Tristan Kilmer

Originally located on the back wall of the MOD, IRIS was a 3-dimensional automated aperture that opened to about 17-ft in diameter to reveal a lit cyclorama in its opening. For the Virtual Campus, we will be modeling the iris in 3D software, then using lighting software to create various lighting looks. Christian Mejia (MFA2, […]

Cloudcast An art therapy piece that utilizes a car experience to guide the audience in an intimate experience of self

A class album and some videos Nina Flagg, Medusa

Kai-Luen Liang Tomorrow There Will Be Wind ( Automatic Windchimes ) A performance of playing an Arduino controlled set of wind chimes. Vibration motors are activated through a motor driver creating divisions and polyrhythms based on various “states.” First iteration prototype with beer bottle activation.   Trevor Bock 4-Note Bottle Blowing Instrument I have always […]

Three kinetic sculptures explore relationships between circularity/co-opting/recycling and linearity/polarization/binary-ness, and how personal agency or positionality intersects with these linked mechanics. (They’re NOT “voting machines;” they reflect the operation of many large systems, frameworks and conversations, e.g., the relationship between the DIY ethos and capitalism, between the political far left and far right, and among nested […]

Scenes Inspired by film, memory, and collage, “Scenes” uses found and original material to recreate three scenes from its author’s life.  

Rob Ford Explorer Original experimental music from CalArts that would be perfect for the virtual expo! Greg Lewis, Cameron Sax

TW/CW: abuse, violence, suicide This song is about overcoming depression and suicide awareness through hope.  

A laser pointer is pointed at a mirror attached to a balloon. Sounds from a synthesizer vibrate the balloon, causing the mirror to move. This moves the laser pointer, resulting in the visualization of how the sound causes the balloon to vibrate. The images produced from this process are called lissajous figures. The improvisation explores […]

ML Landscape I am interested in the inaccurate and unpredictable result that a machine can make. In order to understand its “mind”, I train the machine using images that have not been cropped, to see how it understands a thing that has not be seen before.