Calvin Hulse

Co-Founder

TOGETHR

The Ivy League Student Consortium

Hello,

My name is Calvin Hulse

In my free time I explore disruptive technologies and their applications to my workflows, new projects, digital art, and each other.

This website background is one such application, where I used Cinema 4D with the Houdini Ocean Toolkit and Octane Render to construct a 3-D oceanic environment, captured and rendered from a 2-D perspective camera.

Skills and Passions I Nurture:

Adobe Suite

Autodesk CAD

Autodesk Fusion 360 Generative Design

Cinema 4D & Octane

Computer Vision

Crypto Markets

Impressionistic Art

Enterprise-grade Metaverse

Mixed & Virtual Reality

Python

Risk Modeling

SQL

Stable Diffusion and DALLE-2

Tokenized Assets

Quantitative Analysis

Young Professionals Networking Events

Current Projects

Facial Recognition & Interactive Media

I am learning how to use open source, pre-trained, deep facial recognition and object detection methods, combined with databases, to identify anonymous individuals and ultimately link their anonymous schema with widely available datasets. This is one step in a much larger project, the entirety of which I believe has the potential to greatly transform interactive media and services.

I believe that by truly linking the physical and digital identities, we can open new frontiers in advertising, consumer analytics, law enforcement, city planning, and more. The key consideration here is that of consumer agency - consumers should willingly give this information in what they feel is a mutually beneficial transaction.

2-D -> 3-D Video Conversion

I'm exploring NVIDIA Neuralangelo and testing its limitations with regard to 3D scene reconstruction. Specifically, I want to understand the depth of information (namely resolution, number of angles, contrast) minimally necessary to reconstruct variousscenes in 3 dimensions. Derivatively, I want to understand how these minimum requirements can be manipulated to construct scenes which may have 3 dimensions, but which also may be limited in their viewing angles.

I believe these methods can be applied to existing television and movies - by utilizing the frames sandwiching a target frame to create sufficient context window, 2D frames may be able to be transformed full-depth 3 dimensional scenes, viewable within virtual reality through a sort of "window", rather than on a traditional 2D screen.

Apple's recent reveal of 3D memories on their new Vision Pro headset further confirms that this is something which is not only possible, but could likely be desired by consmer groups, as opposed to the unintuitive "3D" TVs of a decade ago.

The concept of 3-dimensional, experiential video...

...applied to popular motion pictures.

Quant Trading

I'm exploring topics in quantitative analysis as applied to trading. This involves macro and micro research, understandings of market microstructure, strategy development, backtesting, and execution. Through this endeavor I am learning classical startegies such as statistical arbitrage and momentum; newer strategies like sentiment analysis and ML-based approaches; and i'm building my own strategies. I find myself gravitating toward FX and ETFs due to their high liquidity, but I want to explore commodities and fixed income instruments as well.

A single equity's movement against the standard deviations of the cointegrated mean.

A snapshot from an ETF basket pairs strategy in my QuantConnect environment.