Hi.
My name is Jiahao Wu
Welcome to my online home.
About Me
As a Technical Project Manager with over 5 years of experience in mechanical engineering and robotics, I currently lead critical projects at CRRC MA Corporation aimed at advancing the reliability and efficiency of rail transit vehicles. My expertise spans managing comprehensive project lifecycles, enhancing system reliability, and spearheading operational efficiencies. My academic foundation includes a Master’s degree from Columbia University, where I contributed to pioneering research in robotics.
WORK EXPERIENCE
As a Technical Project Manager at CRRC MA Corporation in Boston since June 2023, I oversee projects aimed at enhancing the reliability and efficiency of rail transit vehicles. My role involves leading a team that has successfully shortened the vehicle failure resolution time from 86 days to 2.5 days. I initiated and manage the cross-functional Fault Review Committee to improve systems reliability and operational efficiency.
Previously, I worked as a Mechanical Engineer II / Design at Dexai Robotics, where from September 2018 to August 2020, I was responsible for transitioning robotics products from research and development to commercial viability. I led the design and integration of the “Alfred” chef robot, focusing on improving reliability and operational functionality. My contributions included the development of a detailed hardware debugging process which facilitated faster issue resolution.
Before my current position at CRRC, I was a Mechanical Engineer in the R&D Department from January 2022 to June 2023. There, I led technical support efforts that resolved over 250 technical issues, enhancing manufacturing efficiency by 6.5%. I developed a database for lessons learned to support future projects and improve communication with clients and inspectors.
RESERACH
Robot Metabolism
Biological organisms can metabolize: break down nutrients into the basic building links and then use those building links to create new things. What if we could reproduce this kind of process in a robotic system?
ACADEMIC PROJECTS
Evolutionary Algorithm Application
Traveling Salesman Path
In the traveling salesman problems, we are given a set of cities, traveling costs between city pairs and fixed source and destination cities. The objective is to find a minimum cost path from the source to destination visiting all cities exactly once.
Solving Linear Regression
Linear regression can be analytically solved by matrix calculus. However, it is a problem in which we can be approximately correct, hence a good example for demonstrating how genetic algorithms work.
Soft Robot Evolutionary
In 1994 Karl Sims showed that computational evolution can produce interesting morphologies that resemble natural organisms. Despite nearly two decades of work since, evolved morphologies are not obviously more complex or natural, and the field seems to have hit a complexity ceiling. One hypothesis for the lack of increased complexity is that most work, including Sims’, evolves morphologies composed of rigid elements, such as solid cubes and cylinders, limiting the design space. A second hypothesis is that the encodings of previous work have been overly regular, not allowing complex regularities with variation. Here we test both hypotheses by evolving soft robots with multiple materials and a powerful generative encoding called a compositional pattern-producing network (CPPN). Robots are selected for locomotion speed. We find that CPPNs evolve faster robots than a direct encoding and that the CPPN morphologies appear more natural.
Predict Amazon Stock Price By Using Machine Learning Algorithms
In the stock market, stock investment’s biggest problem is that the information and data in the stock market are complex and excursive. Individual investors are not always able to receive useful and helpful information. Sometimes they even have to pay extra to get this kind of information. Until today, There are still fewer data science tools in the market which are able to provide comprehensive information to individual investors and use machine learning to help their investment decision. The individual investor often replies on some cost-free “Gossip” instead of scientific-technical analysis to decide the stock market’s next action. As a result, Individual investors often lose a lot of their investment for the above reasons.
I plan to aid in such development by designing a machine model that can predict a daily close price for a company that could provide help and suggestions to individuals investors in their stock daily trade.
Three Wheels EV
In 2017, approximately 63% of the energy consumed in the United States was generated from fossil fuels. Such energy sources are inherently unsustainable as the consumption rate is greater than the replenishing rate. Additionally, the usage of fossil fuels pollutes the environment due to the emission of greenhouse gases. Although renewable energy generation has significantly increased, it has yet to surpass fossil fuels. Such outcome is a result of the subsidies received by the fossil fuel industry from the Federal government. Thus, the fossil fuel industry does not have an incentive to develop renewable energy sources. However, automobile companies such as Tesla, Toyota and BMW are currently developing the technology for electric and hydrogen-powered cars.
Team VeloSITy plans to aid in such development by designing a hydrogen-powered vehicle that will participate in future Shell Eco-marathon competitions as they are globally recognized for exhibiting development in the automobile industry.
In this Project, Jiahao is the team leader of VeloSITy Team 2 and also designs the vehicle steering system and braking system.