
• 08/2021: Invited to serve as a PC member for AAAI 2022.
• 08/2021: One paper is accepted by CIKM 2021.
• 05/2021: Received John A. Stankovic Graduate Research Award.
• 04/2021: One paper is accepted by IJCAI 2021.
• 10/2020: Two papers are accepted by BIBM 2020.
• 10/2020: Invited to serve as a PC member for The Web Conference 2021.
• 08/2020: Received the Sture G. Olsson Fellowship in Engineering.
• 08/2020: Invited to serve as a PC member for AAAI 2021.
• 05/2020: One paper is accepted by KDD 2020.
• 05/2020: Invited to serve as a PC member for IEEE BigData 2020.

Publications

• Jianhui Sun, Mengdi Huai, Kishlay Jha, and Aidong Zhang, "Demystify Hyperparameters for Stochastic Optimization with Transferable Representations", the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2022), Washington DC, USA, August 2022. (Acceptance Rate: 254/1695=15%). [PDF]
  
• Mengdi Huai, Jinduo Liu, Chenglin Miao, Liuyi Yao, and Aidong Zhang, "Towards Automating Model Explanations with Certified Robustness Guarantees", the 36th AAAI Conference on Artificial Intelligence (AAAI 2022), Vancouver, Canada, February 2022. (Acceptance Rate: 1349/9020=15%). [PDF]
  
• Mengdi Huai, Tianhang Zheng, Chenglin Miao, Liuyi Yao, and Aidong Zhang, "On the Robustness of Metric Learning: An Adversarial Perspective", accepted by ACM Transactions on Knowledge Discovery from Data (TKDD). [PDF]
  
• Yi Zhu, Chenglin Miao, Foad Hajiaghajani, Mengdi Huai, Lu Su, and Chunming Qiao, "Adversarial Attacks against LiDAR Semantic Segmentation in Autonomous Driving", the 19th ACM Conference on Embedded Networked Sensor Systems (SenSys 2021), November 2021. (Acceptance Rate: 25/139=17.9%). [PDF]
  
• Liuyi Yao, Yaliang Li, Sheng Li, Mengdi Huai, Aidong Zhang, and Jing Gao, "SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation", the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 2021. [PDF]
  
• Zhiyu Xue, Shaoyang Yang, Mengdi Huai, and Di Wang, "Differentially Private Pairwise Learning Revisited", the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), August 2021. (Acceptance Rate: 587/4204=13.9%). [PDF]
  
• Mengdi Huai, Chenglin Miao, Jinduo Liu, Di Wang, Jingyuan Chou, and Aidong Zhang, "Global Interpretation for Patient Similarity Learning", the 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2020), Online, December, 2020. (Acceptance Rate: 19.4%). [PDF]
  
• Jingyuan Chou, Stefan Bekiranov, Chongzhi Zang, Mengdi Huai, and Aidong Zhang, "Analysis of Meta-Learning Approaches for TCGA Pan-cancer Datasets", the 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2020), Online, December, 2020. (Acceptance Rate: 19.4%). [PDF]
  
• Mengdi Huai, Jianhui Sun, Renqin Cai, Liuyi Yao, and Aidong Zhang, "Malicious Attacks against Deep Reinforcement Learning Interpretations", the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020), San Diego, USA, August, 2020. (Acceptance Rate: 216/1279=16.9%, Best Paper Runner-up). [PDF]
  
• Mengdi Huai, Di Wang, Chenglin Miao, and Aidong Zhang, "Towards Interpretation of Pairwise Learning", the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA, February 2020. (Acceptance Rate: 1591/7737=20.6%). [PDF]
  
• Mengdi Huai, Di Wang (co-first author), Chenglin Miao, Jinhui Xu, and Aidong Zhang, "Pairwise Learning with Differential Privacy Guarantees", the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA, February 2020. (Acceptance Rate: 1591/7737=20.6%). [PDF]
  
• Jinduo Liu, Junzhong Ji, Guangxu Xun, Liuyi Yao, Mengdi Huai, and Aidong Zhang, "EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks", the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, USA, February 2020. (Acceptance Rate: 1591/7737=20.6%). [PDF]
  
• Mengdi Huai, Chenglin Miao, Yaliang Li, Qiuling Suo, Lu Su, and Aidong Zhang, "Learning Distance Metrics from Probabilistic Information", ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 14, No. 5, 2020. [PDF]
  
• Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang, "ACE: Adaptively Similarity-preserved Representation Learning for Individual Treatment Effect Estimation", the 19th IEEE International Conference on Data Mining (ICDM 2019), Beijing, China, November 2019. (Acceptance Rate: 194/1046=18.5%). [PDF]
  
• Mengdi Huai, Di Wang, Chenglin Miao, Jinhui Xu, and Aidong Zhang, "Privacy-aware Synthesizing for Crowdsourced Data", the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, August 2019. (Acceptance Rate: 850/4752=17.9%). [PDF]
  
• Mengdi Huai, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, and Aidong Zhang, "Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm", the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China, August 2019. (Acceptance Rate: 850/4752=17.9%). [PDF]
  
• Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang, "DTEC: Distance Transformation Based Early Time Series Classification", the 2019 SIAM International Conference on Data Mining (SDM 2019), Alberta, Canada, May 2019. (Acceptance Rate: 90/397=22.7%). [PDF]
  
• Mengdi Huai, Chenglin Miao, Yaliang Li, Qiuling Suo, Lu Su, and Aidong Zhang, "Metric Learning from Probabilistic Labels", the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, United Kingdom, August 2018. (Acceptance Rate: 107/983=10.9%). [PDF]
  
• Chenglin Miao, Qi Li, Lu Su, Mengdi Huai, Wenjun Jiang, and Jing Gao, "Attack under Disguise: An Intelligent Data Poisoning Attack Mechanism in Crowdsourcing", the World Wide Web Conference (WWW 2018), Lyon, France, April 2018. (Acceptance Rate: 171/1155=14.8%). [PDF]
  
• Mengdi Huai, Chenglin Miao, Qiuling Suo, Yaliang Li, Jing Gao, and Aidong Zhang, "Uncorrelated Patient Similarity Learning", the 18th SIAM International Conference on Data Mining (SDM 2018), San Diego, USA, May 2018. [PDF]
  
• Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang, "Representation Learning for Treatment Effect Estimation from Observational Data", the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montreal, Canada, December 2018. (Acceptance Rate: 1011/4856 = 20.82%). [PDF]
  
• Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Mengdi Huai, and Aidong Zhang, "Multi-Task Sparse Metric Learning for Monitoring Patient Similarity Progression", the 18th IEEE International Conference on Data Mining (ICDM 2018), Singapore, November, 2018. [PDF]
  
• Chenglin Miao, Qi Li, Houping Xiao, Wenjun Jiang, Mengdi Huai, and Lu Su, "Towards Data Poisoning Attacks in Crowd Sensing Systems", the 19th ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2018), Los Angeles, USA, June 2018. (Acceptance Rate: 30/178=16.8%, Best Paper Award Nominee). [PDF]
  
• Di Wang, Mengdi Huai, and Jinhui Xu, "Differentially Private Sparse Inverse Covariance Estimation", the 6th IEEE Global Conference on Signal and Information Processing (GlobalSip 2018), California, USA, November, 2018. [PDF]
  
• Qiuling Suo, Fenglong Ma, Ye Yuan, Mengdi Huai, Weida Zhong, Jing Gao, and Aidong Zhang, "Deep Patient Similarity Learning for Personalized Healthcare", IEEE Transactions on NanoBioscience (TNB), Vol. 17, No. 3, 2018. [PDF]
  
• Qiuling Suo, Fenglong Ma, Ye Yuan, Mengdi Huai, Weida Zhong, and Aidong Zhang, "Personalized Disease Prediction Using A CNN-Based Similarity Learning Method", the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2017), Kansas City, MO, USA, November, 2017. [PDF]
  
• Mengdi Huai, Liusheng Huang, Wei Yang, Lu Li, and Mingyu Qi, "Privacy-preserving Naive Bayes Classification", the 8th International Conference on Knowledge Science, Engineering and Management (KSEM 2015), Chongqing, China, October 2015. [PDF]
  
• Mengdi Huai, Liusheng Huang, Yu-e Sun, and Wei Yang, "Efficient Privacy-Preserving Aggregation for Mobile Crowdsensing", the IEEE 5th International Conference on Big Data and Cloud Computing (BDCloud 2015), Dalian, China, August 2015. [PDF]
  
• Jun Wang, Shangfei Wang, Mengdi Huai, Chongliang Wu, Zhen Gao, Yue Liu and Qiang Ji "Capture Expression-dependent AU Relations for Expression Recognition", the IEEE International Conference on Multimedia and Expo Workshops (ICMEW 2014), Chengdu, China, July 2014. [PDF]
  

Selected Awards

• Rising Star in EECS at MIT, 2021
• Rising Star in Data Science at UChicago, 2021
• John A. Stankovic Graduate Research Award, 2021
• Sture G. Olsson Fellowship in Engineering, 2020
• Best Paper Runner-up, KDD, 2020
• Student Registration Award, KDD, 2020
• Student Scholarship, AAAI, 2020
• Student Travel Award, IJCAI, 2019
• Student Travel Award, KDD, 2018
• National Scholarship for Graduate Students, Ministry of Education of P. R. China, 2016

Professional Activities

• Program Committee Member
  2023: AAAI (SPC), WSDM
  2022: KDD, AAAI, WWW, CIKM, ICDM, BigData
  2021: AAAI, WWW
  2020: AAAI, BigData
  
• Journal Reviewer
  IEEE Transactions on Mobile Computing (TMC)
  IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
  IEEE Internet of Things (IoT) Journal
  IEEE Access
  
• Conference External Reviewer
  SIGKDD, SIGMOD, VLDB, NeurIPS, ICML, AAAI, IJCAI, WWW, WSDM, CIKM, ICDM, BigData, BIBM, etc.