Tingfeng Li (She/Her)
tli@nec-labs.com

I am a Researcher at NEC Laboratories America, where I work on zero-shot/few-shot learning, generative model, LLM/VLM with their applications to real-world problems. I obtained my Ph.D. degree in Department of Computer Science at Rutgers University, advised by Distinguished Professor Dimitris N. Metaxas. I earned my Master’s degree in ECE at Shanghai Jiao Tong University in Shanghai, China, where I worked with Professor Xu Zhao.

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Education

Sep. 2018 - May 2023
Rutgers, The State University of New Jersey - New Brunswick. Piscataway, NJ
Ph.D. Candidate in Computer Science
  • Supervised by Prof. Dimitris Metaxas
  • PhD Thesis: "Deep Learning with Limited Data"
  • GPA: 4.0/4.0
Sep. 2015 - Mar. 2018
Shanghai Jiao Tong University. Shanghai, China
M.E. in Control Engineering
  • Supervised by Prof. Xu Zhao
  • Master Thesis: "Subcategory-aware CNN for object detection and head pose estimation"
Sep. 2011 - Jun. 2015
University of Electronic Science and Technology of China. Chendu, China
B.E. in Automation Engineering
  • GPA: 3.93/4.00

Experience

Feb. 2023 - Present
Optical Networking + Sensing, NECLA, Princeton, US.
Researcher
  • Representation learning, transfer learning, domain adaptation
  • Generative model, LLM/VLM
  • Signal processing and sensing applications
Sep. 2022 - Jan. 2023
Optical Networking + Sensing, NECLA, Princeton, US.
Research Intern. Mentor: Dr. Shaobo Han
  • Vehicle Run-off-road Detection by Fiber Optic Sensing with Anomaly Detection
May 2022 - Aug. 2022
Fashion Science, Amazon, Seattle, US.
Applied Scientist Intern. Mentor: Dr. Lian Xiong
  • New Arrivals Popularity Prediction for Recommendation
Sep. 2021 - May 2022
Optical Networking + Sensing, NECLA, Princeton, US.
Research Intern. Mentor: Dr. Shaobo Han
  • Zero-shot Domain Adaptation
May 2021 - Aug. 2021
Fashion Science, Amazon, Seattle, US.
Applied Scientist Intern. Mentor: Dr. Peng Yang
  • Video Classification and Compilation
May 2020 - Aug. 2020
Optical Networking + Sensing, NECLA, Princeton, US.
Research Intern. Mentor: Dr. Shaobo Han
  • Vehicle Run-off-road Detection by Fiber Optic Sensing and Machine Learning
Sep. 2018 - May 2021
Computer Science Department, Rutgers Univeristy. Piscataway, NJ, US.
Research Assistant. Superviser: Prof. Dimitris N. Metaxas.
  • American Sign Language Recognition
  • Model Robustness
  • Automatic Data Augmentation
Sep. 2019 - May 2020
Computer Science Department, Rutgers Univeristy. Piscataway, NJ, US.
Teaching Assistant.
  • Compilers (CS415) - Spring 2020
  • Principles of Programming Languages (CS314) - Fall 2019

Research

Deep Learning-Based Intrusion Detection and Impulsive Event Classification for Distributed Acoustic Sensing Across Telecom Networks
Shaobo Han, Ming-Fang Huang, Tingfeng Li, Jian Fang, Zhuocheng Jiang, Ting Wang
Journal of Lightwave Technology (JLT), Vol. 42, No.12 (2024) 4167-4176
[Paper] [Link] [Bibtex] 
              @ARTICLE{10530902,
                author={Han, Shaobo and Huang, Ming-Fang and Li, Tingfeng and Fang, Jian and Jiang, Zhuocheng and Wang, Ting},
                journal={Journal of Lightwave Technology}, 
                title={Deep Learning-Based Intrusion Detection and Impulsive Event Classification for Distributed Acoustic Sensing Across Telecom Networks}, 
                year={2024},
                volume={42},
                number={12},
                pages={4167-4176},
                keywords={Cables;Sensors;Task analysis;Optical fiber cables;Optical fiber networks;Acoustics;Monitoring;Acoustic event classification;deep learning;distributed optical fiber sensing;gunshot detection;intrusion detection;machine learning;network field experiment},
                doi={10.1109/JLT.2024.3401244}}
Learning Transferable Reward for Query Object Localization with Policy Adaptation
Tingfeng Li, Shaobo Han, Martin Renqiang Min, Dimitris Metaxas
International Conference on Learning Representations (ICLR), 2022
[Paper] [Slides] [Talk] [Code] [Bibtex] 
@inproceedings{
li2022learning,
title={Learning Transferable Reward for Query Object Localization with Policy Adaptation},
author={Tingfeng Li and Shaobo Han and Martin Renqiang Min and Dimitris N. Metaxas},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=92tYQiil17}
}
Vehicle Run-Off-Road Event Automatic Detection by Fiber Sensing Technology
Tingfeng Li, Yuheng Chen, Ming-Fang Huang, Shaobo Han, Ting Wang
Optical Fiber Communications Conference and Exhibition (OFC), 2021
[Paper] [Bibtex] 
@INPROCEEDINGS{9489744,
author={Li, Tingfeng and Chen, Yuheng and Huang, Ming-Fang and Han,
Shaobo and Wang, Ting},
booktitle={2021 Optical Fiber Communications Conference and Exhibition (OFC)},
title={Vehicle Run-off-Road Event Automatic Detection by Fiber Sensing Technology},
year={2021},  volume={},  number={},  pages={1-3},  doi={}}
}
game AdaTransform: Adaptive Data Transformation
Zhiqiang Tang, Xi Peng, Tingfeng Li, Yizhe Zhu, Dimitris Metaxas
International Conference on Computer Vision (ICCV), 2019 (oral)
[Paper] [Bibtex] 
@InProceedings{Tang_2019_ICCV,
author = {Tang, Zhiqiang and Peng, Xi and Li, Tingfeng and Zhu, Yizhe and Metaxas, Dimitris N.},
title = {AdaTransform: Adaptive Data Transformation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}
Simultaneous Face Detection and Head Pose Estimation: A Fast and Unified Framework
Tingfeng Li, Xu Zhao
Asian Conference on Computer Vision (ACCV), 2018
[Paper] [Bibtex] 
@inproceedings{li2018simultaneous,
  title={Simultaneous Face Detection and Head Pose Estimation: A Fast and Unified Framework},
  author={Li, Tingfeng and Zhao, Xu},
  booktitle={Asian Conference on Computer Vision},
  pages={187--202},
  year={2018},
  organization={Springer}
}
Cost Efficient Subcategory-aware CNN for Object Detection
Tingfeng Li, Xu Zhao
International Conference on Image Processing (ICIP), 2017
[Paper] [Bibtex] 
@INPROCEEDINGS{8297074,
author={Li, Tingfeng and Zhao, Xu},
booktitle={2017 IEEE International Conference on Image Processing (ICIP)},
title={Cost efficient subcategory-aware CNN for object detection},
year={2017},
pages={4202-4206},
doi={10.1109/ICIP.2017.8297074}}