
Listings
Educational Background
- M.S., Finance, University of Illinois at Urbana-Champaign, 2008
- M.S., Computer Science, Indiana University, 1999
- B.S., Computer Science, Tsinghua University, 1995
Positions Held
- Consultant, Whova Inc, 2017 to present
- Instructor of Accountancy, University of Illinois at Urbana-Champaign, 2017 to present
- Senior Application Developer, Whova Inc., 2015-2017
- Commodity Future Trading Platform Developer, Interactive Brokers, 2007-2014
- Application Analyst, Safeco FIS, 2003-2007
- Senior Consultant, OSI Consulting Inc, 2001-2003
- Application Developer, eToys, 1999-2000
- Software Engineer, ASDC Inc, 1995-1997
Honors and Awards
- List of Teachers Ranked as Excellent by their Students, University of Illinois, 2024
- List of Teachers Ranked as Excellent by their Students, University of Illinois at Urbana Champaign, 2022, 2023
- List of Teachers Ranked as Excellent by their Students, University of Illinois at Urbana-Champaign, 2018, 2019, 2020, 2021
Current Courses
-
Data Analytics for Mgmt Acctg (ACCY 512) Data analytics incorporated into management decision making, including planning, cost management, and management control system design. Focuses on developing your skills of gathering and analyzing data for internal decision making purposes.
-
Data Analytics Foundations (ACCY 570) Concepts and foundations underlying data analytics for accounting. Provides fundamental knowledge of how to acquire, organize, synthesize and analyze (possibly large) volumes of data to address questions and problems. After completing this course, students should (1) have a foundational understanding of the techniques underlying data analytics, (2) recognize scenarios and identify appropriate tools for various types of data analysis and (3) use Python and Tableau to perform data analysis.
-
Stat Analyses for Accountancy (ACCY 571) Fundamental knowledge of how to perform statistical analyses useful for leveraging accounting information to solve business problems. After completing this course, students should (1) have a foundational understanding of the statistical analyses underlying data analytics, (2) recognize scenarios and identify appropriate statistical tools for various types of data analysis and (3) use common computer-based tools to perform statistical analyses.
-
Machine Learning for Accting (ACCY 577) This course introduces machine learning algorithms and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses feature importance and model optimization.
-
ACCY Analytics Appl - A (ACCY 578) Develops students’ knowledge regarding the role, methods, and implications of business and data analytics in accounting via real-world applications of fundamental and advanced analytics principles. Application opportunities span multiple areas of accounting, including audit, fraud identification and detection, financial accounting, and managerial accounting. After engaging in this course, students should (1) have a foundational understanding of the role of business / data analytics in accounting and (2) be able to apply this knowledge to real-world clients, business decisions, etc.