Akshaye Shenoi

PHD Candidate

Singapore
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Summary

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Senior
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Top School
Akshaye Shenoi is a PhD candidate at ETH Zurich based at the Singapore-ETH Centre, specializing in the intersection of machine learning, ubiquitous computing, and digital health with a focus on wearable sensor data for psychiatric assessment. Over a decade of experience spans research roles at NUS and TUMCREATE and industry positions at GE, where he worked on cloud migrations and low-power wireless sensing reliability. His work combines theory-informed modeling and signal-processing expertise to reveal physiological–psychological links that can enable non-invasive, scalable mental health sensing and interventions. He has practical systems experience—designing consensus protocols for resource-constrained sensors and privacy-preserving IoT techniques using trusted execution environments—that underpins his applied ML research. A visiting scholar at Dartmouth and mentor/TA during his academic journey, he blends rigorous research with real-world engineering impact. Beyond publications, he aims to translate sensor-driven insights into intelligent health-sensing systems that support healthy longevity at scale.
code10 years of coding experience
job5 years of employment as a software developer
bookBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Manipal Institute of Technology
bookDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at ETH Zürich
bookMaster of Computing, Master of Computing at National University of Singapore
languagesMarathi, Hindi, English
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Github Skills (126)

simulate9
predix9
duke9
shadow9
connected8
emulation8
predix-ui8
container-image8
simulation8
tor8
private-network8
electrical-engineering8
nodejs8
simulator7
internet7

Programming languages (10)

TypeScriptJavaShellCRustJavaScriptGoPHP

Github contributions (5)

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akshayeshenoi/missiles

Sep 2016 - Dec 2024

Contributions:1 push, 3 branches in 8 years 4 months
akshayeshenoi/StompWS

May 2017 - Jan 2019

A Python library to enable simple STOMP communication over WebSockets. Works on the client-side with any STOMP server.
Contributions:9 commits, 2 PRs, 8 pushes in 1 year 9 months
python-librarypythonwebsocketsclient-sidecommunication
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