Prasad Madhava Kamath

Senior Engineer, DSP (Audio) • Applied ML / Applied Research

Chicago, USA prsdkamath7@gmail.com LinkedIn GitHub

Summary

DSP engineer with 7+ years of experience designing signal processing algorithms, audio frameworks, and production-grade software for commercial audio products. Strong foundation in signal processing, machine learning, and neural networks with hands-on experience designing research prototypes, and translating them into deployable, real-world audio products.

Applied Research → Product Embedded / Real-time DSP Audio ML

Professional Experience

Shure Incorporated — Senior Engineer, DSP

Chicago, USA • Apr 2023 – Present
  • Led DSP development of MV7i microphone, the first with an integrated audio interface.
  • Designed and implemented low-compute, low-latency automatic audio equalization algorithms suitable for embedded constraints.
  • Researched and proposed audio codec optimization approaches to improve efficiency and quality under bandwidth/compute limits.
  • Developed an ML-based objective perceptual quality characterization method to reduce evaluation listening time while maintaining decision reliability.

Shure Incorporated — DSP Engineering Intern

Chicago, USA • Jun 2022 – Sept 2022
  • Developed a hybrid neural + adaptive filtering approach for nonlinear residual echo suppression.
  • Prototyped room characterization algorithms in Python/MATLAB and translated to optimized C/C++ for target hardware.

Analog Devices India Pvt Ltd — Engineer-2, Infotainment Processing & Connectivity

India • Aug 2016 – Aug 2021
  • Developed signal processing libraries for floating and fixed-point DSPs in C and DSP assembly (SHARC, ADAU14xx).
  • Designed and implemented algorithms & systems for Noise Reduction, ANC, and AEC in real-time embedded environments.
  • Designed a multi-rate feedback canceller reducing resource consumption by ~40%, enabling deployment on lower-cost DSPs.
  • Integrated audio frameworks and peripherals for embedded audio systems, supporting robust product deployment.

Academic Projects

Quantifying Time–Frequency Variations in MCW Sets for Hearing Aid Applications

UC San Diego • Jan 2023
  • Advised by Dr. Harinath Garudadri, Dr. Bhaskar Rao
  • Conducted research at the intersection of machine learning, signal processing, and speech phonetics to develop algorithms for hearing-aid self-fitting.
  • Developed phonetic contrast functions and methods for distinguishing minimal word pairs in hearing-aid signal processing.

Echo Cancellation and Residual Echo Suppression: A Hybrid Approach

Jun 2022
  • Developed a hybrid scheme for non-linear echo cancellation using a shallow Neural Network (UNet, LSTM) as a post-filter.
  • Achieved mean ERLE of 38 dB and mean signal-to-distortion ratio of 13 dB during double talk.

Prototypical Few-Shot Learning for Image Segmentation

Jun 2022
  • Implemented prototypical network with metric learning for few-shot image segmentation on PASCAL and COCO.
  • Performed ablation study and integrated architectural changes using DeepLabv3 to improve mean IoU by 20% versus baseline.

Publications & Presentations

  • A phonetic contrast function to improve sound processing in hearing aids, J. Acoust. Soc. Am. 153, A158 (2023)
  • Broad phonetic feature classifier for real-time hearing aid processing, J. Acoust. Soc. Am. 153, A156 (2023)
  • Design and Implementation of LST Based Dynamic Scheduler on Real Time OS, IJEECSE - NEWS 2