Congrats!!!! 🎉🎉🎉 Go Aggies!

Absolutely looks amazing! Hope I was there!

Thanks for the promotion! 🎉🎉 Super excited to meet and talk with you at Davis!

Thank you Lynn! Excited and looking forward!

I would like to thank my PhD advisor @richardhuskey.bsky.social, for his extraordinary guidance, support, and suggestions!

I also would like to thank my dissertation committee members Cuihua (Cindy) Shen and Erie Boorman for their suggestions, contributions and inputs.

Check our work and read our preprints! 😃

Happy reading!

4. Computational models (Gaussian regression model and Upper Confidence Bound Model) can predict future reading choices by readers’ previous reads and ratings.

5. People with high curiosity personality tend to make more exploratory reads and feel more enjoyable from exploratory reads.

2. Readers tend to read more and more similar and high rating books over time.

3. When readers explore unfamiliar books, they tend to choose books that are associated with high uncertainty (unpopular books or high variance in book ratings)

We investigated near two million book reading records from thirty five thousands readers and confirmed our findings in a behavioral experiment.

We found:
1. People optimize reading enjoyment by learning from past reading experiences, and choose books that are similar to high enjoyable books.

Absolutely! 😃

I would like to give my best thanks to my collaborator, advisor, and life mentor @richardhuskey.bsky.social. This work is impossible without his brilliant and thought-provoking guidance, advice, comments, and questions!