Hello! I am Payal (hear pronunciation). I am a final year PhD candidate in Computer Engineering at Northwestern University advised by Prof. Qi Zhu. I work on machine learning for time-series under practical constraints, with a focus on healthcare and audio applications. Previously, I have been a student researcher at Mitsubishi Electric Research Labs (Summer 2025) and at Meta Reality Labs (Summers 2024 and 2023). My key research interests are:

1. Practical Multimodal Learning: I design efficient architectures for handling 10+ heterogeneous sensing modalities without combinatorial complexity. My work on MAESTRO (NeurIPS Spotlight 2025) introduces sparse adaptive cross-attention with symbolic tokenization, replacing expensive pairwise operations with scalable multimodal fusion. I showed that explicitly encoding missingness improves longitudinal signal monitoring for person identification, achieving top performance in the ICASSP’23 Signal Processing Grand Challenge. I also studied missingness in multimodal disfluency detection (InterSpeech’24), where opportunistically incorporating video when available enhanced performance.

2. Generalizable Time-Series Representations: I build models robust to distribution shifts from device changes and signal nonstationarity—common in real-world applications. I proposed a phase-anchored generalizable representation learning framework that is performant across a wide range of applications from sleep stage classification using Electroencephalogram (EEG) to gesture recognition using Electromyography (EMG) (TMLR’25, TS4H@NeurIPS’25).

3. Human-Centric Applications: I develop ML methods for: a) Subjective Labels: I designed custom optimization objectives to monitor physical fatigue in manufacturing workers at Boeing and John Deere (PNAS Nexus’24) and multi-label objectives to model auditory attention with Meta Reality Labs. b) Data Constraints: I designed data distillation and self-supervised frameworks for disfluency detection (ICASSP’23) and achieved state-of-the-art silent speech understanding from surface EMG without paired audio using LLMs (ACL’25).

From 2017 to 2021, I was a Design Engineer at Analog Devices Inc., where I worked on the consumer electronics team and supported the tape-out of two chips. I earned my Master’s in Electrical Engineering from IIT Madras, India, where I designed an end-to-end cardiac wrist-wearable (sensor and on-device algorithms) robust to skin pigmentation variations. My research interests are a product of my broad system level experience in consumer sensing devices that helps me prioritize pragmatism while developing state-of-the-art machine learning methods for sensing applications.

News

Selected Papers

Selected Recognition

• EECS Rising Star, MIT Workshop (2024)
• Top Performer, Computational Paralinguistics Challenge (ComParE), ACM Multimedia 2023
• Third Place, e-Prevention Challenge, ICASSP 2023
• Best Research Video, Design Automation Conference Young Fellowship, (2021)
• Winner, Make-in-India Anveshan Design Challenge, Analog Devices Inc. (2017)

Services

• Program Committee : 3rd ACM International Workshop on Intelligent Acoustic Systems and Applications (IASA 2025)
• Reviewer:
  • Journals : IEEE Internet of Things’25, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems’25, IEEE Transactions on Automation Science and Engineering’25
  • Conferences : ASP-DAC’26, ICASSP’25, ICLR’25, IMWUT’24, IROS’24, ICASSP’24
  • Workshops : TS4H’25 (Neurips), IEEE MLSP 2025, TSALM’24 (Neurips)
  • 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:
  • 2025: Xiaoyuan Zhang, Haodong Yang (MS students, Computer Engineering, Northwestern)
  • 2024: Talia Ben-Naim (MS students, Computer Engineering, Northwestern), Brooks Hu (Undergraduate, Computer Engineering, Northwestern), Mark Zhang (MS student, Mechanical Engineering, Northwestern)
  • 2023:
    • Yueyuan Sui (MS, Northwestern University → PhD, Northwestern University), Shamika Likhite (MS, Northwestern University → SWE, SpeechAce)
    • Kiva Joseph (Undergraduate, Computer Engineering, Northwestern)
    • Jonathan Li Chen, Ben Forbes, Justin Lau (Undergraduates, Mechanical Engineering, Northwestern)
  • 2022: Devashri Naik (MS, Northwestern University → PhD, University of Illinois at Chicago), Jinjin Cai (MS, Northwestern University → PhD, Purdue University)