Priyanka Mammen

Priyanka Mary Mammen

CS PhD Candidate, UMass Amherst
Advisor: Prashant Shenoy

I am on the Industrial Job Market for full-time positions!!

I am a CS PhD student at UMass Amherst. I am passionate about developing scalable, uncertainty-aware, and resource-efficient machine learning solutions that address real-world challenges in LLM evaluation, ranking systems, and edge AI. My work has contributed to improving retrieval latency, energy efficiency in machine learning infrastructure, and developing large-scale health monitoring systems.

Selected Publications

Visit Google Scholar for a full list.

  1. S. Ghosh et al., “AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons”
    2025 White Paper

  2. B. Vidgen et al., “Introducing v0.5 of the AI Safety Benchmark from MLCommons”
    2024 White Paper

  3. P.M. Mammen, “Federated Learning: Opportunities and Challenges”
    arXiv, 2021

  4. P.M. Mammen, C. Zakaria, T. Ochir, A. Trivedi, R. Balan, and P. Shenoy, “WiSleep: Sleep Monitoring via Smartphone Sensing and Unsupervised Learning”
    ACM JCSS, 2024

  5. P.M. Mammen, C. Zakaria, P. Shenoy, “SleepLess: Personalized Sleep Monitoring Using Smartphones and Semi-supervised Learning”
    CSI Transactions on ICT, Springer, 2024

  6. P.M. Mammen, N. Bashir, R. Kolluri, E.K. Lee, P. Shenoy, “CUFF: A Configurable Uncertainty-driven Forecasting Framework for Green AI Clusters”
    ACM e-Energy, 2023

  7. C. Zakaria, G. Yilmaz, P.M. Mammen, B. Parkman, M. Chee, R. Balan, and P. Shenoy, “SleepMore: Inferring Sleep Duration at Scale via Multi-Device WiFi Sensing”
    IMWUT / UbiComp, 2023

  8. P.M. Mammen, P. Shenoy, “Are you asleep when your phone is asleep? Semi-supervised methods to infer sleep from smart devices”
    NeurIPS Health Workshop, 2022

Awards

Recent News

Extracurriculars

I enjoy biking, photography, cooking, and poetry. My poetry collection is available on Amazon.

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