The Advanced Science Research Center

Applied Science: A Conversation about STEM Higher Education & Science Communication With Malcolm Gladwell
2022-12-02 14:00 - 15:00 (America/New_York) | Advanced Science Research Center (ASRC), 85 St. Nicholas Terrace, New York, NY, 10031, United States
Join us on December 2, 2022 at 2 p.m. for a special “Communicating Your Science” event with Malcolm Gladwell, New York Times best-selling author, social commentator and host of the podcast Revisionist History, where he’ll discuss the role that public higher education institutions can play in communicating science and ensuring that STEM education and research data are available and accessible to all. Malcolm Gladwell’s recently released audio book, I Hate the Ivy League: Riffs and Rants on Elite Education, is a collection of the writer’s podcast episodes on higher education.
During this insightful conversation Gladwell and CUNY Graduate Center Dean for the Sciences Josh Brumberg will discuss:

The role public higher education institutions have in making science more accessible and valuable to the public
How we can make STEM education and careers more accessible to underrepresented communities
How students and faculty at public higher education institutions should be thinking about their roles as science communicators and facilitators of STEM education access
What being a reporter revealed about communicating with the public

To attend, please register at https://bit.ly/3h7FChy There will be time for Q&A.

This event has passed. Watch the video recording below:

Lunch and Learn: How to Reduce Variables in Your In Vivo Research
2022-12-05 11:30 - 12:30 | ASRC 1st Floor Seminar Room, 85 St. Nicholas Terrace, New York, NY, 10031, United States
December 5th from 11:30m-12:30pm in the 1st fl Seminar Room
Have you ever heard of the phrase, “What you put in is what you get out?”
Yes, we’re talking about diet!
Standard laboratory animal diet ingredients can affect brain function, tumor growth, estrogen receptor binding, and so much more. At this Lunch and Learn, hosted by Inotiv, you’ll learn how to make more mindful decisions from project to project on which animal diet will yield less variable, more translatable outcomes.
This event will be hosted by Sabrina Ladarola, Sales Director at Inotiv.
Further info. can be found at inotivco.com or by emailing asrc.event@gc.cuny.edu

ASRC-CCNY Seminar Series in Biochemistry, Biophysics and Biodesign: Tristan Bepler, NYSBC
2022-12-07 12:00 - 13:00 | ASRC Auditorium, 85 St. Nicholas Terrace, New York, NY, 10031, United States
In this weekly seminar series, Tristan Bepler, Group Leader at the Simons Machine Learning Center, New York Structural Biology Center, New York, NY, will be presenting a one-hour talk titled:
Learning to simultaneously locate and classify particles in cryo-electron micrographs without supervision
ABSTRACT In many imaging modalities, objects of interest can occur in a variety of locations and poses (i.e., are subject to translations and rotations in 2d or 3d), but the location and pose of an object does not change its semantics (i.e., the object’s essence). That is, the specific location and rotation of an airplane in satellite imagery, or the 3d rotation of a chair in a natural image, or the rotation of a particle in a cryo-electron micrograph, do not change the intrinsic nature of those objects. Here, we consider the problem of learning semantic representations of objects that are invariant to pose and location in a fully unsupervised manner. We address shortcomings in previous approaches to this problem by introducing TARGET-VAE, a translation and rotation group-equivariant variational autoencoder framework. TARGET-VAE combines three core innovations: 1) a rotation and translation group-equivariant encoder architecture, 2) a structurally disentangled distribution over latent rotation, translation, and a rotation-translation-invariant semantic object representation, which are jointly inferred by the approximate inference network, and 3) a spatially equivariant generator network. In comprehensive experiments, we show that TARGET-VAE learns disentangled representations without supervision that significantly improve upon, and avoid the pathologies of, previous methods. When trained on images highly corrupted by rotation and translation, the semantic representations learned by TARGET-VAE are similar to those learned on consistently posed objects, dramatically improving clustering in the semantic latent space. Furthermore, TARGET-VAE is able to perform remarkably accurate unsupervised pose and location inference. We expect methods like TARGET-VAE will underpin future approaches for unsupervised object generation, pose prediction, and object detection.
This seminar will be presented in the ASRC Auditorium and broadcast via Zoom, with snacks and refreshments to start at 11:30am.
To join these ongoing events via Zoom, please use the link below:
Zoom access>>>
For more information about this hybrid event please contact:
Hyacinth Camillieri
hcamillieri@gc.cuny.edu
