Nadia Nahar
Details
Nadia Nahar is a Software Engineering Ph.D. student at Carnegie Mellon University. Nadia's research topic is Software Engineering for Machine Learning, often referred to as SE4ML/SE4AI. Her recent publication on collaboration challenges in building ML production systems has received ACM SIGSOFT Distinguished Paper Award at the 44th International Conference on Software Engineering (ICSE) 2022. She spent her last summer at Microsoft in a software engineering internship in the Deep Learning Inference Service team.
Talk Outline:
The talk will cover the discussion on the findings of her paper, "Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process" which received the award - https://conf.researchr.org/details/icse-2022/icse-2022-papers/153/Collaboration-Challenges-in-Building-ML-Enabled-Systems-Communication-Documentation
Topics:
- Machine Learning (ML) in software products
- From models to products
- How the product view is often neglected in ML practice
- Productionizing ML needs a team effort
- Stories of the interviewees from the collaboration paper
- What can we learn from the perspective of requirements, training data, and model-product integration
Tentative agenda:
6:00 - 6:30 Networking/ Intro
6:30 - 7:30 Talk by Nadia
7:30 - 8:00 Q&A
Parking and transit info:
This meeting will be held in the Microsoft Building: 3709 157th Ave NE, Redmond, WA 98052
Link to a map of the campus: Google map, Apple map
Parking: You will find a campus parking map here: visitor
COVID Protocols:
All attendees will need to check in with the receptionist team upon arrival. Below is the current MS COVID policy.
Complete the health check app.
Upload Vaccinate card & obtain certificate (aka.ms/healthcheck)
Negative Covid test (done at least 7 days prior to event) No need to bring on-site
Previous Covid-19 recovery
-OR-
Options at check-in:
Provide vaccination proof, verbally attest to a negative covid test or recent Covid- 19 recovery
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Data Circles (formerly SeaWiDS) is a supportive community that focuses on inspiring and empowering women in data science through professional development, knowledge sharing, and mentorship. We wish to lift up women at all levels of their data science journey to find community, support, and growth. We strive to host a diverse group of speakers including women of color, immigrants, veterans, LGBTQ women, and women with disabilities.
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