Project 1: Engineering Practices for Machine Learning Engineers – the state-of-the art

Machine Learning has been come popular among software engineers with available frameworks, tools, infrastructure for performing large scale data processing tasks. In the article “Software Engineering for Machine Learning: A Case Study”, the authors described practices using Artificial Intelligence among engineers at Microsoft. Based on a nine stage of machine learning workflow, the authors describe challenges as well as best practices at Microsoft. The work is interesting and should be replicated at a larger scale. We are interested in questions, such as RQ1: What are Machine Learning workflows used in the investigated organizations? RQ2: What are software/ hardware infrastructure used ? RQ3: What kind of Software Engineering tasks that Machine Learning techniques are applied? RQ4: What are challenges of using ML in such tasks? RQ5: What are the best practices? Research approach: interviews, surveys,…

Project 2: Risk management in Software Startups

Starting up a new venture is a high risk activity. Majority of startups fail within the first two years of their creation. Even though, software startups are experimental by nature and an entrepreneurial process is opportunistic, there is still a distinction between taking calculated risks, and neglect of best engineering practices. Empirical evidence reveals that one of the key difficulties to practice software engineering in start-ups is to manage multiple areas at once. Existing work about Software Engineering activities in startup context, including requirement engineering, architecture, prototyping, customer development and ecosystem infers the effectiveness of planning, controlling activities in startup product development. However, there is no explicit investigation of project or product management skills in software startups. Questions: RQ1. What kind of risks are awared by software startups at the early stage? RQ2. Are risks prioritized? and how? RQ3. How are these risks monitored during early stage startups? Research approach: Empirical studies, i.e. interviews with startup companies.

Contact Person: Anh Nguyen-Duc