David M. Andrzejewski
Software, systems, data
Bio Sketch
Prior to my current role, most recently I had worked at Sumo Logic, which I joined as a Software Engineer pre-launch (Series A) in 2011. I had the opportunity to play a variety of Engineering roles over the course of the company's journey to the 2020 IPO and beyond. When I left the company in 2024, I was focused on the development of product capabilities that take advantage of machine learning and proprietary datasets in order to help customers ensure the reliability and security of their business-critical software applications.
I had also co-organized the SF Bay Area ML meetup from 2011 to 2019, organizing more than 60 in-person events while accumulating 7500 members and 16k Twitter followers. Co-organizing the meetup was great fun and involved wrangling speakers, venues, sponsors, logistics, promotion, social, video, and (far too much) pizza. I have also maintained connections to the broader ML community via reviewing activities including conferences such as NeurIPS, ICLR, ICML, AISTATS, IJCAI, and AAAI, as well as some technical books (mostly O'Reilly Media).
Prior to Sumo Logic, I was a Postdoctoral Research Staff Member at Lawrence Livermore National Laboratory (LLNL) working on knowledge discovery in the national security domain. Before that, I was a student of at the fabulous University of Wisconsin--Madison, and was fortunate to have some fantastic internship experiences at GE Healthcare and Microsoft Research.
Selected Works
The main site contains more details and materials than you probably care to wade through. The links below aim to provide a more curated subset of recent and relevant writings, projects, and talks. The "Work themes" page should also serve as a good starting point summarizing key areas related to my work at Sumo Logic.
Personal blog posts
- Conway and Coase on Collaboration in Software
- Engineering as Shadow Price Discovery
- Models and iteration speed in coding
- Graphs, combinatorial optimization, and product development
Recent projects at Sumo Logic
- Accelerated vendor migrations with LLMs
- How Confidence Scoring Is Delivering Superior Cybersecurity Threat Analysis
- Patents and Applications
- Global Confidence: Using crowdsourcing and machine learning to scale your SOC resources
- Troubleshooting Outages at 3 AM with Alert Response
Technical conference talks
- Reliable Machine Learning (Scale By The Bay 2019)
- Understanding Software System Behavior with ML and Time Series Data (QCon.ai 2018)
- Privacy aware data science in Scala with monads and type level programming (Scale By The Bay 2018)