Haifeng Chen, Data Science, NEC Labs

Haifeng Chen

Data Science and
Systems Security Department

NEC Laboratories America
4 Independence Way
Princeton, NJ 08540
Email: myfirstname@nec-labs.com

Dr. Haifeng Chen is heading the Data Science and Systems Security Department at NEC Laboratories America in Princeton, New Jersey. He and his team members are working on the various aspects of big data research including data management and mining, artificial intelligence, software and system security, smart services and platforms. Haifeng has served in the program committee for a number of top conferences, such as SigKDD, AAAI, IEEE BigData, and has been in the panel of NSF programs. He has co-authored more than a hundred conference/journal publications including best papers from top conferences such as SigKDD, and has over 60 patents granted. Many of the research results have lead to advanced solutions and products for various industrial domains including IT & data centers, network security, power plants, petroleum , satellite, natural disaster, finance, and retail businesses. As a result of his significant business contributions, Haifeng has received a large number of awards in the past years including the 2014 " NEC Contributors of the Year " - the highest and most prestigious award from NEC Corp.

News We have several researcher positions available. If interested, please submit your CV and research statement through our career center: Researcher (Data Science), Researcher (System Security), Data Scientist.

News We have several summer/fall/winter intern positions available. If interested, please submit your CV through our career center.

Congrats We have four papers accepted by 2023 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-23)

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations
Privacy Preserved Interpretable Skill Learning via Imitation
Incremental Causal Graph Learning for Online Unsupervised Root Cause Analysis
Interdependent Causal Networks for Unsupervised Root Cause Localization (ADS-track)

Congrats Our paper "Uncertainty-Aware Bootstrap Learning for Joint Extraction on Distantly-Supervised Data" has been accepted by the Annual Meeting of the Association for Computational Linguistics (ACL) (ACL-23)

Congrats Our paper "Personalized Federated Learning under Mixture of Distributions" has been accepted by the Fortieth annual conference on machine learning (ICML-23)

News Our collaboration with Lockheed Martin is recognized by NASA, who selected our SIAT technology as one of the five AI techniques that support their Artemis mission. ( Link)

News Our Skill Aquisition Learning (SAiL) technique appeared in Nikkei xTECH news, regarded as NEC's unique imitation learning technology. ( Link)

Congrats Our paper "Multi-Label Temporal Evidential Neural Networks for Early Event Detection" has been accepted by 2023 IEEE International Conference on Acoustics, Speech and Signal Processing. (ICASSP-23)

Congrats Our paper "Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning" has been published at IEEE Transactions on Neural Networks and Learning Systems, 33(6): 2365-2377, 2022

Congrats Our project "complex system management" won the 69th Electrical Science and Engineering Promotion Award in Japan. (Link 1, Link 2)