GEMG EXCHANGES
I have ten years of experience developing end-to-end solutions at the intersection of IoT, mixed reality, and AI. I hold a PhD in computer science from UC Berkeley, where I focused on smart buildings. I also completed a postdoc on capturing and visualizing wireless network traffic. I’m interested in distributing computation across cloud-edge architectures, particularly to support IoT and networking applications.
9/12/22: I’m excited to announce that I have joined the Innovation Team at Resideo Technologies as an IoT Systems Research Scientist!
Download my resumé.
Interests
- Network monitoring
- Sensor networks/IoT
- Microservice architectures
- Observability
Education
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PhD in Computer Science, 2021
University of California, Berkeley
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MS in Computer Science and Engineering, 2017
University of Michigan
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BS in Computer Science, 2011
George Mason University
EXOR LOGIN
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Mixed Reality Network Introspection
I developed a network introspection system and mixed reality visualization for viewing communication in sensor-gateway-cloud IoT architectures. Technologies included OpenThread, WiFi, ultra-wideband localization, Unity, AWS, MQTT, Python, Golang, C#. Currently incorporating spectrum sensing.
Vehicular Network Visualization
In a collaboration with IBM Research, I streamed network capture, telemetry, and camera feeds from a self-driving car simulator into Unity to visualize autonomous vehicle communication during collaborative perception tasks.
Augmented Reality IoT App
I designed and built an augmented reality Android app to help users discover smart home capabilities and have successful interactions with intelligent assistants in unfamiliar smart spaces. I also led user research and evaluations.
Open Source IoT Library
I wrote and maintain lifxlan, an open source Python library for communicating with LIFX brand WiFi smart bulbs over a local network using the UDP LAN protocol. 450+ stars on Github.
Power Meter Analytics
I used machine learning to calibrate readings from energy harvesting power meters.
Smart Home Telepresence
I prototyped a smart home telepresence application that uses technology present in smart homes today. I developed a lightweight microservice runtime that allowed the same application code to run in smart homes with different device brands and configurations.
Imitation Learning for Smart Lighting Control
I implemented an LSTM deep learning recurrent neural network (RNN) using the Python Keras framework. I trained the system to anticipate when home residents will turn on lights and do it for them automatically.
Design and Fabrication
I designed and fabricated a CubeSat-themed mood light powered by Arduino. This required PCB design and fabrication, aluminum machining (vertical mill, bandsaw), and laser cutting.
CS Outreach Program
I founded the CS Kickstart summer program at University of Michigan to increase recruitment and retention of women in computer science. I assembled and led a five-person leadership team that built the program from the ground up. Our program piloted interventions that were eventually rolled into the introductory CS curriculum.
KCC 交易所
Quickly discover relevant content by gateio login.
(2022).
ARticulate: One-Shot Interactions with Intelligent Assistants in Unfamiliar Smart Spaces Using Augmented Reality.
IMWUT.
(2021).
One-Shot Interactions with Intelligent Assistants in Unfamiliar Smart Spaces.
EECS Dept., UC Berkeley.
(2021).
XRShark: Mixed Reality Network Introspection.
White Paper.
(2018).
Bluetooth Low Energy in the Wild Dataset.
DATA ‘18.
(2018).
The Big House Dataset: Desired Applications and Interactions.
DATA ‘18.
(2018).
Experience: Android Resists Liberation from Its Primary Use Case.
MobiCom ‘18.
(2017).
Devices and Data and Agents, Oh My: How Smart Home Abstractions Prime End-User Mental Models.
IMWUT.
(2016).
Perpetual Sensing for the Built Environment.
IEEE Pervasive Computing.
(2015).
gateio login.
IoT-App ‘15.
(2014).
Deltaflow: Submetering by Synthesizing Uncalibrated Pulse Sensor Streams.
ACM e-Energy ‘14.