Open Family Office Wealth Management Company

AUM @ 20M 

Acquiring class B/C small commercial Multifamily properties (e.g., 6~50 units per parcel) in Class A/B locations, improving the financial performance of the properties via a suite of value-add strategies, stabilizing the performance of the property, and exiting the investment via various exit strategies, e.g., cash-out refinancing, 1031 exchange. 

At OFO, we believe that access to wealth management strategies and investment opportunities shouldn't be limited to just ultra-wealthy families. My vision is to democratize the family office and provide middle-class families with access to the same level of expertise, insights, and investment opportunities that are typically only available to the ultra-wealthy. We understand that many middle-class families face financial challenges such as high income tax rates, volatile stock markets, and the fear of job loss. That's why our mission is to provide our investors with exclusive private equity real estate investment opportunities that offer strong returns, while minimizing risks and providing a hedge against market volatility. Our commitment to transparency, accountability, and long-term value creation ensures that our investors have access to the same level of due diligence and investment expertise that is typically only available to ultra-wealthy families. By providing our investors with access to these exclusive investment opportunities, we empower them to diversify their portfolios and build passive income streams that can provide financial security for their families. At OFO, we're not just in the business of building wealth; we're also dedicated to making a positive impact in the communities where we invest. Our focus on sustainable growth and community impact ensures that our investments create jobs, revitalize neighborhoods, and support local businesses. Join us today and start building a brighter financial future for you and your loved ones

Founder & Managing Partner

Facebook

- Working on Modern Recommendation System Platform team
- Lead a strategic product for FB App, targeting US young adults users, leveraging state-of-art infrastructure and machine learning technologies in the arsenal at FB.

Staff Software Engineer

Communities Ecosystem Growth
- Change the paradigm for how FB promote the product growth in newsfeed. E.g., I lead a v-team of 10+ senior engineers successfully migrate Group-You-Should-Join (GYSJ) promotional unit from ads auction system to newsfeed ranking system in all traffic. For the first time, the company can trade long-term product growth off short-term newsfeed engagement, instead of ads revenue.

- Built an user understanding service that leverages sophisticated infrastructure of search engine and machine learning technologies, and now powers tens of recommendation products at FB.

Senior Software Engineer

ByteDance

First engineer hired at the Global Monetization organization in bay area. Helped built the team of ads auction platform and ads quality platform for $10B business, e.g., TikTok, Douyin, Toutiao, etc.

Feed Ads Delivery
- Author of "Fresh Ads Tail Load" mechanism that subtly trade latency off CPU cost in ads system, and manage to improve ads revenue by 3% for FB Inc. This work is highlighted in the company Earning Report of 2019 Q2. From COO Sheryl Sandberg :

"We're constantly making incremental improvements to Facebook Feed Ads. This quarter, we improved how quickly we refresh the ads people see. In the past, these ads were pre-selected at the beginning of a Feed session. Now the ads are refreshed while people are scrolling through their feed. This means people get more relevant ads which improves engagement and delivers a better return on investment for advertisers."

Senior Research Scientist

Feed Ads Delivery
- Identified opportunities to improve the ads auction system and ads retrieval & ranking system. Increased overall ads revenue by 4% for FB Inc.

- Main engineer migrating 100K lines of code for the core business logic of feed ads delivery, which account for 65% FB Inc. revenue. Made it modernized and maintainable.

Research Scientist

University of California, Davis

- Developed schemes to enhance system throughput. Developed constraint programming (CP) formulation to jointly optimize heterogeneous network resource allocation. System throughput can be enhanced by 25% for cell-average users and by 645% for cell-edge (5% worst case) users.
– Designed schemes to reduce the number of handovers for mobile users. Developed an Integer Linear Program for mobility-aware scenario, and heuristic algorithms for mobility-unaware scenario. Developed a randomwalk-based simulator in Java, where our schemes can reduce handover number by more than 50%.
– Designed an energy management framework based on network virtualization paradigm. Developed an energy optimization model based on Integer Linear Programs, and a suite of traffic balancing and consolidation heuristics. Energy consumption of central office was lowered by more than 72% across a wide range of traffic statistics.

Research Assistant

Orange

Techno-economic Study for Designing Low-cost 5G Radio Access Networks:

Conducted a techno-economic study on designing 5G radio access network architecture. Developed models for splitting wireless processing functional chain, to decide how much functions to be centralized or distributed. Used constraint programming to find the optimal functional splits for base station with given configurations. Up to 15% total cost of ownership (Million Euros) is expected to be saved for network operators.

Research Engineer Intern

KTH Royal Institute of Technology

Energy Consumption Modeling of 5G Mobile Network Architectures:

- Participated in an industry-driven project (“SooGREEN”) with 18 European research initiatives and companies, addressing the need to reduce the energy consumption of services in different 5G mobile network architectures.

– Proposed an energy-efficient mobile network architecture based on network function virtualization paradigm. Developed constraint programming formulations for a network resources management framework.

Visiting Researcher

Ennetix, Inc.

Network Performance Monitoring System:

- Developed distributed network data-collectors in C++ that can periodically probe network health status, detect performance anomalies of monitored network using Gaussian Kernal Estimation method, and send reports to cloud servers.

– Developed cloud-based anomaly-diagnoser using Akka Actor (in Scala) that can handles massive concurrent analysis requests. Used decision-tree method to quickly diagnose anomalies by analyzing reports from collectors.

– Developed cloud-based anomaly-localizers in Scala to localize network anomalies using network tomography algorithms, which can efficiently identify problematic network links or nodes by analyzing end-to-end measurement data.

Software Engineer Internship

Tsinghua University

Developed simulation software to test survivability strategies for backbone optical networks.

Taplio

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Xinbo Wang, Ph.D.

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