Jacob Kelly

@jacobjinkelly

Research Intern . Machine Learning and Computational Biology. Undergrad in Computer Science, Math, and Statistics.

Toronto, Ontario
Vrijeme pridruživanja: lipanj 2018.

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  1. 1. velj

    “Writing things in your to-do list and coming back to them later helps you focus, but it comes at the cost: you’ve now converted an interesting idea into work.” Improvising for Productivity by via

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  2. 18. sij

    "It’s easiest if you get to meet people in person, several times. If you meet someone three times in three months, and notice detectable improvement each time, pay attention to that."

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  3. 18. sij

    "If you actually figure out how to help other investors you respect, and to really help good founders, then good investment opportunities will come your way."

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  4. 18. sij

    "Putting a lot of energy into networking actually works, as long as you aren’t just trying to touch base when people can find some time away from their crazy calendars to grab coffee." "how to invest in startups"

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  5. proslijedio/la je Tweet
    12. sij

    Does biology have truly difficult ideas? Studying math, comp sci, physics, etc., one quickly encounters material that is hard to truly grasp (and many of us get to a point where we mentally just can't go further, while some others can). Does this exist in biology? If not, why?

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  6. 1. sij

    fav books of 2019: 1. Finding Meaning in an Imperfect World 2. The Person and the Situation 3. The Power Broker 4. The Emperor of All Maladies 5. Models of My Life 6. I Will Teach You to be Rich 7. Understanding Power 8. Personal History more on my blog:

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  7. 29. pro 2019.

    - Maintain tight feedback loops after school to stay on track towards your goals - “I had a great conversation with someone I met at a group dinner. When I told my friend about it, she asked: “What does he do?” I have no idea. I never asked.” by

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  8. 28. pro 2019.
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  9. 21. pro 2019.

    pick one person to listen to for advice. otherwise you'll end up "shopping" for the advice you want to hear, or taking the average of everything you hear. from "who should founders listen to for advice"

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  10. 19. pro 2019.

    Also a great case study of the development of single-cell RNA-Seq and why it's such an exemplar of the paradigm shift in experimental biology

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  11. 19. pro 2019.

    Really liked the picture frame analogy to compare classical experimental design (where we make perturbations from a few known states) to experiments designed to maximize the powers of inference (by sampling randomly, and using structure to interpolate)

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  12. 19. pro 2019.

    How to study something systematically if it cannot be done exhaustively? From opening talk at LRML workshop by Aviv Regev, "Design for Inference: How to learn the convolutions of life" (starts at 10:45)

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  13. 19. pro 2019.

    “I heard here’s my network a lot today...it would be nice if we start by articulating what we’re trying to capture...not only a task of predicting something cool in mind, but understanding something new about biology”

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  14. 19. pro 2019.

    Also the idea of different levels of abstraction in biology (e.g. from molecules to physiology to evolution), and that ultimately evolution is the underlying generative process which we should focus more on trying to model explicitly

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  15. 19. pro 2019.

    Another theme I found interesting was the nature of biological data, specifically its sparsity, and the underlying structure which allows us to interpolate over this sparsity

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  16. 19. pro 2019.
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  17. 19. pro 2019.

    “We’ve seen a lot of beautiful tSNE images...I haven’t seen enough work in trying to understand these latent variables, understand what they mean, what they represent.” - Dana Pe'er at Learning Meaningful Representations of Life Workshop @

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  18. proslijedio/la je Tweet
    13. pro 2019.

    Want a sneak peak for what's next with Neural ODEs? I will be talking about Higher Order Autodiff in JAX. Work with , , and ! Program Transformations: Sat. 14, Room West 114 Poster: 12-14:00 Talk: 17:00-17:20

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  19. 8. pro 2019.

    Really want to learn more about biology now

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  20. 7. pro 2019.

    Really interesting to learn how improving computational methods can help to accelerate progress in this area

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