Name: Stanford Seminar - How to Design Addictive Games @stanfordonline
Uploaded: 2026-09-27T08:17:00-05:00
Duration: 8 min 17 s
Description: Stanford Seminar - How to Design Addictive Games

Stanford Seminar - How to Design Addictive Games

Stanford Online 2026-09-27 | Stanford Seminar - How to Design Addictive Games

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 18

Stanford Online 2024-03-26 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 17

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 16

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 15

Stanford Online 2024-03-25 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 14

Stanford Online 2024-03-24 | o follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 13

Stanford Online 2024-03-23 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 12

Stanford Online 2024-03-22 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 11

Stanford Online 2024-03-21 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 10

Stanford Online 2024-03-20 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Course Overview: Change Management: Reskilling in the Age of Analytics and AI

Stanford Online 2024-03-19 | Learn more and enroll: stanford.io/4acykQ2

Advancements in artificial intelligence (AI) and data analytics have the power to radically transform the way our businesses operate. But there’s a catch: new technology is only as good as the people using it and the processes in place to harness it.

In this digital transformation course, you will learn how to reskill, restructure, and reimagine the work of your team(s) to capitalize on the opportunities presented by new technology. You’ll apply three lenses of organizational change management–strategic design, power and politics, and culture–to navigate the restructuring of data, analytics, and artificial intelligence initiatives. Through exclusive interviews with digital transformation leaders, you will gain firsthand insights into how leading companies are navigating change and optimizing their teams for the future of work.

#reskill #changemanagement

Stanford Seminar - The State of Design Knowledge in Human-AI Interaction

Stanford Online 2024-03-19 | March 1, 2024
Krzysztof Gajos, Harvard University

My research is at the intersection of HCI and AI. I design, build and evaluate interactive systems that have some kind of machine intelligence under the hood. I strive to build intelligent interactive systems that are useful, that give people a meaningful sense of control, and whose behavior aligns with the mental models held by their users. This is challenging because the underlying AI technology can be occasionally wrong, it delivers the most value if it is allowed to act proactively, and it frequently behaves in unexpected ways. In the past two decades, the human-AI interaction community has grown and has made substantial progress in producing useful design knowledge that addresses these challenges. Machine intelligence is now present in many real-world interactive systems from nearly invisible (like predictive text helping with mobile text entry), to highly consequential (like AI-powered decision-support systems). However, there are also some important gaps in our knowledge. For example, the results of our behavioral experiments indicate that adaptive user interfaces require more cognitive effort to operate than we had assumed, predictive text changes the content of what people write instead of just making text entry more efficient, and decision makers presented with AI-generated decision recommendations and explanations rarely engage cognitively with the content of what the AI communicates. Meanwhile the results of our other studies point out some unverified assumptions underlying the common choices of what (and whose) problems we solve with AI in clinical and public sector settings.

This said, I believe that we can design useful and usable AI-powered interactive systems but the relevant design knowledge is relatively knew and is still a work in progress. The contemporary enthusiasm for using machine intelligence in interactive systems is an opportunity to grow our knowledge. It is also a danger in that it creates conditions where following the best practices of others, without having the time or opportunity to examine them, can turn unverified assumptions into fundamental principles of our field.

About the speaker:
Krzysztof Gajos is a Gordon McKay professor of Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. Krzysztof s current interests include 1. Principles and applications of intelligent interactive systems; 2. Tools and methods for behavioral research at scale (e.g., LabintheWild.org); and 3. Design for equity and social justice. He has also made contributions in the areas of accessible computing, creativity support tools, social computing, and health informatics.

Krzysztof received his Ph.D. from the University of Washington and his M.Eng. and B.Sc. degrees from MIT. He was a postdoctoral researcher at Microsoft Research at the Adaptive Systems and Interaction group. From 2013 to 2016 Krzysztof was a coeditor-in-chief of the ACM Transactions on Interactive Intelligent Systems (ACM TiiS), he was the general chair of ACM UIST 2017, and he was a program co-chair of the 2022 ACM Conference on Intelligent User Interfaces. His work was recognized with a Sloan Fellowship and with best paper awards at ACM CHI, ACM COMPASS, and ACM IUI. In 2019, he received the Most Impactful Paper Award at ACM IUI for his work on automatically generating personalized user interfaces.

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 9

Stanford Online 2024-03-19 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 8

Stanford Online 2024-03-18 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 7

Stanford Online 2024-03-17 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 6

Stanford Online 2024-03-16 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 5

Stanford Online 2024-03-15 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 4

Stanford Online 2024-03-14 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford Seminar - Robot Learning in the Era of Large Pretrained Models

Stanford Online 2024-03-13 | February 23, 2024
Dorsa Sadigh, Stanford University

In this talk, I will discuss how interactive robot learning can benefit from the rise of large pretrained models such as foundation models. I will introduce two perspectives. First I will discuss the role of pretraining when learning visual representations, and how language can guide learning grounded visual representations useful for downstream robotics tasks. I will then discuss the choice of datasets during pretraining. Specifically, how we could guide large scale data collection, and what constitutes high quality data for imitation learning. I will discuss some recent work around guiding data collection based on enabling compositional generalization of learned policies. Finally, I will end the talk by discussing a few creative ways of tapping into the rich context of large language models and vision-language models for robotics.

About the speaker: https://dorsa.fyi/

More about the course can be found here: stanfordasl.github.io/robotics_seminar

View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford Enterprise Education for Transformation: Unleash Your Organization’s Potential

Stanford Online 2024-03-13 | The Stanford Center for Professional Development is a global leader in professional and executive education located on the Stanford University campus.

We leverage Stanford’s multidisciplinary expertise in innovation, technology, and business, as well as the Silicon Valley ecosystem to deliver programs that help teams, organizations and communities transform.

Our Stanford Enterprise Education for Transformation programs blend the key pillars of business, science, and engineering so you can elevate your organization's readiness to face its most pressing transformation challenges.

Learn more on our website: stanford.io/49ZUDsv

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 3

Stanford Online 2024-03-13 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford CS221 I Externalities and Dual-Use Technologies I 2023

Stanford Online 2024-03-12 | For more information about Stanford’s online Artificial Intelligence programs, visit: https://learn.stanford.edu/Social-AI-YouTube.html

To follow along with the course, visit the course website:
stanford-cs221.github.io/autumn2023

Speaker: Veronica Rivera
vrivera2017.github.io

Percy Liang
Associate Professor of Computer Science and Statistics at Stanford University
https://cs.stanford.edu/~pliang/

Dorsa Sadigh
Assistant Professor of Computer Science and Electrical Engineering at Stanford University

Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford CS221 I The AI Alignment Problem: Reward Hacking & Negative Side Effects I 2023

Stanford CS221 I Encoding Human Values I 2023

Stanford Online 2024-03-12 | For more information about Stanford’s online Artificial Intelligence programs, visit: https://learn.stanford.edu/Social-AI-YouTube.html

To follow along with the course, visit the course website:
stanford-cs221.github.io/autumn2023

Speaker: Diana Acosta-Navas
https://ethicsinsociety.stanford.edu/people/diana-acosta-navas

Percy Liang
Associate Professor of Computer Science and Statistics at Stanford University
https://cs.stanford.edu/~pliang/

Dorsa Sadigh
Assistant Professor of Computer Science and Electrical Engineering at Stanford University

Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford CS221 I Algorithms and Distribution I 2023

Stanford Online 2024-03-12 | For more information about Stanford’s online Artificial Intelligence programs, visit: https://learn.stanford.edu/Social-AI-YouTube.html

To follow along with the course, visit the course website:
stanford-cs221.github.io/autumn2023

Speaker: Diana Acosta-Navas
https://ethicsinsociety.stanford.edu/people/diana-acosta-navas

Percy Liang
Associate Professor of Computer Science and Statistics at Stanford University
https://cs.stanford.edu/~pliang/

Dorsa Sadigh
Assistant Professor of Computer Science and Electrical Engineering at Stanford University

Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs221-artificial-intelligence-principles-and-techniques

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 2

Stanford Online 2024-03-12 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 1

Stanford Online 2024-03-11 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee364a/

Stephen Boyd
Professor of Electrical Engineering at Stanford University
https://web.stanford.edu/~boyd/

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee364a-convex-optimization-i

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford Seminar - Rethinking Design for Accessibility

Stanford Online 2024-03-07 | February 23, 2024
Anne Marie Piper, University of California, Irvine

Approximately 61 million Americans, or one in four U.S. adults, have a disability that affects daily life. Despite the prevalence of disability, accessibility is often an afterthought in technology design. Discussions of accessibility often center on checklists of requirements and whether or not a system has particular features. In this talk, I draw on theories from disability studies to argue for a view of accessibility that is collaboratively negotiated, situated, and enacted. Grounded in extensive field work, I will present three cases of design for accessibility that shift how we think about building systems with and for individuals with disabilities. Collectively, these projects reveal the interactive nature of accessibility that is often missing in individualistic system design and call attention to the importance of the social and political dimensions of accessibility alongside the technological.

About the speaker:
Anne Marie Piper is an Associate Professor in the Department of Informatics at the University of California, Irvine. Her research in human-computer interaction focuses on designing and studying new technologies to support communication, social interaction, and learning for people across the lifespan. Her research is funded by NSF, including a CAREER award, the Mellon Foundation, and Microsoft, and has been recognized with numerous Best Paper Awards and Nominations at ACM CHI, CSCW, DIS, and ASSETS. Anne Marie earned her PhD in Cognitive Science from the University of California, San Diego, MA in Education from Stanford University, and BS in Computer Science from Georgia Tech. Prior to joining UC-Irvine, she was a tenured faculty member at Northwestern University

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

The Role of Water and #Energy for Circular Economies with Will Tarpeh

Stanford Online 2024-03-06 | In Professor Tarpeh's new course, he introduces innovative circular economy strategies, emphasizing the critical role of water in designing and implementing sustainable water management practices. This course covers a range of industries and global communities, integrating new digital and sensing technologies to meet evolving needs.

Learn more about our Water, Energy and Circular Economies course (stanford.io/49uW9C8)
Learn more about the Stanford Energy Innovation and Emerging Technologies Program (stanford.io/42OWSw9)

Stanford Seminar - Robot Skill Acquisition: Policy Representation and Data Generation

Stanford Online 2024-03-06 | February 16, 2024
Shuran Song of Stanford University

What do we need to take robot learning to the 'next level?' Is it better algorithms, improved policy representations, or is it advancements in affordable robot hardware? While all of these factors are undoubtedly important, however, what I really wish for is something that underpins all these aspects – the right data. In particular, we need data that is scalable, reusable, and robot-complete. While ‘scale’ often takes center stage in machine learning today; I would argue that in robotics, having data that is also both reusable and complete can be just as important. Focusing on sheer quantity and neglecting these properties make it difficult for robot learning to benefit from the same scaling trend that other machine learning fields have enjoyed. In this talk, we will explore potential solutions to such data challenges, shed light on some of the often-overlooked hidden costs associated with each approach, and more importantly, how to potentially bypass these obstacles.

About the speaker: shurans.github.io

More about the course can be found here: stanfordasl.github.io/robotics_seminar

View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford Seminar - Integrating interactive devices with the users body

Stanford Online 2024-03-01 | February 9, 2024
Pedro Lopes, University of Chicago

The main question that drives my research is: what is the next interface paradigm that supersedes wearable devices? I argue that the new paradigm is one in which interactive devices will integrate with the user s body.

My way of engineering devices that intentionally borrow parts of the user s biology puts forward a new generation of miniaturized devices; allowing us to circumvent traditional physical constraints. For instance, in the case of my devices based on electrical muscle stimulation, they demonstrate how to circumvent the constraints imposed by the size of motors used in traditional haptic devices (e.g., robotic exoskeletons). Taking this further, we can apply this integrated approach to other modalities. For instance, we engineered a device that delivers chemicals to the user to create temperature sensations, without the need to rely on cumbersome thermal actuators, such as air conditioners or heaters. My approach to miniaturizing devices is especially useful to advance mobile interactions, such as in virtual or augmented reality, where users have a desire to remain untethered & free.

Integrating devices with the users body allows to give users new physical abilities. For example, we have engineered a device that allows users to locate odor sources by smelling in stereo as well as a device that physically accelerates the users reaction time using muscle stimulation, which allows users to steer to safety or even catch a falling object that they would normally miss.

While this integration can offer many benefits (e.g., faster reaction time, realistic simulations in VR/AR, or faster skill acquisition), it also requires tackling new challenges, such as the question of agency: do we feel in control when our body is integrated with an interface? Together with our colleagues in neuroscience, we have been measuring how our brain encodes agency to improve the design of this new type of integrated interface. We found that, even in the extreme case of interfaces that electrically control the users muscles, it is possible to improve the sense of agency. More importantly, we found that it is only by preserving the user's sense of agency that these integrated devices provide benefits even after the user takes them out.

About the speaker:
Pedro Lopes is an Associate Professor in Computer Science at the University of Chicago. Pedro focuses on integrating interfaces with the human body exploring the interface paradigm that supersedes wearables. These include: muscle stimulation wearables that allow users to manipulate tools they have never seen before or that accelerate reaction time, or a device that leverages the smell to create an illusion of temperature. Pedro s work has received several academic awards, such as six CHI/UIST Best Papers, the Sloan Fellowship and the NSF CAREER award, and captured the interest of the public (e.g., New York Times, exhibited at Ars Electronica, etc.; more: https://lab.plopes.org).

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford Webinar - Artificial Intelligence Online Programs Info Session 2024

Stanford Online 2024-03-01 | February 2024
Get more information about Stanford's Online AI programs: stanford.io/ai

Artificial Intelligence is transforming nearly every industry and changing the way we live and work. You can be a part of this transformation by mastering the techniques, tools, and fundamental concepts driving the AI revolution.

Stanford Online offers two paths to AI expertise: the AI Graduate Program and the AI Professional Program. Both programs allow you to learn directly from renowned Stanford faculty who are at the forefront of AI research and innovation.

In this online informational session, you will learn more about both programs and see which one will best fit your learning goals.

This session includes:
What you can expect taking a graduate or professional AI course
How to apply and enroll
Q+A

Browse Stanford's online AI programs: https://online.stanford.edu/artificial-intelligence

#artificialintelligence #ai #aicourse #learnai

Stanford Seminar - Embodied Intelligence for Extreme Environments

Stanford Online 2024-02-29 | February 9, 2024
Paul Glick, JPL Robotics

Extreme environments penalize the sensing, actuation, computation, and communication that robotic systems rely upon. Compounding this challenge is the fact that these remote locations are often some of the least mapped areas on and beyond our planet. Structured compliance offers a pathway for robots to adapt to their environment at the mechanical level while preserving the strength to support payload mass & forceful interactions. This theme is explored across projects that include gripping in space, exploration of coral reefs, data acquisition under ice, and a cold-operable robotic arm.

About the speaker: www-robotics.jpl.nasa.gov/who-we-are/people/paul-glick

More about the course can be found here: stanfordasl.github.io/robotics_seminar

View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Kevin Blaine talks about Stanfords Medical Statistics Program

Stanford Online 2024-02-29 | Learn more: https://online.stanford.edu/programs/medical-statistics-program

The fully online, 3-course Medical Statistics Program will give you the tools you need to analyze, interpret, and visualize data. With examples and real-world case studies, you'll learn how to effectively apply foundational statistical knowledge to your career.

Stanford Webinar: A People-First Strategy for Digital Transformation

Stanford Online 2024-02-22 | Learn more on this topic: https://online.stanford.edu/courses/xdgt115-human-centered-design-digital-transformation?utm_source=youtube

As your team is being driven to quickly create new digital solutions, it’s easy to get caught up in the technology and lose sight of the people interacting with this technology. At the core, digital transformation is about problem-solving. And your new innovations, automations, and processes will only be successful if they make the lives of your customers or colleagues easier.

In this webinar, Julie Stanford shows you how to view digital transformation with a human-centered lens and use problem-solving techniques to plan and execute successful digital transformation projects.

#digitaltransformation #humancentereddesign

Stanford Seminar - From Flat to Phantasmal

Stanford Online 2024-02-20 | From Flat to Phantasmal: How Spatial Computing Advancements Enhance Contextual and Creative User Experiences

February 2, 2024
Jasmine Roberts
Microsoft Research

"What tools and systems will streamline the spatial computing creation pipeline?"

Advances in semantic understanding, object recognition, depth detection, and machine learning are needed to create tools that empower developers to prototype in a spatial context instead of current pipelines that require creators to transition between 3D creator tools and 3D game engines.

"How will we personalize experiences to accommodate a wide range of abilities?"

By understanding the context and environment in which people are using applications, we can dynamically modify the scale and location of interactive content relative to a person's needs. A combination of voice controls, wearables, and configurable UI are needed to adapt the application to fit each individual's preferences. Hard-coded components interfere with the ability to scale testing and reduce the amount of actionable feedback from a variety of demographics.

"How will the diverse set of capabilities provided by adjacent technologies advance mixed-reality?"

How can we use physiological, gestural, and biometric data to both determine the effectiveness of VR and to drive immersive experiences? How will the blending of quantitative data, informed with insights from qualitative interpretation, emphasize user-determined creativity?

About the speaker:

Jasmine Roberts is a software engineer and research design prototyper. Contributing to Google's ARCore Depth API, PlayStation VR 2's eye-tracking and interface design, and Unity MARS (Mixed and Augmented Reality Studio), Jasmine has played a pivotal role in shaping cutting-edge mixed-reality technologies. Notably, in her role as part of the Microsoft Research team, she is actively involved in the initial investigations of generative AI within game engines and mixed-reality environments.

Jasmine has been acknowledged by the industry for her dedication to practical application, earning distinctions such as the Oculus Launch Pad Fellowship, Snap's AR Creator Residency Fellowship, Mozilla XR Studio Fellowship, Intel Scholar Award, and Epic Games' Unreal Engine Fellowship. In 2020, she was recognized as Forbes 30 Under 30 for Games.

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford Seminar - Flying Robots: Exploring Hybrid Locomotion and Physical Interaction

Stanford Online 2024-02-13 | January 26, 2024
Dr. Raphael Zufferey of EPFL

Autonomous flying robots have become widespread in recent years, yet their capability to interact with the environment remains limited. Moving in multiple fluids is one of the great challenges of mobile robotics, and carries great potential for application in biological and environmental studies. In particular, hybrid locomotion provides the means to cross large distances and obstacles or even change from one body of water to another thanks to flight. At the same time, they are capable of operating underwater, collecting samples, video and aquatic metrics. However, the challenges of operating in both air and water are complex. In this talk, we will introduce these challenges and cover several research solutions which aim to adress these in different modalities, depending on locomotion and objectives. Bio-inspiration plays a crucial role in these solutions, and the topic of flapping flight in the context of physical interaction will also be presented.

About the speaker: raphzufferey.com

More about the course can be found here: stanfordasl.github.io/robotics_seminar

View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford Seminar - Reducing Misinformation Sharing at Scale Using Digital Accuracy Prompt Ads

Stanford Online 2024-02-12 | January 26, 2024
David Rand of MIT

Interventions to reduce misinformation sharing have been a major focus in recent years. Developing "content-neutral" interventions that do not require specific fact-checks or warnings related to individual false claims is particularly important in developing scalable solutions. Here, we provide the first evaluations of a content-neutral intervention to reduce misinformation sharing that are conducted at scale in the field. Specifically, across two large-scale on-platform randomized control trials, one on Meta's Facebook and the other on Twitter, we find that simple messages reminding people to think about accuracy--delivered to large numbers of users using digital advertisements--reduce misinformation sharing, with effect sizes on par with what is typically observed in digital advertising experiments. These findings suggest that content-neutral interventions which prompt users to consider accuracy have the potential to complement existing content-specific interventions in reducing the spread of misinformation online.

About the speaker:
David Rand is the Erwin H. Schell Professor and Professor of Management Science and Brain and Cognitive Sciences at MIT. Bridging the fields of cognitive science, behavioral economics, and social psychology, David's research combines behavioral experiments and online/field studies with mathematical/computational models to understand human decision-making. His work focuses on illuminating why people believe and share misinformation and "fake news"; understanding political psychology and polarization; and promoting human cooperation. He has published over 200 articles in peer-reviewed journals such Nature, Science, PNAS, the American Economic Review, Psychological Science, CHI, CSCW, Management Science, New England Journal of Medicine, and the American Journal of Political Science, and his work has received widespread media attention. David regularly advises technology companies such as Google, Meta/Facebook, and TikTok in their efforts to combat misinformation, and has provided testimony about misinformation to the US and UK governments. He has also written for popular press outlets including the New York Times, Wired, and New Scientist. He was named to Wired magazine's Smart List 2012 of "50 people who will change the world," chosen as a 2012 Pop!Tech Science Fellow, awarded the 2015 Arthur Greer Memorial Prize for Outstanding Scholarly Research, chosen as fact-checking researcher of the year in 2017 by the Poyner Institute's International Fact-Checking Network, awarded the 2020 FABBS Early Career Impact Award from the Society for Judgment and Decision Making, and selected as a 2021 Best 40-Under-40 Business School Professor by Poets & Quants. Papers he has coauthored have been awarded Best Paper of the Year in Experimental Economics, Social Cognition, and Political Methodology.

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

The Role of Water and Energy for Circular Economies with Will Tarpeh

Stanford Online 2024-02-08 | Learn more about our Water, Energy and Circular Economies course (stanford.io/49uW9C8)
Learn more about the Stanford Energy Innovation and Emerging Technologies Program (stanford.io/42OWSw9)

This course introduces innovative circular economy strategies, emphasizing the critical role of water in designing and implementing sustainable water management practices. It covers a range of industries and global communities, integrating new digital and sensing technologies to meet evolving needs.

The course covers the essentials of water management, including its basic principles, concepts, and stewardship. It examines water’s key role in circular economies, focusing on the sustainable use of elements like nitrogen, carbon, and phosphorus in battery technologies and other products. The course also addresses advanced topics like wastewater refining, electrochemical treatment, and the integration of energy storage with water management.

By the end of the course, you will have honed your ability to assess the tradeoffs between cost, environmental impact, and energy input, empowering you to make informed decisions in wastewater treatment and chemical manufacturing across various degrees of centralization.

#energy #sustainability #water #climatechange

Stanford EE259 I Lenses, image sensors, image signal processing I 2023 I Lecture 20

Stanford Online 2024-02-05 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE259 I Camera principle of operation and architectures, image formation I 2023 I Lec. 19

Stanford Online 2024-02-04 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford Seminar - Single-Life Robot Deployment: Adapting On-the-Fly to Novel Scenarios

Stanford Online 2024-02-03 | January 19, 2024
Annie Chen of Stanford University

A major obstacle to the broad application of robots is their inability to adapt to unexpected circumstances, which limits their uses largely to tightly controlled environments. Even equipped with prior experience and pre-training, robots will inevitably encounter out-of-distribution (OOD) situations at deployment time that may require a large amount of on-the-fly adaptation. In this talk, I will first motivate and introduce the problem setting of single-life deployment, which provides a natural setting to study the challenge of autonomously adapting to unfamiliar situations. I will then present our recent work on this problem, Robust Autonomous Modulation (ROAM). By effectively identifying relevant behaviors on-the-fly, ROAM adapts over 2x as efficiently compared to existing methods when facing a variety of OOD situations during deployment. Crucially, this adaptation process all happens within a single episode at test time, without any human supervision.

About the speaker: anniesch.github.io

More about the course can be found here: stanfordasl.github.io/robotics_seminar

View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford EE259 I Lidar range and direction of arrival estimation I 2023 I Lecture 18

Stanford Online 2024-02-03 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford Seminar - Improving Robotic Dexterity with Optical Tactile Sensor DenseTact

Stanford Online 2024-02-02 | January 19, 2024
Won Kyung Do of Stanford University

Dexterous manipulation, particularly of small everyday objects, remains a complex challenge in the field of robotics. In this talk, I will present two studies addressing these challenges with DenseTact, a soft optical tactile sensor. The first study introduces an innovative approach to inter-finger manipulation using a tactile sensor-equipped gripper. This development not only enhances grasping accuracy in cluttered environments but also facilitates improved manipulation and reorientation of small objects, enabling more precise classification. The second study addresses the challenges of grasping objects of varying sizes on flat surfaces. I will introduce the DenseTact-Mini, an optical tactile sensor featuring a soft, rounded, smooth gel surface, compact design, and a synthetic fingernail. This sensor enables the grasping of multi-scale objects using three distinct strategies for different sizes and masses of objects. This presentation will underscore how these advancements open new avenues in robotics, particularly in enhancing manipulation capabilities in complex scenarios where vision is limited due to occlusions.

More about the speaker: https://arm.stanford.edu/people/wonkyung-do

More about the course can be found here: stanfordasl.github.io/robotics_seminar

View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford EE259 I Photodetection principles (direct vs. coherent), lidar system arch. I 2023 I Lec 17

Stanford Online 2024-02-02 | To follow along, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE259 I Gaussian beams, beam scanning techniques I 2023 I Lecture 16

Stanford Online 2024-02-01 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford Webinar - Human-Robot Interaction

Stanford Online 2024-02-01 | Learn more from Monroe Kennedy and Bill Burnett during their on-campus program happening March 20-22, 2024: https://online.stanford.edu/courses/xdes500-emerging-technologies-designing-strategy-and-forecasting-disruption

How will technology change the way we think, live, and work? Is there a future in which robots will work autonomously beside humans, and what work is being done to get us there?

In this webinar, Stanford University School of Engineering faculty Monroe Kennedy and Bill Burnett explore a future in which robots can think “independently” to enhance human performance and understand human intent. Get a glimpse at the future of collaborative design with previews from the Stanford Assistive Robotics and Manipulation Lab.

#robot #robotics #technology #design

Stanford Seminar - Catalyzing AI Advances with Human-Centered Interactive systems

Stanford Online 2024-01-31 | January 19, 2024
Xiang 'Anthony' Chen of UCLA

Despite the promises of AI, what we often ignore is the gap between a high-performing AI model and how such AI models can serve humanity. In this talk, I discuss how my research closes this gap by developing interactive systems that catalyze advances in AI to achieve three levels of human-centered objectives: aligning with human values, assimilating human intents, and augmenting human abilities.

About the speaker:
Xiang Anthony' Chen is an Assistant Professor in UCLA's Department of Electrical & Computer Engineering. He received a Ph.D. in the School of Computer Science at Carnegie Mellon University. Anthony's area of expertise is Human-Computer Interaction (HCI). His research employs human-centered design methods to build systems that catalyze advances in AI to augment human activities, supported by NSF CAREER Award, ONR YIP Award, Google Research Scholar Award, Intel Rising Star Award, Hellman Fellowship, NSF CRII Award, and Adobe Ph.D. Fellowship. Anthony s work has resulted in 50+ publications with three best paper awards and three honorable mentions in top-tier HCI conferences.

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore

Stanford EE259 I Lidar principle of operation, laser physics I 2023 I Lecture 15

Stanford Online 2024-01-31 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE259 I Waveform orthogonality in MIMO radar, radar noise and interference I 2023 I Lec. 14

Stanford Online 2024-01-30 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Stanford EE259 I MIMO imaging radar, direction of arrival est, target detection I 2023 I Lecture 13

Stanford Online 2024-01-29 | To follow along with the course, visit the course website:
https://web.stanford.edu/class/ee259/index.html

Reza Nasiri Mahalati
Adjunct Professor of Electrical Engineering at Stanford University
https://profiles.stanford.edu/reza-nasiri-mahalati

Learn more about the course and how to enroll: https://online.stanford.edu/courses/ee259-principles-sensing-autonomy

To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu