We are Project Noise Lab, an AI-driven, fully legal investment firm with an exclusive focus on crypto assets and blockchain-related projects. Our mission centers around addressing the wealth gap by preventing large investment institutions from monopolizing the market.Committed to social responsibility, we contribute 20% of our profits to charitable causes and actively work to increase financial literacy within the community. Our approach involves leveraging a set of machine learning and quantitative-based methodologies, reminiscent of those employed in the high-frequency trading world. Through this strategic framework, we empower traditional investors to participate in the emerging digital asset class with a professional, secure, liquid, and transparent exposure.Project Noise Lab stands at the forefront of merging cutting-edge technology with a commitment to ethical and responsible investment practices, fostering a transformative approach to wealth management in the ever-evolving landscape of crypto assets and blockchain technology.

• Implemented machine learning models (linear and polynomial regression) on property data, improving on the valuations• Researched major mortgage indexes and relevant economic factors, identifying variables that improve valuation accuracy• Designed data pipeline streamlining the data acquisition process from open source platforms (REBNY, Property Report)

Teaching Assistant for Department of Chinese,Computer Science and Economics: Classes include --Python, Intermediate Chinese, Econometrics.

• Conducted competitor analysis for top 10 competitors in both P2P and wealth management industry• Oversaw data infrastructure implementation project and create monthly report• Created a visualization project that elevates the efficiency and gives sales force more insight on different customer sectors

• Dissected financials of over 150 companies to combine with proprietary traffic signals. Assisted senior researchers in predicting corporate earnings and macro indicators• Researched and implemented relevant time series statistical models (i.e. ARIMA, ARIMAX, etc.) with Python• Created an algorithm combining Google search and Yelp listings with the company’s geo-location editor, proliferating the efficiency and accuracy on closed physical stores tracking

• Provided iOS UI design for Crown Inc., • Constructed a model to determine whether the phone of a truck’s driver and the truck are at the same location for ALCT Logistic company• Analyzed the deviation of coordinates between the BeiDou Navigation Satellite system (BDS) and US GPS • Resolved an logistic tax issue for the Chinese government

• Analyzed eye cone cell data and identified the gap between manual counting and auto counting• Created a model for normal cone cell density by operating a prototype adaptive optics-scanning laser ophthalmoscope• Controlled the quality of data collections to ensure the result of the representing data sets