Resume-aware faculty matching

Find professors who actually fit you

Upload your resume. Four AI agents analyze your background, rank the faculty who fit, inspect their recent research, and help you draft outreach — grounded in their actual work, not templates.

Free to startNo credit cardCancel anytime
Top matches Balanced preset
Dr. Sarah Chen
Stanford · Interpretability · NLP
91
Dr. Marcus Holloway
MIT · Robotics · RL
84
Dr. Aisha Okonkwo
CMU · Fairness · HCI
82
Nova · Professor Researcher · re-ranking top 20…

Srinivasa Narasimhan

· Robotics Institute (interim)Verified

Carnegie Mellon University

h-index
Citations
Papers
Funding$7.8M
See your match with Srinivasa Narasimhan — sign in to PhdFit.Sign in

Research topics

  • Computer Science
  • Artificial Intelligence
  • Optics
  • Computer vision
  • Physics
  • Geometry
  • Acoustics
  • Mathematics
  • Computer graphics (images)

Selected publications

  • Dual-Shutter Optical Vibration Sensing

    2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 21 citations

    Senior authorCorresponding
    • Computer Science
    • Artificial Intelligence
    • Computer Science

    Visual vibrometry is a highly useful tool for remote capture of audio, as well as the physical properties of materials, human heart rate, and more. While visually-observable vibrations can be captured directly with a high-speed camera, minute imperceptible object vibrations can be optically amplified by imaging the displacement of a speckle pattern, created by shining a laser beam on the vibrating surface. In this paper, we propose a novel method for sensing vibrations at high speeds (up to 63kHz), for multiple scene sources at once, using sensors rated for only 130Hz operation. Our method relies on simultaneously capturing the scene with two cameras equipped with rolling and global shutter sensors, respectively. The rolling shutter camera captures distorted speckle images that encode the high-speed object vibrations. The global shutter camera captures undistorted reference images of the speckle pattern, helping to decode the source vibrations. We demonstrate our method by capturing vibration caused by audio sources (e.g. speakers, human voice, and musical instruments) and analyzing the vibration modes of a tuning fork.

  • Holocurtains: Programming Light Curtains via Binary Holography

    2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 13 citations

    • Computer Science
    • Artificial Intelligence
    • Computer Science

    Light curtain systems are designed for detecting the presence of objects within a user-defined 3D region of space, which has many applications across vision and robotics. However, the shape of light curtains have so far been limited to ruled surfaces, i.e., surfaces composed of straight lines. In this work, we propose Holocurtains: a light-efficient approach to producing light curtains of arbitrary shape. The key idea is to synchronize a rolling-shutter camera with a 2D holographic projector, which steers (rather than block) light to generate bright structured light patterns. Our prototype projector uses a binary digital micromirror device (DMD) to generate the holographic interference patterns at high speeds. Our system produces 3D light curtains that cannot be achieved with traditional light curtain setups and thus enables all-new applications, including the ability to simultaneously capture multiple light curtains in a single frame, detect subtle changes in scene geometry, and transform any 3D surface into an optical touch interface.

Recent grants

  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Srinivasa Narasimhan

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

  • Free to start
  • No credit card
  • 30-second signup