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SCS
Student
Seminar
Series
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abstracts
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previous talks
scs seminars
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SCS
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CMU
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All SSS talks can be carried out either in person or through Zoom.
Fall 2021 Schedule
Mon, Aug 30 |
Fri, Sep 03 |
Mon, Sep 06 |
Fri, Sep 10 |
Mon, Sep 13 |
Fri, Sep 17 |
Mon, Sep 20 |
Fri, Sep 24 |
Mon, Sep 27 |
Fri, Oct 01 |
Mon, Oct 04 |
Fri, Oct 08 |
Mon, Oct 11 |
Fri, Oct 15 |
Mon, Oct 18
Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data
Presented by Helen Zhou, Mon, Oct 18 12-1pm, Remote https://cmu.zoom.us/j/3710473554
Since the COVID-19 pandemic began, the United States's case fatality rate (CFR) has plummeted. Using national and Florida data, we unpack the drop in CFR between April and December 2020, accounting for such confounders as expanded testing, age distribution shift, and detection-to-death lags. Guided by the insight that treatment improvements in this period should correspond to decreases in hospitalization fatality rate (HFR), and using a block-bootstrapping procedure to quantify uncertainty, we find that although treatment improvements do not follow the same trajectory in Florida and nationally (with Florida undergoing a comparatively severe second peak), by December, significant improvements are observed both in Florida and nationally (at least 17% and 55% respectively). These estimates paint a more realistic picture of improvements than the drop in aggregate CFR (70.8%–91.1%). We publish a website where users can apply our analyses to selected demographics, regions, and dates of interest.
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Fri, Oct 22 |
Mon, Oct 25
Toward fairer and more transparent civic participation
Monday, October 25th, 2021 from 12-1 pm in GHC 6501.
Presented by Bailey Flanigan, CSD
Citizens' assemblies are a form of civic participation in which a panel of randomly-chosen constituents convenes to hear testimony from experts, deliberate, and ultimately make a policy recommendation on a political issue. These assemblies offer a unique combination of features: they give everyday people the opportunity to participate directly in political decision-making, while also ensuring that they are well-informed and have spent time digesting and hearing others' perspectives on the issues. In the recent decades, citizens' assemblies are experiencing a surge in popularity worldwide: they are now being administered by more than 40 organizations in over 25 countries; are commissioned by public authorities on municipal, regional, national and supranational levels; and have recently led to the legalization of same-sex marriage in Ireland.
Our research on citizens' assemblies aims to ensure that the process by which participants are selected is fair [1,2] and transparent [3]. We provide a set of algorithms for selecting participants of citizens' assemblies, each which is guaranteed to be maximally fair for a different fairness notion [2], propose a simple and transparent method of panel selection by uniform lottery, which we prove is always possible to carry out without meaningful loss in fairness [3], and discuss the prospect of end to end fairness, which deals with giving all members of the population an equal chance of participation [1], rather than all self-identifying willing participants.
[1] Neutralizing Self-Selection Bias in Sampling for Sortition
[2] Fair Algorithms for Selecting Citizens' Assemblies
[3] Fair Sortition made Transparent
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Fri, Oct 29 |
Mon, Nov 01 |
Fri, Nov 05 |
Mon, Nov 08 |
Fri, Nov 12 |
Mon, Nov 15 |
Fri, Nov 19
Training Computer Vision Models with Synthetic Images
Friday, Nov 19, 2021, from 12-1pm in GHC 6501. Presented by Roger Iyengar
Wearable Cognitive Assistance (WCA) applications have the potential to help users with tasks such as assembling physical objects. These applications run on a headset with a camera, and process live image streams to determine when steps of the task have been completed. Images are processed using DNNs that must be trained on thousands of labeled images. Capturing and labeling these images is a huge amount of work, especially when the models must be trained to recognize many different task states. Training these models on synthetic data would thus reduce the amount of work required to develop these models. I will discuss some work that I have done generating synthetic images based on CAD files, and then training computer vision models using this data.
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Mon, Nov 22 |
Fri, Nov 26 |
Mon, Nov 29 |
Fri, Dec 03 |
Mon, Dec 06
High-Dimensional Expanders from Chevalley Groups
from 12-1pm in GHC 6501. Presented by Kevin Pratt
High-dimensional expanders are a relatively new class of objects that have motivated work on quantum LDPC codes, locally testable codes, and the resolution of the Mihail-Vazirani conjecture on matroids. Despite this, there are only two known families of (local) high-dimensional expanders. In this talk I will discuss constructions of several new families obtained in joint work with Ryan O'Donnell. This generalizes a previous construction due to Kaufman and Oppenheim.
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Fri, Dec 10
Centralized Library Management for Heterogeneous IoT Devices
Internet-of-Things (IoT) devices have become attractive targets for attack. One potential threat arises from the extensive use of third-party libraries in IoT devices.
In this talk, I will first present my analysis results demonstrating the widespread, problematic library management practices and delays in applying security patches among IoT device vendors.
I will discuss Capture, a novel architecture for deploying IoT device firmware by allowing devices on a local network to leverage a centralized, trusted hub to manage third-party libraries for them.
I propose a new Virtual Device Entity interface that facilitates access control between mutually-distrustful local devices to ensure isolation.
Evaluation results on comprehensive benchmarks show that Capture incurs low overhead, and a single hub can support hundreds of local devices.
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Mon, Dec 13 |
Fri, Dec 17 |
2022 Spring Feb 18, 25, 28 are unavailble
General Info
The Student Seminar Series is an informal seminar
for SCS graduate students to communicate ideas.
Each meeting starts at noon and lasts 1 hour. Lunch is
provided by the Computer Science Department (thanks to
Debbie Cavlovich!). At each meeting, a different student
speaker will give an informal, 40-minute talk about his/her research,
followed by questions/suggestions/brainstorming. We try to attract
people with a diverse set of interests, and encourage speakers to
present at a very general, accessible level.
So why are we doing this and why take part? In the best case
scenario, this will lead to some interesting cross-disciplinary work
among people in different fields and people may get some new ideas
about their research. In the worst case scenario, a few people will
practice their public speaking and the rest get together for a free
lunch.
Steps for Scheduling Talks
To schedule a talk, pick up a free slot and send your (a) name, (b) department, (c) talk title, (d) talk abstract,
and (e) a link to your home page to sss@cs at least TWO WEEKS before your talk.
Each speaker may schedule at most 3 talks per semester.
For SCS students willing to give presentations
counting toward fulfilling their speaking skills requirement,
SSS is an ideal forum to do so.
For CSD students, these are roughly 3 steps:
- Send you talk details as listed above to SSS at least THREE WEEKS before the talk.
- After you are confirmed with your SSS slot, go to
Speakers Club Calendar
and add your talk to it.
- On the day of your talk, bring Speakers Club Evaluation Forms for your evaluators to use.
Each talk starts at noon and lasts 1 hour. The room is booked from 11:30am (30 mins before the talk) to 1:30pm (30 mins after the talk).
Students outside of CSD will need to check with their
respective departments regarding the procedure. As another example,
ISRI students fulfill their speaking requirements by attending a
semesterly Software Research Seminar and giving X number of
presentations per school year. If you have experience with your
department that might help others in your department, please feel free
to contribute your knowledge by emailing us. Thank you!
SSS Coordinators
Juncheng Yang, CSD
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