The Future of Everything

As the world has learned through the recent pandemic, epidemiological studies can be complicated by many unanticipated factors. Lianne Kurina is an expert in the design of epidemiological studies who says that the key to greater confidence is better design.

The gold standard, she says, is the randomized controlled trial—a study that compares groups that are ​essentially identical by every apparent factor but one— the vaccinated vs. the unvaccinated, for instance. In the case of COVID-19 vaccinations, Kurina stresses that investigators did an exemplary job of this.
 

​In situations where we can't use a randomized controlled trial, achieving ​a similar balance and specificity is far harder. Kurina says ​that researcher​s working with observational data, rather than trial data, must always be attuned to the overlooked factors—“confounders” she calls them—that can muddy the data and render a study moot. ​
 

However, Kurina notes, the better one controls the confounders ​in these observational studies via better design ​and data collection, the greater confidence we can have in the end results, as she tells listeners to this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

For decades, the general-purpose central processing unit—the CPU—has been the workhorse of the computer industry. It could handle any task—literally—even if most of those capabilities were unnecessary.

This model was all well and good as chips grew smaller, faster and more efficient by the day, but less so as the pace of progress has slowed, says electrical engineer Priyanka Raina, an expert in chip design. Raina says that, to keep chips on their ever-improving trajectory, chip makers have shifted focus to chips that do specific tasks very well. The graphics processing unit (GPU), which handles the intense mathematics necessary for video and gaming graphics, is a perfect example.

Soon, there’ll be a faster, more efficient chip for every task, but it’ll take industry-wide cooperation to get there, as Raina tells listeners to this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Most people know the seismograph, those ultrasensitive instruments that record every small shift in the Earth’s crust.

But did you know that the very latest method for measuring earthquakes involves fiber optic cables that carry internet data around the world?

Stanford geophysicist Biondo Biondi says that the waves of energy sent forth by an earthquake cause fiber optic cables to stretch and contract ever so slightly. Using precise mathematical algorithms, experts like Biondi can measure earthquake intensity, making every meter of fiber optic cable a potential seismograph and dramatically increasing the data experts can gather in a day. Biondi’s sensor arrays are so sensitive they can detect sinkholes, landslides and even the rumblings of failing urban infrastructure.

These new technologies – and the secrets they might reveal – are only starting to emerge, as Biondi tells listeners in this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Anyone who’s ever made weekend plans based on the weather forecast knows that prediction – about anything – is a tough business. But predictive models are increasingly used to make life-changing decisions everywhere from health and finance to justice and national elections. As the consequences have grown, so has the weight of uncertainty, says today’s guest, mathematician and statistician Emmanuel Candès.
 

Candès knows this paradigm all too well. He is an expert in identifying flaws in today’s highly sophisticated computer models. He says the secret to better prediction rests in building models that don’t try to be right every time, but instead offer a high degree of certainty about things of real consequence.
 

In that regard, the old scientific maxim holds, he says. Correlation does not equal causation. The statistician’s job, therefore, is helping to sort through the noise to find the nuggets of truth in the things that really matter, as Candès tell listeners to this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Electronics are everywhere these days, so much so that often we don't even register that we are using them. The use of electronics will only grow over time as engineers solve societal challenges through increased connectivity, faster computation, new high-tech gadgets, and energy sustainability. Against that backdrop, electrical engineers like Stanford’s Srabanti Chowdhury have been searching for new semiconductors that can expand the application space beyond the ubiquitous silicon. Among the options she’s exploring is an old familiar friend—diamond—and a few new ones, too, like gallium nitride.

The diamonds Chowdhury works with are a far cry from the sparkly gems a jeweler might prize. These diamonds are “doped” with other elements to achieve optimal electrical performance. Meanwhile, gallium nitride has shown promise in LEDs and lasers, as well as in cutting-edge radar systems—among other applications.

While these new semiconductors have raised hopes of scaling new heights where even silicon cannot reach, much work remains if they are ever to move from lab bench to laptops and myriad other electronic devices. The payoff, however, will be smaller, faster, more powerful, more energy efficient, and more versatile electronics, as Chowdhury tells listeners to this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It now seems more certain than ever that the world will make the all-important transition to electric vehicles, but that shift raises important questions about global preparedness.

The world is going to need a lot of batteries to make it happen and engineers are rightly concerned about everything from the availability of raw materials to how many miles can I drive before I run out of juice?

Simona Onori is an electrical engineer by training and a professor of energy resources engineering as well as an expert in creating computer models of what that electric future will look like. For instance, she is developing mathematical battery management systems that assess the internal chemistry of a battery to predict how much life is left in it, how safe it is and, yes, how long until that next charge is needed.

Onori likens her analyses to “battery biopsies” that can help engineers and everyday drivers get more life out of their batteries. Don’t fret, our electric future is in good hands, Onori reassures listeners in this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Engineer Irene Lo studies markets, but not traditional marketplaces based in cash.

Instead, she studies markets for goods/resources that place a high value on social goods like diversity, fairness and equity.

Thus, Lo came to help San Francisco create an algorithm to assign kids more fairly to public schools across geographic, social, racial and economic boundaries. As it turns out, math is just the first step. The most challenging part was getting families to trust in the system, begetting a multi-year community engagement effort.

Lo is now turning her attention to other markets with social impact, like her work on the system that places medical students in residency programs across the country or one trying to make the palm oil supply chain fairer for farmers.

Listen in as Irene Lo explains the changing face of markets to host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Oft-heralded 3-dimensional printers can build objects ranging from simple spoons to advanced running shoes.

While those objects are usually made very slowly, the latest printing technologies portend a new era of 3D printing in real-time for use in health care.
 

The possibilities are endless, says Joseph DeSimone, who is an expert in translational medicine – the field of transferring promising technological breakthroughs into real-world products. He says printers he developed have led to the first FDA-approved 3D printed dentures, ultra-thin microneedles that make it easier and more effective to deliver vaccines, and even implantable chemotherapy devices that kill tumors while reducing side effects for patients.
 

From dentistry to oncology, the promise of 3D printed medical devices is only just emerging, as DeSimone explains in this episode of Stanford Engineering’s The Future of Everything podcast with host Russ Altman. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Tina Hernandez-Boussard is an expert in biomedical informatics who says a new era of understanding the real outcomes of our health care systems is on the horizon thanks to big data, artificial intelligence, and the growing availability of electronic health data. She says that the combination of these tools and data holds the promise of providing never-before-possible insights into whether health procedures truly improve patient quality of life and for which populations.

With these tools, she says, her field can peer into the “real-world” details hidden in the medical records, even going so far as to use natural language processing to analyze the freeform notes and emails to and from the provider. The examples are virtually limitless: matching health records against data from wearable devices to know when a knee patient is not getting enough physical exercise, cross-referencing prescriptions to learn whether a patient might be susceptible to adverse drug combinations, or even revealing undisclosed medical events such as past mild heart attacks.

It’s all there in the data, waiting for us to explore, as Tina Hernandez-Boussard tells bioengineer and host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nate Persily is a professor at Stanford Law School and an expert in election law.

He sees the most recent presidential election as a fundamental change in the way Americans vote. For the first time ever, the majority of voters cast their ballot by mail, rather than at a polling place. It “was an earthquake,” Persily says, speaking metaphorically about the 2020 election’s profound implications for future elections.

But not all agree it was a success. Republicans and Democrats are further apart than ever in their beliefs as to whether the recent presidential election was free and fair. Addressing polarization in beliefs regarding the fairness of the election will be very difficult. Until leaders come together in a bipartisan fashion to affirm the legitimacy of an election winner, reform will not be able to do much to address this underlying problem.

Failing that, we need to bolster the institutional position of all nonpartisan election administrators who are placing the public interest over party, as Persily tells host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads / Bluesky / Mastodon

Connect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.