Tiantian Feng
SAIL Lab, University of Southern California. tiantiaf@usc.edu
This amazing picture was taken by my wife at Skyline Trail, Mount Rainier, 2023.
PS: Prepare enough water for this trail but make sure you are not the one carrying it.
My name is Tiantian Feng, and I grew up in Leshan, China, which is famously for Leshan Giant Buddha. I studied both in Chengdu (both middle school and high school at Chengdu Foreign Language School) and Nanjing (Nanjing University of Posts and Telecommunications, undergraduate). I obtained my master degree at the University of Southern California afterwards. I recently completed my Ph.D. in the Thomas Lord Department of Computer Science at University of Southern California in 2023. I am fortunate to be advised by Professor Shrikanth Narayanan, a globally recognized scientist in speech modeling, linguistics, affective computing, and human understanding.
My research focuses on leveraging sensors and computational methods for understanding natural human behaviors, also with a particular emphasis on inclusiveness and privacy. My research invovles applications such as speech understanding, multimodal understanding, and bio-signal processing, etc. Additionally, I have hands-on experience in industrial sensor design and deploying sensors in research studies. I have interned at both Meta and Amazon as the research scientist.
I am currently a postdoc researcher in SAIL lab at USC, and I am actively looking for tenure-track or similar positions in academia. Don’t hesitate to contact me if you would like to collaborate.
News
Jun 14, 2024 | 3 papers accepted at INTERSPEECH 2024! |
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Jun 10, 2024 | Will serve as a session chair for “Sensing for Sleep, Stress, and Emotion” at EMBC 2024! |
Apr 22, 2024 | Receive IEEE EMBC NextGen Scholar Award! |
Apr 15, 2024 | 1 conference paper got accepted to 2024 EMBC! Congrats to all co-authors! |
Apr 12, 2024 | Give 2 oral and 1 poster presentation at 2024 ICASSP for 2 conference papers and 1 workshop paper (all first author)! My colleagues presented 2 ICASSP conference papers that I collabrated with! |
Apr 05, 2024 | I will be hosting Trustworthy Speech Processing Satellite Workshop at ICASSP 2024, April 15th, 2024 from 2:00 PM to 5:30 PM KST (Room AB203)! Please join us if you are interested in making speech processing safer, more private, and more inclusive! |
Jan 29, 2024 | Received 2024 ICASSP travel grant! |
Dec 15, 2023 | 4 conference papers and 1 workshop paper got accepted to 2024 ICASSP! Congrats to all co-authors! |
Dec 11, 2023 | Successfully defended my Ph.D. thesis: Generative Foundation Model Assisted Privacy-Enhancing Computing in Human-Centered Machine Intelligence! |
Oct 27, 2023 | Received Outstanding Poster Presentation - 2023 Electrical Engineering Research Festival - Ming Hsieh Department of Electrical and Computer Engineering. |
Selected Publications
- ACM Multimedia DatasetMM-AU: Towards Multimodal Understanding of Advertisement VideosIn Proceedings of the 31st ACM International Conference on Multimedia , 2023
- Preprint Generative AICan Text-to-image Model Assist Multi-modal Learning for Visual Recognition with Visual Modality Missing?arXiv preprint arXiv:2402.09036, 2024
- Voice Privacy Generative AIUnlocking Foundation Models for Privacy-Enhancing Speech Understanding: An Early Study on Low Resource Speech Training Leveraging Label-guided Synthetic Speech ContentarXiv preprint arXiv:2306.07791, 2023
- Preprint Generative AIGPT-FL: Generative pre-trained model-assisted federated learningarXiv preprint arXiv:2306.02210, 2023
- Journal TrustworthinessA Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and FairnessAPSIPA Transactions on Signal and Information Processing, 2023
- ICASSP TSP 2024 Federated LearningPartial federated learning: Unlocking non-biometric text information sharing for federated learning2024
- Preprint WearablesUnderstanding Stress, Burnout, and Behavioral Patterns in Medical Residents Using Large-scale Longitudinal Wearable RecordingsarXiv preprint arXiv:2402.09028, 2024
- ACM Transactions WearablesTemporal dynamics of workplace acoustic scenes: Egocentric analysis and predictionIEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021
- ICASSP 2019 WearablesDiscovering optimal variable-length time series motifs in large-scale wearable recordings of human bio-behavioral signalsIn ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2019