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Ti-Chung Cheng

Ti-Chung Cheng

def decision(human, machine):

Research Intern, Software Analysis & Intelligence (SAINTES) Group, Microsoft Research (May 2023 - Aug 2023) #

  • Mentors: Denae Ford Robinson, Nicole Forsgren, Carmen Badea, Christian Bird, Tom Zimmermann, Rob DeLine.
  • Designed and built a prototype aimed to enhance software development operations (DevOps) and experiences.
  • Constructed a complex Python-based team matching tool powered by LLM (Large-language Model) orchestrated with Guidance, FLAML, and MySQL.
  • Spearheaded metrics and proxies to understand and support team-matching decision processes.
  • Outline a two-stage within-subject qualitative study to explore expert users’ perceptions of LLM-based software matches.

Graduate Researcher, The University of Illinois at Urbana-Champaign (Aug 2018 - Present) #

  • Led 3 human-computer interaction research projects in human-data interaction, individual preference elicitation, and smart home privacy.
  • Designed, prototyped, and built an preference elicitation system using Quadratic Voting mechanisms with Nest.js, MongoDB, and Angular.
  • Evaluated multiple interactive systems using interviews, surveys, questionnaires, and in-lab behavioral experiments.
  • Analyzed experiment data using qualitative and quantitative methods, including open coding, thematic analysis, and bayesian analysis.
  • Supported 2 human-computer interaction research projects in smart home user power dynamics and spreadsheet data analysis workflows.

Graduate Teaching Assistant, The University of Illinois at Urbana-Champaign (Aug 2018 - Present) #

Software Engineer Intern, Salesforce (May 2020 - Aug 2020) #

  • Developed VSCode Plugin for Salesforce developers to reduce XML development time by 2x using TypeScript.
  • Contributed to Open Source RedHat XML VSCode extension (#292) and Salesforce VS Code extension (#2726)

Software Engineer Intern, Salesforce (May 2019 - Aug 2019) #

  • Built pipelines and designed 3 dashboards for front-end cache monitoring using Java, Grafana, and Splunk to visualize daily logs on a billion scale.
  • Optimized dashboard queries by 10x loc for better readability and maintainability.

Machine Learning Research Intern, KKBOX, Machine Learning Team (May 2018 - Aug 2018) #

  • Mentor: Dr. Yian Chen
  • Researched and implemented a natural language processing pipeline for mandarin name-entity recognition with 90%+ accuracy.
  • Designed and built a pattern-based relation extraction pipeline for cross-language music content using 3B+ music data.

Undergraduate Research Assistant, The Chinese University of Hong Kong (Dec 2015 - Dec 2017) #

Web Administrator, RIH, The Chinese University of Hong Kong (2016 - 2017) #

Summer Research Intern, National Center for High-Performance Computing (July 2015 - Aug 2015) #

  • Mentor: Dr.Ann, Hsing-Yen
  • Designed and implemented MySQL database pipeline to retrieve and analyze malicious fast-flux domains.
  • Intern report: Development of Bad Domain Tracking System
  • Contributed to Tsai et al. Using BDTS to detect IP changes of malicious domains over time. TANET 2018.