2017 Neukom Research Prize Winners

1st Prize: Cosmic Evolution of Supremassive Black Holes

Student: Mackenzie Jones
Mentors: Ryan Hickox, Physics & Astronomy

“Do you see what I see? Exploring the Consequences of Luminosity in Black Hole-Galaxy Evolution Studies”

Mackenzie’s computational work as a graduate student has broken important new ground in our understanding of the cosmic evolution of supermassive black holes. The model she is building has the potential to be extraordinarily useful for understanding the massive data sets from the coming generation of astronomical surveys.

2nd Prize: Uncertainty at the Synaptic Level

Student: Shiva Farashahi
Mentor: Alireza Soltani, PBS

Metaplasticity as a Neural Substrate for Adaptive Learning and Choice under Uncertainty” Department of Psychological and Brain Sciences

Shiva’s most recent work has been published in the prestigious journal Neuron. This work proposes a new computational model for learning under uncertainty at the synaptic level, and in doing so, bridges the gap between synaptic mechanisms and behavior. This model reveals that there’s not a single rate of learning for everything we do, as the brain can self-­adjust its learning rates using a synaptic mechanism called metaplasticity. Her findings refute the theory that the brain always behaves optimally.

1st Prize: ATLAS (Automated Tone Level Annotation System)

Emily has created a tool ATLAS (Automated Tone Level Annotation System) that will import audio from field recordings of spoken languages, extract and normalize the pitch, then automatically assign each syllable in the recording a “tone level”, a number representing which part of the speaker’s range it is pronounced in. The number of levels can be set by the researcher depending upon how much detail about the pitch contours of a speaker’s utterance is necessary. These annotations are an enormous timesaver for the researcher, who currently must annotate each syllable by hand using either his or her ear or raw acoustic measures. The annotations that are computationally produced by ATLAS are also superior in that they are objective and replicable, based on the actual acoustic signal rather than the researcher’s (often imperfect) ear.

1st Prize: Selective Sharing of Health Data

Student: Emily Greene
Mentor: Dave Kotz, CS

In her senior honors thesis Emily has leveraged advanced cryptographic techniques to make it possible for wearers of Amulet, or similar mobile Health devices, to upload their mobile Health data to the cloud and then selectively share that data with family, friends, caregivers, and researchers. This challenge – selective sharing of health data – is one of the great unsolved problems in the mobile Health sector.

2nd Prize: Augmented Reality for the Visually Impaired

Student: Jonathan Huang 
Mentors: Emily Cooper (PBS) and Wojciech Jarosz (CS)

“A HoloLens Application to Aid People who are Visually Impaired in Navigation Tasks”

Jonathan developed an application for an Augmented Reality (Microsoft HoloLens) device that assists users with severely impaired visual acuity to locate, identify, and read text information. His TextSpotting application makes use of the Microsoft HoloLens’s sensors and combines them with the capabilities of the Google Vision API to locate, highlight and read text.