Upcoming Events

CS Seminar: Exploring the Intersection of AI and Entrepreneurship: Lessons and Insights from Silicon Valley to Acadia University (Seminar held with the LaunchBox) (2:30 pm - 3:30 pm)

Talk by Dr. Junwei Zhang
Tech Lead Engineer/Investment Director

Date: March 8th
Time: 2:30pm – 3:30pm
Location: Online
Teams link: Click here to join the meeting
Profile: LinkedIn
Email: junweizhang23@gmail.com

Abstract: In our rapidly evolving digital age, the impact of Artificial Intelligence on industries and the dynamism of startup ecosystems offer a unique canvas for innovation. Junwei Zhang, who has contributed to technology and venture capital through roles at companies including Uber, Microsoft, and DoorDash, shares insights into the integration of AI with entrepreneurial ventures, reflecting on the challenges and opportunities this convergence presents.
Drawing from a solid foundation in computer vision and parallel computing, alongside practical involvement in tech project leadership, Zhang aims to share his pathway and insights gained from navigating the vibrant tech and investment landscape of Silicon Valley. The discussion will allocate a thoughtful portion to AI — addressing its current frontiers and challenges — while also delving into the realms of startup development and venture capital, informed by Zhang's direct experiences and collaborative endeavors.
This session is designed to be an exchange of learnings rather than a highlight of personal accolades. It seeks to offer a nuanced understanding of how technology and entrepreneurship intersect, providing valuable perspectives for those interested in shaping the future of tech and business. Attendees will gain a broader understanding of the AI landscape, alongside practical advice on entrepreneurship and investment, fostering a spirit of innovation and growth.
Join us for a journey through the complexities and triumphs of merging AI with entrepreneurship, guided by the shared experiences from Silicon Valley's ecosystem to the academic and entrepreneurial communities at Acadia University.

Brief Bio: I am Junwei Zhang, and I am both an engineer and a venture capital investor with a robust background in technology and research. I earned my Ph.D. in Applied Mathematics and Statistics from Stony Brook University in New York. My journey in the tech industry began prior to the Uber IPO when I joined Uber as a software engineer. Following this, I embarked on roles within the Microsoft Azure Cloud + AI team and the DoorDash Growth team, contributing to significant projects and innovations. In addition to my industry experience, I serve as an associate editor for the IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), where I oversee contributions in areas pivotal to our field. My academic contributions include over 10 papers published in top-tier conferences and journals such as ICCV, CAD, CAGD, and TPDS, covering a range of topics from computer vision to geometry processing and parallel computing.
Venture capital investment is another avenue through which I engage with the tech ecosystem. I have led investments in startups, including those that empower Stanford researchers to leverage new AI technologies for mental health initiatives. Moreover, I am an active board member of a Silicon Valley-based tech entrepreneurship leadership community, where we organize monthly webinar discussions to foster innovation and leadership in the tech sector.

Poster Link




Past Events

CS Seminar - Dr. Ying Zhang



Friday, February 26, 2016

2:30 PM

Carnegie Hall 113


Test for Trends in Blocked Time Series Data: Harvesting Maple Syrup in Nova Scotia


Dr. Ying Zhang



Motivated by an investigation on the effects of local environmental conditions on yield in maple syrup production in a Nova Scotia farm, we generalized the nonparametric seasonal Mann-Kendall test procedure to test for trends in blocked and panel time series data. To further answer the question of when the change happens, we proposed a new procedure of testing for the change point in blocked time series data. In this talk, I will review some well-known nonparametric statistics used for testing for trend/change point in univariate time series data and then introduce our generalizations to the blocked data. I will report key findings from our investigation with both parametric and nonparametric methods.

This is a joint work with Elizabeth Abebe supported by an NSERC Engaged Grant and NS 2015 SCEI program.


About the Presenter

Dr. Ying Zhang is a Professor in the Department of Mathematics & Statistics and has been the Director of the Statistical Consulting Centre since coming to Acadia University in 2004.  Prior to this, Ying was the manager of the Statistical Laboratory at Western University (2001-2004), and has been an active statistical consultant since 1999. She has worked with a variety of organizations. Ying has extensive experience with applied statistical methodology research and consulting, specializing in time series intervention analysis, nonparametric statistics, experiment design, and survey sampling. Ying is a researcher member of Acadia Institute for Data Analytics (AIDA) and a board member of Statistical Society of Canada (SSC) and the International Environmetrics Society (TIES).


Everyone is welcome to attend!