Rahul Anand Sharma

Ph.D. Student @Cylab, CMU Previously @ Microsoft Research, IIIT Hyderabad


I am a Ph.D. candidate at Carnegie Mellon advised by Prof. Vyas Sekar and Prof. Anthony Rowe. I am working on the problem of IoT security and applying machine learning to solve interesting challenges in computer networks and systems.

Previously, at Microsoft Research, I was involved in the project FarmBeats, where I worked on developing ML algorithms on sensor data for agriculture.

Before that, I finished my Undergrad and Masters’s from IIIT Hyderabad, India. My Master’s thesis was in the field of computer vision where I developed several algorithms to analyze cricket and soccer broadcast videos.

Here is my CV

I am on the industry job market


Oct 30, 2022 Lumen accepted at CoNEXT 2022
Aug 10, 2022 Presented Lumos at the USENIX Security conference in Boston
Jul 1, 2022 Media coverage of Lumos by Der Spiegel, Hackernews , Blog1, and Blog2
May 1, 2021 Passed my Ph.D. qualification exams. Officially a Ph.D. candidate now
May 15, 2020 Interned with networking research group at Microsoft Research, Redmond
May 10, 2020 Presented GLITTER at IPSN 2020 (Virtual)
Aug 15, 2018 Started my Ph.D. at Carnegie Mellon
Aug 1, 2016 Started as a Research Fellow at Microsoft Research, India on Farmbeats
Jul 1, 2016 Media coverage of Cricket Annotation work by NDTV, Washington Post, Stack, and Register

Selected Publications (see all)

  1. Lumen: A Framework for Developing and Evaluating ML-Based IoT Network Anomaly Detection
    Sharma, Rahul Anand, Sabane, Ishan, Apostolaki, MariaRowe, Anthony,  and Sekar, Vyas
    In CoNEXT 2022
  2. Lumos: Identifying and Localizing Diverse Hidden IoT Devices in an Unfamiliar Environment
    Sharma, Rahul AnandSoltanaghaei, ElaheRowe, Anthony,  and Sekar, Vyas
    In USENIX Security 2022
  3. Accurately Measuring Global Risk of Amplification Attacks using {AmpMap}
    Moon, Soo-Jin, Yin, Yucheng,  Sharma, Rahul Anand, Yuan, Yifei, Spring, Jonathan M,  and Sekar, Vyas
    In USENIX Security 2021
  4. Contention-aware performance prediction for virtualized network functions
    Manousis, AntonisSharma, Rahul AnandSekar, Vyas,  and Sherry, Justine
    In SIGCOMM 2020
  5. All that glitters: Low-power spoof-resilient optical markers for augmented reality
    Sharma, Rahul Anand, Dongare, Adwait, Miller, John, Wilkerson, Nicholas, Cohen, Daniel, Sekar, Vyas, Dutta, Prabal,  and Rowe, Anthony
    In IPSN 2020

Press Coverage

Lumos by Der Spiegel, Hackernews , Technical.ly, and Trak.in
Bill Gates talking about FarmBeats on GatesNotes
Satya Nadella talking about our work on Cricket Annotation
Cricket Annotation work by Washington Post, NDTV, Stack, and Register