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Stanford CS231N Deep Learning for Computer Vision I 2025

Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This course is a deep dive into deep learning methods with a focus on end-to-end models for core vision tasks, alongside modern approaches such as transformers, diffusion models, and visual-language models that power today’s AI systems. During the 10-week course, students will learn to implement and train their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. Additionally, the final assignment will give them the opportunity to train and apply multi-million parameter networks on real-world vision problems of their choice. Through multiple hands-on assignments and the final course project, students will acquire the toolset for setting up deep learning tasks and practical engineering tricks for training and fine-tuning deep neural networks. https://online.stanford.edu/courses/cs231n-deep-learning-computer-vision

Battery-free skin-conformal wearable system can measure electrocardiogram signals

A research team led by Prof. Jerald Yoo from the Department of Electrical and Computer Engineering at Seoul National University (SNU) has developed a skin-conformal wearable health care system, “SkinECG,” capable of measuring electrocardiogram (ECG) signals without a battery. By combining energy harvesting with human body–coupled power transfer, the study presents a new solution to one of the most critical challenges in wearable devices: power supply.

The findings are published in Science Advances.

Wearable health care systems are emerging as next-generation medical technologies that enable real-time monitoring of physiological signals through body-worn sensors, allowing early detection of disease-related abnormalities.

Jacob Barandes — “A New Formulation of Quantum Theory”

Talk by Jacob Barandes (Harvard University)
Seminar Website: https://harvardfop.jacobbarandes.com/
YouTube Channel: / @foundationsofphysicsharvard.
Foundations of Physics @Harvard Seminar Series.
April 12, 2023.

Abstract: In this talk, I will present a novel, exact correspondence between stochastic-process theory and quantum theory. On the one hand, this stochastic-quantum correspondence means that one can use the Hilbert-space tools of quantum theory to model real-world stochastic processes beyond the usual Markov approximation, generalizing previous stochastic approaches to quantum theory as well as potentially opening up new applications for quantum simulators and quantum computers. On the other hand, the stochastic-quantum correspondence implies that one can replace the instrumentalist textbook axioms of quantum theory with much more physically transparent axioms. The result is a clearer physical picture underlying quantum theory that is consistent with the standard no-go theorems, helps clarify the meaning of signature features of quantum theory like interference and entanglement, and has potential implications for addressing the measurement problem.

Small Study Shows One-time Cell Therapy Can Control HIV Infection

Unlike previous HIV “cures” involving cancer patients given bone marrow stem cells from a donor with a rare genetic mutation that resists HIV infection, researchers said CAR-T could be used by a much broader patient population. The Phase 1 trial involved CAR-T, a one-time therapy in which a patient’s T-cells are extracted, altered and multiplied in a lab and infused back into ⁠their body. In this case, the CAR-T targeted the CD4 and CCR5 binding sites of the HIV.

Of three trial patients ‌treated with a standard CAR-T dose, researchers said two maintained undetectable to ‌very low levels of HIV after stopping antiretroviral therapy — one for over two years so far and another for nearly a year. “The two that have ‌been off (HIV drugs) the longest and doing well were importantly diagnosed pretty quickly and put on therapy pretty quickly,” said Dr. Steven Deeks, professor of medicine at the University of California, San Francisco and the study’s lead investigator.

Currently, CAR-T ‌treatments are available for several types of blood cancer, and are being developed for autoimmune diseases like lupus and scleroderma. Tap the link to learn more about the recent study.

Re-engineering an HIV patient’s own immune cells to find and destroy the virus succeeded in controlling the infection in a small first-in-human study, but researchers said work is needed to confirm ⁠the findings and determine which patients are most likely to benefit.

Designing in situ power stations for future Mars missions

You’re in the lab analyzing Martian regolith samples within your cozy Mars habitat serving on the fifth human mission to Mars. The power within the habitat has been flowing flawlessly thanks to the MARS-MES (Mars Atmospheric Resource & Multimodal Energy System), including the general habitat lighting, science lab, sleeping quarters, exercise equipment, the virtual reality headsets the crew use for rest & relaxation, oxygen and fuel generation, and water. All this from converting the Martian atmosphere into workable electricity.

While this scenario might be decades away, scientists on Earth are working hard to make this concept a reality today. This includes a team of scientists from China who propose using a novel concept for converting the thin Martian atmosphere into heat and electricity. Their findings were recently published in National Science Review and could help revolutionize how electricity is produced on Mars through a process called in situ resource utilization (ISRU) without the need for power or power supplies being shipped from Earth.

For the study, the researchers propose several concepts for producing power and electricity on a future human Mars mission, including Martian air capture, in situ power generation and storage, and life support resources transformation. The team notes all these methods carry their own benefits and challenges while emphasizing the importance of using ISRU for powering future human Mars missions.

How everyday devices could train AI faster while keeping personal data on-device

A new method developed by MIT researchers can accelerate a privacy-preserving artificial intelligence training method by about 81%. This advance could enable a wider array of resource-constrained edge devices, like sensors and smartwatches, to deploy more accurate AI models while keeping user data secure.

The MIT researchers boosted the efficiency of a technique known as federated learning, which involves a network of connected devices that work together to train a shared AI model.

In federated learning, the model is broadcast from a central server to wireless devices. Each device trains the model using its local data and then transfers model updates back to the server. Data are kept secure because they remain on each device.

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