Projects
Innovating at the Intersection of Health and Technology
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Step into a sample showcase of impactful and innovative MedTech projects led by Beenish—where cutting-edge engineering meets real-world healthcare challenges. From intelligent diagnostic tools to life-changing devices, these projects reflect her passion for building technologies that heal, empower, and push the boundaries of what’s possible in healthcare and life sciences.
AI on Voice for Detecting Abnormality
This project dives into the transformative potential of AI in healthcare, focusing on voice data analysis for early detection of conditions like laryngeal cancer and Parkinsons Disease. This project explores AI applications in voice analysis, tackle the challenges and unveil strategies for harnessing AI to enhance patient outcomes. In collaboration with Dr. Taghizadeh, MD, an Otolaryngologist, Beenish has developed an AI model that can be trained on synthetic and real voice data for abnormality detection. She has open sourced this model for growth and adoption of the idea. If you want to discover how AI is changing the future of healthcare—one voice at a time, check out this project and reach out to Beenish if you have questions.
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Published resources:
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Github link to open-source AI Model: Voice abnormality Detection
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Technical paper: AI Driven Approaches in the laryngeal cancer care continuum
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Technical paper: Voice Analytics and AI: New Frontier in Early Disease Detection
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IEEE WIE ILC Speaker: Unlocking the potential of AI in Voice
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Lossless Compression
This project details work led by Beenish on low-latency lossless compression. This project evaluates and optimizes compression methods for 16-bit raw monochrome medical images—commonly used in modalities like MRI and CT—emphasizing both efficiency and speed. The study benchmarks various codecs and identifies High Throughput JPEG 2000 (HTJ2K) as the most suitable choice. To further boost performance, the project explores advanced optimizations that significantly reduce encoding latency, making the solution ideal for real-time, diagnostic-grade systems where preserving full image fidelity with minimal delay is critical.
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Published Resources:
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Technical Paper: Intel® AVX2/AVX-512 Optimizations for JPEG2000 and HTJ2K Open-source Codecs
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Technical Paper: Low Latency Lossless Compression of Monochrome Medical Images
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IEEE Proceedings: 2023 Data Compression Conference , Low Latency Lossless Compression of Monochrome Images
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Electronic Pillbox Logger
This project details Beenish’s work on designing and implementing an electronic pillbox logger for people with Parkinson’s Disease. Beenish designed and prototyped a pocket-sized, portable electronic pillbox to support medication adherence in people with Parkinson’s Disease (PD). The device features multiple compartments, customizable alarms, and electronic logging of pill presence to ensure timely medication intake. Unlike conventional pillboxes, it records actual pill removal rather than just box opening and connects to a host computer for data retrieval. This solution complements a wearable movement-monitoring device and helps clinicians optimize PD therapy based on adherence and response data. While tailored for PD, the design can be adapted for other conditions requiring strict medication schedules. The project linked describes how Beenish laid out PCB (Printed Circuit Board) for the design, had it manufactured for prototyping, wrote all the necessary software to boot the PCB and have it functional, as well as the 3D printed design of the physical box.
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Published Resources: