Aalap Khanolkar

About Aalap Khanolkar

Over the past few years, I’ve been exploring the space where signal processing, machine learning, and audio engineering come together. I’ve always been fascinated by how sound and data can shape experiences, and I enjoy finding practical ways to connect theory with real-world applications.My journey began with music, where curiosity about sound naturally grew into an interest in the science and engineering behind it. Over time, that curiosity led me deeper into signal processing, machine learning, and audio engineering areas where I could explore both creativity and technology side by side.Working with tools like Python, TensorFlow, and MATLAB has helped me translate concepts in DSP and statistical modeling into real applications. I’ve enjoyed exploring how algorithms can reduce noise, improve clarity, and make sense of complex signals, often drawing on my hardware background to connect theory with systems in practice.At Tektronix, I learned how DSP and machine learning can complement each other to advance signal analysis. Currently, at Sonix-Tektronix, I’m applying DSP and image processing techniques to ultrasonic systems, which continues to challenge me and expand my perspective on acoustics and inspection accuracy.

Experience

1. Research & Development - Ultrasonic Signal Engineer

   Tektronix

   Nov 2023 — Present · VA, US

   Designed and implemented advanced digital signal processing (DSP) algorithms to analyze ultrasonic waveforms for high-resolution material characterization in semiconductor wafers- Applied machine learning techniques to classify and enhance acoustic signal patterns, improving defect detection accuracy in Scanning Acoustic Microscopy (SAM)-Developed custom image processing pipelines to enhance acoustic image clarity, contrast, and resolution, enabling more precise failure analysis and inspection.Integrated AI-driven denoising and feature extraction methods to boost signal-to-noise ratio and automate anomaly detection in acoustic datasets- Optimized real-time signal and image processing workflows, reducing inspection latency while maintaining sub-micron precision in high-throughput environments- Leveraged deep learning models for pattern recognition and predictive analytics in acoustic imaging, supporting proactive quality control in semiconductor manufacturing- Pioneered hybrid DSP and image fusion techniques to extract richer insights from multi-modal inspection data, pushing the boundaries of non-destructive evaluation.

Education

• Portland State University

  Master's degree, Electrical and Electronics Engineering

• Bhartiya Vidya Bhavans Sardar Patel Institute of Technology Munshi Nagar Andheri Mumbai

  BE - Bachelor of Engineering, Electronics Engineering

  2016 — 2020