Donald Loveland

About me

Research Scientist Snap Research

I am a Research Scientist on the User Modeling and Personalization team at Snap Research. Simultaneously, I am completing my Ph.D. in Computer Science and Engineering at the University of Michigan, Ann Arbor, where I am advised by Danai Koutra. My doctoral work has been supported by an NSF Graduate Research Fellowship and a Rackham Merit Fellowship.

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Donald Loveland

01 / Research

Some of my
recent work

I work on large language models for recommendation, from item representations to personalization. I also study how graph structure shapes what models learn and how they reason about connections.

Explore research
Original figure comparing randomly initialized item embeddings with centroid-initialized embeddings that preserve semantic clusters.

Recent paper · Item semantics

What should a new item token know?

Loveland et al. · Preprint 2026

02 / Experience

Research and
industry experience

From scientific machine learning at national labs to graph learning and personalization in industry. A look at the places and people that have shaped my work.

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  1. Present

    Snap Research 

    Research Scientist

  2. Doctoral research

    University of Michigan 

    Computer Science & Engineering

  3. Summer 2025

    Amazon 

    Research internship

Earlier work at Snap, MIT Lincoln Laboratory & LLNL 

03 / Mentorship

Supporting other researchers

As a first-generation college student, I am deeply grateful for the guidance I have received throughout my academic and professional career, and I aim to pay this forward by supporting students from similar backgrounds. I have served as a peer mentor for first-generation undergraduate students throughout my graduate studies, and while at Lawrence Livermore National Laboratory, I helped organize and mentor a two-week machine learning challenge focused on teaching students how to conduct applied research. Please feel free to reach out if you’d ever like to chat.

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From the paper

View figure in paper ↗