Recommendation systems, being an Applied Scientist & Building a good research career | Mina Ghashami

Mina Ghashami is an Applied Scientist in the Alexa Video team at Amazon Science alongside being a lecturer at Stanford University. Prior to joining Amazon she was a Research Scientist at Visa Research working on recommendation systems built on transactions from users and few other projects. She completed her PhD in Computer Science from University of Utah followed by a PostDoctoral position at Rutgers University. At Amazon she is mainly focused on Video based ranking recommendation systems, something we talk about in detail in this conversation.
Time stamps of the conversation
00:00:50 Introductions
00:01:40 Alexa Video - Ranking and Recommendation research
00:05:25 Feature engineering for recommendation systems
00:08:30 Ground truth for training recommendation systems
00:12:46 What does an Applied Scientist do? (at Amazon)
00:19:17 What got you into AI? And specifically recommendation systems
00:24:30 Matrix approximation
00:27:15 Challenges in recommendation research
00:32:00 What's more interesting, theoretical or applied side of research?
00:37:10 Over parametrization vs generalizability
00:39:55 Managing academic and industry positions at same time
00:46:26 Should one do a PhD for research roles in industry?
00:50:00 Skills learned while pursuing a PhD
00:54:22 Deciding industry vs academia
00:56:20 Coping up with research in deep learning
01:02:14 What makes a good research dissertation?
01:04:16 Advice to young students navigating their interest in machine learning
To learn more about Mina:
Homepage: mina-ghashami.github.io/
Linkedin: / minaghashami
Research: scholar.google.com/citations?...
Also check-out these talks on all available podcast platforms: jayshah.buzzsprout.com
About the Host:
Jay is a PhD student at Arizona State University.
Linkedin: / shahjay22
Twitter: / jaygshah22
Homepage: www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
**Disclaimer: The information contained in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.**

[@saliexplore3094]

What a great podcast. Mina is a great guest, starting each answer with enough context for listeners to follow.

[@convolutionalnn2582]

1) Do I have to know the whole maths derivation of Supervised and Unsupervised Algorithms if i wanna do research in RL
2) I am now learning maths for ML....I am able to use most of the common Supervised and Unsupervised Algorithms but can't derive....Should I do DL course or wait until i am able to derive the algo I have learn ? As my end goal is research in RL

[@Jay-Shah]

Derivation of algorithms is not always needed while working with ML problems. However, if you’re planning to get into research, an understanding of that might be very useful while trying to improve an existing method or algorithm.

[@dhruvpatel4948]

Just a suggestion (after watching few of your episodes) keep your questions brief and to the point. Most of your questions can be asked in one or two sentences but at times feel like you’re just repeating yourself. Otherwise good pod attempt. Keep it up.