Boston Chapter of IEEE Computer Society and GBC/ACM
7:00 PM, Thursday, 24 April 2025
MIT Room 32-G449 (Kiva) and online via Zoom
Learning, engineering, and targeting cell states in cancer
Ava Amini
Please register in advance for this seminar even if you plan to attend in person at
https://acm-org.zoom.us/webinar/register/WN_Msf8F_LXTcSD2mWpDeVx5A
After registering, you will receive a confirmation email containing information about joining the webinar.
Indicate on the registration form if you plan to attend in person. This will help us determine whether the room is close to reaching capacity. We plan to serve light refreshments (probably pizza) before the talk starting at around 6:30 pm. Letting us know you will come in person will help us determine how much pizza to order.
We may make some auxiliary material such as slides and access to the recording available after the seminar to people who have registered. Abstract:
Cancer is often treated using a reductionist approach: distilled to an individual subtype, mutation, or phenotype. But fundamentally, cancers are complex ecosystems that necessitate systems-level understanding and intervention. Addressing this problem is equal parts biology and computer science. In Project Ex Vivo, a joint cancer research collaboration between Microsoft Research and the Broad Institute, we are envisioning a new, constructionist paradigm for precision oncology, one powered by the bottom-up integration of computation and experimentation to understand the complexity of cell state ecosystems in cancer. In this talk I will share our recent efforts to build AI models to better define, model, and therapeutically target cell states in cancer.
Bio:
Ava Amini is a Principal Researcher at Microsoft Research in Cambridge, MA. Her research focuses on developing new AI methods to understand and design biology, with the ultimate aim of realizing precision biomedicines that improve human health. She is a co-lead of Ex Vivo , a collaborative effort between Microsoft and the Broad Institute, that is focused on defining, engineering, and targeting cell states in cancer.
In addition to research, Ava is passionate about AI education and outreach — she is a lead organizer and instructor for MIT Introduction to Deep Learning , an in-person and global course on the fundamentals of deep learning.
Ava completed her PhD in Biophysics at Harvard University and the Massachusetts Institute of Technology (MIT), where she was advised by Sangeeta Bhatia at the Koch Institute for Integrative Cancer Research and supported by the NSF Graduate Research Fellowship. Ava received her Bachelor of Science in Computer Science and Molecular Biology from MIT.
Directions to 32-G449 - MIT Stata Center, 32 Vassar Street, Cambridge, MA: Please use the main entrance to the Stata Center at 32 Vassar Street (the entrance closest to Main street) as those doors will be unlocked. Upon entering, proceed to the elevators which will be on the right after passing a large set of stairs and a MITAC kiosk. Take the elevator to the 4th floor and turn right, following the hall to an open area; 32-G449 will be on the left. Location of Stata on campus map
This joint meeting of the Boston Chapter of the IEEE Computer Society and GBC/ACM will be hybrid (in person and online).
Up-to-date information about this and other talks is available online at https://ewh.ieee.org/r1/boston/computer/. You can sign up to receive updated status information about this talk and informational emails about future talks at https://mailman.mit.edu/mailman/listinfo/ieee-cs, our self-administered mailing list.
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