About me
I am a fourth-year PhD candidate in Computer Engineering at Northwestern University, part of the IDEAS Lab and advised by Dr. Qi Zhu.
My research is focused on human-centric applications that bridge computer science and health. Specifically, I develop machine learning techniques for real-world challenges involving audio, healthcare, and time-series sensor data. These applications are pervasive but often come with challenges in data analysis and model development. I aim to design robust algorithms that handle issues like data quality, sparsity, and resource constraints. A significant part of my work explores the trade-offs between personalization and generalization in algorithm design, with an emphasis on making technology more inclusive for underrepresented users (e.g., atypical speakers in voice technology, and skin-tone diversity in optical heart rate monitoring). In addition to model performance, I prioritize explainability and resource efficiency.
Before my PhD, I worked as an IC design engineer at Analog Devices Inc., developing formal verification methods for application-specific ICs. I hold a Masters by Research in Electrical Engineering from Indian Institute of Technology, Madras, where I designed a sensing and algorithms framework for cardiac wearables.
You can reach me at payalmohapatra2026 at u dot northwestern dot edu.
Link to my CV (last updated February 2025)
Ongoing Projects
Learning from Irregular and Heterogenous Modalities
Investigating methods to model the underlying process dynamics for irregular time-series, ranging from uniformly sampled to sparse or missing variates, to learn task-agnostic representations while modeling the inter-modality interactions.
Practitioner's Guide to Manufacturing Workplace Safety
Collaborating with Boeing and MxD to create a browsable repository of COTS sensors and wearable-data analytics to enhance workplace safety by quantifying risk factors. Assessing the validity of off-the-shelf pose analytics for extracting ergonomic risk metrics (RULA/REBA scores).
News
- [February 2025] - Submited our paper on surface-EMG based silent-speech recognition using LLMs to ACL.
- [Januaray 2025] - Submited our paper on head-orientation based acoustic zones’ localization to IMWUT.
- [January, 2025] - Submited our paper on phase driven domain generalization for time series to TMLR.
- [December 2024] - Successfully passed my PhD Prospectus examination – 2/3 of the journey complete!
- [October 2024] - Our paper Wearable Network for Multi-Level Physical Fatigue Prediction in Manufacturing Workers is accepted in PNAS Nexus journal. Featured by tech news outlets like TechXplore and Popular Science.
- [August, 2024] - Excited to be selected as the EECS Rising Star 2024! Invited to the 2-day workshop hosted at MIT in October. Read more in this article by Northwestern.
- [June, 2024] - Started my summer internship with Meta Reality Labs as Research Scientist.
- [June, 2024] - Our paper on Missingness-resilient Video-enhanced Multimodal Disfluency Detection is accepted and chosen for oral presentation at InterSpeech’24.
- [February, 2024] - My internship work with Meta Reality Labs on efficient event detection on smart glasses – Non-verbal Hands-free Control for Smart Glasses using Teeth Clicks, is now live!
- [October, 2023] - Corresponding with Meta Reality Labs, Audio Research group as a part-time student researcher.
- [July, 2023] - Our paper on the Effect of Attention and Self-Supervised Speech Embeddings on Non-Semantic Speech Tasks has been accepted for ACM Multimedia 2023 Multimedia Grand Challenges Track.
- [June, 2023] - I will be interning with Meta Reality Labs, Redmond, WA this summer as a Research Scientist. Reach out if you are here and want to collaborate (or just catch up over coffee).
- [May, 2023] - We are participating in the ACM Multimedia 2023 Computational Paralinguistics Challenge (ComParE).
- [February, 2023] - Our paper on EFFICIENT STUTTERING EVENT DETECTION USING SIAMESE NETWORKS is accepted in ICASSP’23.
- [February, 2023] - Secured third place in e-Prevention: Person Identification and Relapse Detection from Continuous Recordings of Biosignals Challenge in ICASSP’23. Invited to present a paper on methodology - PERSON IDENTIFICATION WITH WEARABLE SENSING USING MISSING FEATURE ENCODING AND MULTI-STAGE MODALITY FUSION.
- [December, 2022] - Demonstrated final working prototype of fatigue prediction in workers with near-real-time visualisation at the Boeing, Everett, Washington, factory floor.
- [August, 2022] - Demonstrated initial working prototype of fatigue prediction in workers with near-real-time visualisation at the John Deere, Knoxville, Tennesse, factory floor.
- [July, 2022] - Presented Speech Disfluency Detection with Contextual Representation and Data Distillation at Intelligent Acoustic Systems and Applications co-located with MobiSys’22.
- [April, 2022] - Presented poster on Speech Disfluency Detection under data-constraints at CRA-WP grad cohort at New Orleans, Louisiana.
Services
- Reviewer: ICASSP’25, ICLR’25, NeurIPS’24 (TSALM workshop), IMWUT’24, IROS’24, ICASSP’24
- External Reviewer: ASP-DAC’24, EMSOFT’23, ICCPS’23, NSys’22
- Book Reviews: Cambridge University Press early reader’s reviewing
- Organize biweekly inter-laboratory Cyber-Physical Systems study group at Northwestern.
- Active participant in the ML reading group at Northwestern, covering topics like XGBoost, MultiModal Learning, and Non-Stationary Transformers.
- Mentoring:
- 2024: Xiaoyuan Zhang, Talia-Ben Naim (MS students, Computer Engineering, Northwestern), Brooks Hu (Undergraduate, Computer Engineering, Northwestern), Mark Zhang (MS students, Mechanical Engineering, Northwestern)
- 2023:
- Yueyuan Sui, Shamika Likhite (MS students, Computer Engineering, Northwestern)
- Brooks Hu, Kiva Joseph (Undergraduates, Computer Engineering, Northwestern)
- Jonathan Li Chen, Ben Forbes, Justin Lau (Undergraduates, Mechanical Engineering, Northwestern)
- 2022: Devashri Naik, Jinjin Cai (MS students, Computer Engineering, Northwestern)