David Ban


Software Engineer / Student



Game Designer
Software Engineer

Hi! I'm David! I'm a gamer who enjoys rhythm games and music.
I helped teach and facilitate the Game Design Decal, where we teach students how to create video games in Unity. I also participated in the class, and have an itch page with all the games I've helped make. In particular, I produced, designed, and coded a rhythm game titled Rhythmic Blade.
I was also recently in the Wuthering Waves second closed beta, and you can check out my teardown of the game and the mechanics here.
I also developed a realistic fluid simulation inside of Unity only using Shaders. You can see the writeup of the project here, and my other projects for the class here.
Hello! I'm David, a computer science graduate from UC Berkeley.
Currently working at Houlihan Lokey under their Data and Analytics department, but am doing full stack development on a new software for the company for bankers. I'm also doing a part time masters at Georgia Tech with a 4.0 GPA
In addition to school and work, I constantly seek opportunities to expand my knowledge. I have attended numerous hackathons, game jams, and organized several math tournaments for high school and middle school students including the Berkeley Math Tournament. I also did research at the Center for New Music and Audio Technologies (CNMAT) at Berkeley where I utilized generative AI to create reactive music videos. I am also a founding officer of the Dance Games @ Berkeley, which hosts and maintains the Dance Dance Revolution machine on campus. You can see our website which I helped build here.
I also enjoy learning new hobbies, and have tried to learn at least one every semester at Berkeley. You can find the full list of hobbies here!


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Portfolio



Papers and Presentations


Name Year URL
'Network Bending of Diffusion Models for Audio-Visual Generation' 2024 Paper
'Experimental results of conductive inserts to reduce nuclear fuel temperature during nuclear volumetric heating' 2021 Paper Link
'Dry in-pile fracture test (DRIFT) for separate-effects validation of ceramic fuel fracture models' 2021 Paper Link
Predicting Protein-Ligand Binding Using Deep Learning with Spatial Transformations 2020 Paper
American Medical Informatics Association Presenter 2019 Presentation Slides