CIS Grace Hopper Lecture: “Data Privacy is Important, But It’s Not Enough”
Our current data ecosystem leaves individuals, groups, and society vulnerable to a wide range of harms, ranging from privacy violations to subversion of autonomy to discrimination to erosion of trust […]
CIS Seminar: “Generative multitask learning mitigates target-causing confounding”
We propose a simple and scalable approach to causal representation learning for multitask learning. Our approach requires minimal modification to existing ML systems, and improves robustness to prior probability shift. […]
A Celebration of the Life of Dr. Max Mintz
The CIS Department and GRASP Lab invite you to please join us on Thursday, November 17th, at 3:30pm as we celebrate the life and legacy of Dr. Max Mintz, Professor […]
CIS Seminar: “Designing Hardware for Cryptography and Cryptography for Hardware”
There have been few high-impact deployments of hardware implementations of cryptographic primitives. We present the benefits and challenges of hardware acceleration of sophisticated cryptographic primitives and protocols, and describe our […]
CIS Seminar: “Designing Hardware for Cryptography and Cryptography for Hardware”
There have been few high-impact deployments of hardware implementations of cryptographic primitives. We present the benefits and challenges of hardware acceleration of sophisticated cryptographic primitives and protocols, and describe our […]
CIS Seminar: “The Long Arm of Theoretical Computer Science: A Case Study in Blockchains/Web3”
Blockchains that support a general contract layer (e.g., Ethereum) export the functionality of a general-purpose, ownerless, and open-access computer that can enforce property rights for digital data. How is such […]
CIS Seminar: “Rater Equivalence: An Interpretable Measure of Classifier Accuracy Against Human Labels”
In many classification tasks, the ground truth is either noisy or subjective. Examples of noisy ground truth include: does this radiology image show a cancerous growth? does this radar data […]
CIS Seminar: “Equilibrium Complexity and Deep Learning”
Deep Learning has recently made significant progress in learning challenges such as speech and image recognition, automatic translation, and text generation, much of that progress being fueled by the success of […]
ESE/CIS Joint Seminar: “Future Heterogeneous Systems Need More First-Class Citizens”
For those that are not able to attend please join on Zoom:
https://upenn.zoom.us/j/93664182228?pwd=NVBHT0wzaERxaWxRUERWYjV2eXorZz09
Meeting ID: 936 6418 2228
Passcode: 096853
CIS Seminar: ” Rich Babies, Poor Robots: towards rich sensing, continuous data and multiple environments”
For those that may not be able to attend the talk please sue this zoom link:
https://upenn.zoom.us/j/92928358554?pwd=MWdDU0lJRmE3U0hDWUdmU284UmNGZz09
Meeting ID: 929 2835 8554
Passcode: 488035