Meghan Clark

Meghan Clark

Postdoctoral Scholar

University of California, Berkeley

Biography

I have ten years of experience developing end-to-end solutions at the intersection of IoT, mixed reality, and AI. I recently completed my PhD in computer science from UC Berkeley, where I focused on smart buildings. I’m interested in distributing computation across cloud-edge architectures, particularly to support IoT and mixed reality 5G applications.

I am currently looking for positions!

Download my resumé.

Interests
  • Network monitoring
  • Sensor networks/IoT
  • Microservice architectures
  • Observability
Education
  • PhD in Computer Science, 2021

    University of California, Berkeley

  • MS in Computer Science and Engineering, 2017

    University of Michigan

  • BS in Computer Science, 2011

    George Mason University

Projects

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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.
Mixed Reality Network Introspection
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.
Augmented Reality IoT App
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.
Open Source IoT Library
Power Meter Analytics
I used machine learning to calibrate readings from energy harvesting power meters.
Power Meter Analytics
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.
Smart Home Telepresence
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.
Imitation Learning for Smart Lighting Control
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.
Design and Fabrication
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.
CS Outreach Program