#38 – Newton Nguyen

November 9th, 2026

#38 – Newton Nguyen

Editor’s Note: Full episode video is available here.

{Music}

Angus Stocking – Host (00:04.11)
This is Everything is Somewhere. I’m Angus Stocking. My guest today is Newton Nguyen, a scientist at Stanford University. I was introduced to Newton by my previous guest, Brandon Biggs, who’s a researcher and entrepreneur striving to make graphically intense fields more accessible to the visually impaired. And so my listeners know, Newton himself is blind and I think he’ll tell us more about that. And I don’t want to go into greater detail. I’m gonna let Newton introduce himself. So with that, Newton, welcome to Everything Is Somewhere.

Newton Nguyen (00:57.56)
Thank you. I’m really excited to chat with you and get to tell my story.

Angus Stocking – Host (01:04.02)
And and I’m eager to hear it. could we start with maybe a a more involved your personal story is quite interesting and I want to hear more about it from you. could you maybe tell us are you blind from birth? what was your education like? How did you get interested in the work you’re doing now? Just a superhero introduction, if you would, origin story.

Newton Nguyen (01:31.576)
All right. Well, all heroes have an origin story, I’m guessing. But yeah, so I am currently a climate scientist at Stanford University in the departments of earth systems and physics. I specialize in how do you how do you make measurements under uncertainty and how do you make decisions under uncertainty?

And to do this, it requires lots of like maps, lots of like data analysis and instrumentation. so I’ve been always trying to figure out how to you know make make geospatial and just just graphical data accessible to me. this challenge started when I was around twelve years old is actually when I lost my vision. it was really difficult because at the time actually I failed my math classes. And turns out that like if you can’t see, it’s really hard to pass your math classes.

Angus Stocking – Host (02:47.842)
Let me break in there that it seems like a pretty big distinction. Brandon was born blind and to have it happen upon you at twelve…

What are the advantages and disadvantages, if I could put it that way? Is it harder having the sudden change or is it easier because you’ve got at least the at least you know what you’re missing? And I don’t know if I’m making sense of it, and maybe that’s an indelicate question, but if you could weigh in on that.

Newton Nguyen (03:28.448)
Yeah, I think in some ways it’s an advantage because you know, it takes a while for your visual cortex to actually form from a biological perspective, and so you have a lot of like like a large proportion of the human like the human brain is actually designed for con for visual processing. So I had the advantage where like I was able to have that part of my brain develop really well. So I could like visualize things.

Actually that’s the way I do math now is that or do math or do physics now is actually I actually picture it in my head. and like visually, like what would I what would those equations look like? How do I manipulate them in my head? And that’s I do a lot of that. so that’s probably an advantage on my end. I think like the adaptation though, like the tools and stuff I had to learn on the fly.

And that’s that was a a drawback for me. So that’s that’s the con there, but yeah

Angus Stocking – Host (04:32.514)
Thank you for taking the time to answer that. It’s been a curiosity of mine for some time and your interest or emphasis on the visualization. Many great scientists of all stripes have had a capacity for intense visualization, you know, even Nicola Tesla, by reputation, was able to visualize machines and build them in his head and that would be a tremendous advantage. So good on you and thank you for taking the time and please continue.

Newton Nguyen (05:12.524)
Yeah. so after I lost my vision, I eventually learned how to get the help that I needed to describe things to me. So what these figures look like, what these equations look like, and went into you know, went to the physics world and went into like the climate science world when I went to university.

And then once I arrived at university, I got really interested in working on climate change problems. how do we s how do we monitor climate change? How do we like quantify greenhouse gas emissions? These kinds of issues. So after I graduated college, I worked for the US Department of Energy at the Lawrence Berkeley National Lab. there I was working on a couple of NASA projects with NASA to develop their satellite observation network for like greenhouse gas and climate change monitoring.

And that’s kind of where I did my PhD as well, at Caltech, and there I got more into like specifically like greenhouse gas quantification and mapping as well. and that brought me to Stanford and working at Puloli, the former company I was previously at. So really, I’m just trying to make a big dent in understanding our carbon emissions and how to monitor climate change because in the end how do you how do you fix what you can’t detect? How do you fix what you cannot monitor?

Angus Stocking – Host (06:52.896)
Interesting. So it sounds like you had your academic interests or your scientific interests formed pretty early and you were interested in climate change. Was there some temptation to divert to a field that didn’t rely so much on maps and graphic information and something that might have been more accommodating of blindness or was there a like a determination to do what you wanted to do, whether or not it was easy?

Newton Nguyen (07:29.292)
Yeah, there was a lot of like encouragement for me to switch paths and do something that’s more verbal, and less visual for sure. I think especially like when I first started university, that was really difficult. and it was tempting, right? Like I it would have been in a little easier for me to do that, but in the end I decided to stick with it, just because I like a challenge, but also because I felt like it was the right thing to do.

I did not want to let my like disability dictate what I can or cannot do. and if I, you know, if I wanted to do it, you know, it would require like way more work, way more effort, you know, way more all-nighters to studying and like trying to make things work but I think that was what I chose to do and made that sacrifice and it was worth it.

Angus Stocking – Host (08:33.518)
And as you made that choice and you were first engaging with professors and then employers, what kind of reception did you make? Was it was how much help did you get adapting the profession to your circumstances?

Newton Nguyen (08:53.358)
Honestly, like it was it was definitely like very much like I’m on my own. Like in many in many places that I’ve been at, no one knew I was like the first blind person at Caltech. And that’s a really, you know, prestigious place that’s been around for a 140 years. So being in that kind of place, I had to like kinda educate people on like what my needs were.

Actually even for myself, like learn what my own needs were. ’cause it was like kind of impossible to anticipate what kind of problems would be thrown at me, both like personally and professionally, with my disability. So dealing with that and then just figuring it out and just I think in the end just having good, decent people skills to like ask for help was like really helpful for me. So I did get a lot of help as well.

Angus Stocking – Host (10:00.878)
Sure. so yeah, I’m guessing that the academic life one thing is you’re seeking publication, trying to do new research and theorizing and so forth. could you give us a an early example of a topic that you pursued and publication, a paper or something that you you know what what have you added to this the field, I guess.

What discoveries were you pursuing and and how did you do it? And how did you even maybe s give us an idea of some of the things you learned how to do in this very interesting field that needs smart people from whatever walk of life? how did it work for you?

Newton Nguyen (10:50.658)
Yeah, I guess I guess I’ll give like two different kind of dis two different two different discoveries that I guess I’m pretty like two of my early discoveries. great. Yeah. So the first one is so I was on a team that essentially showed how strong methane was as a greenhouse gas.

Angus Stocking – Host (11:02.808)
Yeah, thank you.

Newton Nguyen (11:20.606)
So for context here, methane is a second most important greenhouse gas. Well, excuse me, human emitted greenhouse gas. The second most important human emitted greenhouse gas. is responsible for about a third of climate change. however, it has a ten year lifetime. so if you stop methane emissions today, then in ten years, like that kind of like warming will decrease. So you’ll see the effects in pretty rapid succession.

My contribution on this team, we essentially like quantified how much does methane actually like warm the planet. And to do this, we used observations from the space missions from the Saturn from Saturn and Jupiter, the Jovian planets, the reason why we did this was because those planets are full of methane. So we were able to get that signal from those the Cassini mission from these other like Jovian missions from NASA, measure like the how much like heat methane traps on those planets and transfer that to Earth in the end.

Angus Stocking – Host (12:40.75)
And what mechanics for you of that? You were getting the data, finding a way to look at maps and then turning to you know, research or visualization. What was that like?

Newton Nguyen (12:56.652)
Yeah. So there’s two domains that’s like kinda like graphical. The first domain is is spectral, so infrared, like different bands of the infrared. and you could see one if you if I plot like absorption of radiation, like heat, as a function of infrared light, then you see like little spikes. And these little spikes are the fingerprints of methane and like you add them all up together and that gives you the full like amount of warming that methane provides on a planet. So like the patterns of those spikes actually really matter for how we how like much methane warms up the planet.

So that’s like very spatial. You need to actually like see that. You need to actually like understand what the pattern is. The second thing is like Earth is not equally bright everywhere. So if you have a lot of clouds in a certain place, then you have a lot of, you know, there’s more radiation being reflected. You have if it’s like, you know, dark surface ocean, then you have more radiation being absorbed. And so that actually affects the way that greenhouse gases absorb radiation as well. And so mapping out both in the spectral domain and in the spatial domain, you could actually get a full budget of how much methane is warming our planet.

Angus Stocking – Host (14:18.731)
Okay. Were you using the tactile maps that Brandon talked to me about for….

Newton Nguyen (14:26.974)
So this was 10 years ago. So not yet. so at the time I was actually using like just listen literally just listening to the numbers. So it would be like, you know, 16 point, no, it’d be like 160 1650 nanometers, and you get like a number like 0.03. And then like kind of like go through like 1655 nanometers, point one. and like just like visualizing that in my head as I like listen to these to these numbers.

Angus Stocking – Host (15:00.622)
You’re making me realize as you speak, something as simple as a bar graph or a pie chart or something like that to me is you know, relatively simple and I can understand that. that would be a bit of a chore for you, the you know, the time required to bring that information in would be difficult and my admiration for you is growing. so it it so I do I derailed you. you were working on you were comparing Jovian planet Jovian to Earth data I think and what did you learn and what did that lead to?

Newton Nguyen (15:48.126)
So we learned that, you know, the amount of warming that methane causes was underestimated. so we closed that budget. we had the most, you know, I would say interesting and sorry, comprehensive and I would say exotic observations of methane possible. So we ended up yeah, closing up closing the budget of methane and like that was the that’s essentially the final number that everybody uses now for like methane’s impact on climate change.

And it’s used a lot now, these numbers are used a lot now for the United Nations, and also carbon credits. So, you know, having this kind of metric of like, you know, what is the climate change impact of methane? And if you stop meeting it, how much does it how much does it actually like you know, save our planet? that’s a that’s a way to that’s definitely a way to like provide a contribution for people. In a very finite way. Thanks. That’s one paper…

Angus Stocking – Host (16:58.242)
Right. And then you said you said two, so I’m ready.

Newton Nguyen (17:01.448)
Yeah. This one’s a little more relevant actually for this year. And the reason why is because it’s especially related to El Niño. so for the your listeners, I’m Stanford is in California, is where which is where I live. Well typically I live in San Francisco, but point the point is the west coast, we experience a lot of extra rain during El Niño. However on the other side of the Pacific Ocean, the Western Pacific, sorry, the eastern Pacific, we see l a drought, huge amount of drought. So like basically like the water shifts from the like Indonesia to California. So what this does in the other side of the Pacific, in Indonesia, is it causes conditions for wildfires.

Lots and lots of wildfires. And you can kind of see today, even if she look it up today, there’s a record breaking wildfires in Indonesia. So one of the contributions I made back when I was 2017, 2018, I think, my first year of grad school, was showing that El Niño, these wildfires, you know, during El Niño, they actually contribute to methane emissions in two different ways.

The first one is because wildfires also emit methane. They emit a lot of methane as well. so it’s like the direct, I call it the direct effect. And then there’s something called the indirect effect, which is all that smoke, all that carbon monoxide that gets sent sent into the atmosphere from these wildfires, they actually make methane last longer in the atmosphere. So like your lifetime goes from 10 years to like 13 years to 14 years.

And so the stronger the wildfire, the longer methane lasts in the atmosphere. Because like basically you have a certain amount of we call hydroxyls, these molecules in the atmosphere that eat up methane. But they react, they also they also eat up with they also eat up carbon monoxide, they eat up you know, like black carbon and stuff in the atmosphere. So like there’s only a certain supply of those molecules in the atmosphere and you emit and you have a bunch of stuff.

Newton Nguyen (19:24.854)
Much of other stuff coming in, essentially much of other pollutants coming in that’s not methane, then then that takes up all the all this hydroxyl and then methane lasts longer. So it actually increases methane’s like effective climate change potential.

Angus Stocking – Host (19:41.58)
That’s super interesting and something I would not have guessed in a thousand years that wildfire sounds like you’re saying particulates or you know, things that are physical stuff that’s left in the air can permit or enable meth methane to last longer in the atmosphere and thus have more effect on climate. Is that a way to sum it up?

Newton Nguyen (20:07.488)
Exactly correct. Yeah.

Angus Stocking – Host (20:10.008)
Right. So interesting stuff and I and I’m also getting a you know strong sense of what you can what you are contributing to the field and how you are doing it. what what have you learned in terms of this specific h how is your ability to do high level work in this field? you know, ten years ago to today… What have you added to your workflow that has helped you to do this better and maybe faster and maybe at a even higher level? what’s how’s the technology adapting or how are you adapting to do better work?

Newton Nguyen (21:01.678)
Well the question is whether we’re adapted to technology or the da is the technology adapting to us, right? In this era nowadays. but yeah, so I guess I’ll tell you what happened ten years ago, like what what my workload not workload, but what my setup was ten years ago. And I’ll tell you what it is now. So ten years ago, I have this, you know, my computer, my MacBook, it reads stuff out to me. It reads out what’s on the screen.

And this is actually a a lot of this is like my main my main tool. I listen to code, I listen to equations, and then I, you know, just type on a computer like a normal person. but yeah, it’s it’s kind of like mentally exhausting after a while though, because imagining having to listen to like thousand like thousands of lines of code.

And having to like sort of memorize it on the spot and look at the structure. in addition to that, so that’s like the way I would use to, you know, generate or analyze the data. But then how do I communicate that and how do I how do I understand it? That goes into like actually like coding out the figures, coding out the the actual like graphs. so a lot of like what I do also is like data visualization, ironically. so yeah, I would definitely like just code those data.

Me sorry, code the code up write the scripts to actually generate the the figures for communication. and so that was that was interesting. It was very difficult, I guess.

Angus Stocking – Host (22:43.81)
And that was ten years ago.

Newton Nguyen (22:45.4)
That was ten years ago. Okay. But nowadays, there’s a couple of different advances that’s actually really helped. Number one is before I wasn’t able to actually understand like figures and the graphs that people sent me. So now I just like could upload it to AI and have it describe it to me. Or like or like separate it s like, you know, basically read out the data into like a Excel file or something and listen to the numbers that way. another way but now like I’ve been working with Brandon Biggs on this audio data product. essentially it’s a way to map out and listen to geospatial data and interact with it. That’s the most important part. To interact with the data.

So like if there’s a specific place that I’m looking at, for example, a satellite sees, I don’t know, a methane leak or some sort of like ecosystem anomaly, I could like zoom in on that now as a blind person. and then like like okay, okay, what does this correlate with? What was this correspond to? look, like there’s like a flood there. I could like change the variable up and say like, okay, instead of methane, let’s take a look at water level, water table, soil moisture,. these kinds of other variables that correlate to methane emissions. so that’s also been an advance. So the combination of both AI and like this kind of like audio tool to actually like fully interact with the data has enabled me to like be more comfortable accessing geospatial data.

Angus Stocking – Host (24:36.584)
You mentioned AI and just to drill down on that a bit, so you you load up you know, a chart or a graphic, something like is it as simple as giving a prompt something like, I’m blind, give me a visual take on this and suggest to me where I can, you know, drill down with verbal information. Is it something like that, or do you have a you know custom app you know AI applications that are helping you to do this?

Newton Nguyen (25:11.872)
Yeah, so I guess combination of the two. So I like developed an AI skill for myself. So that like when I upload to Chat GPT or Cloud, it’ll do that for me. It’ll describe it the way I like to the way I like it to be described. you know, they say like every picture is worth a thousand words, right? So let’s make sure that when the when the words are chosen, they’re the right they’re like accurate, they’re the right words to describe the picture. So for example, whenever you see something in the New York Times or like in like a paper, like a journal, scientific journal, every single figure has an argument.

It’s making an argument. Like just like how every map is also making an argument. and so the way I kind of have it’s like the skill designed is to like try to figure out like what is the argument that this figure is trying to make and how is it trying to support it with the data being shown. So at least that’s it’s very it’s a very reductive way to look at like graphics and maps and stuff. But I think it’s the most like utilitarian, like the most efficient way to do this. So then the thousand words that are chosen to describe the figure is the most useful thousand words for me.

Angus Stocking – Host (26:34.456)
Have you found you know a very general question is would be say I’m reading the New York Times and there’s a fairly involved article that is using maps and graphs and charts and I know from my work that graphics can often be a kind of elaborate way to tell lies, you know, can you present framed statistics that make an argument that isn’t really in the data. Are do you feel like you’re better at detecting let’s call it malicious framing of data because you’re looking at charts and graphs and maybe maps in a different way.

Newton Nguyen (27:28.13)
Definitely. I I think so. I think one way to think about it is also like how has a data been transformed to make it look like it’s trying to show something? If that makes sense. So for example, there’s like some some people kind of show like you know there hasn’t been climate change since nineteen ninety seven. and what they do is they like they like the the left part

Like if you have a temperature versus time, they start the time at 1997 and they s they show up being flat or something like that. Or like depends on where you start it, right? Where you start the where you start the initial data point. you could draw a line, like you draw a horizontal line to know to any two data to any like two data points, right? You could just you kinda manipulate the data in that way. so it’s like what is the trend?

How robust is that trend? And you know, where what does that trend, what time period is that trend describing? And so like when it comes to like describing these graphics, I’m always like very skeptical and making sure that I I know the transformations being applied on the data and what is being shown and especially what is not being shown.

Angus Stocking – Host (28:49.496)
Do you ever find yourself taking minority positions among your fellow climate scientists because you have a different take or different viewpoint and parenthetically I recognize the irony of saying viewpoint and looking so forth. But do you ever find yourself at odds with other researchers because of the way you’re taking in data?

Newton Nguyen (29:24.626)
I think so. Some I think I’ve seen had some I’ve encountered some of that a little bit. meaning that like like we could interpret interpret a a trend differently. or like on a on a heat map, like interpret the color scales differently. Because since I’m looking at numbers and people are looking at colors, then that can actually affect the way that people interpret the data.

Right. If there’s like a hot sp if like a map has like a hot spot at a certain place. but then and it’s like, you know, bright red against a blue background, yeah, that sticks out. But then when I look at the numbers, it’s like it’s only like a five percent enhancement. Okay, then that’s no big deal. Right. So again, it’s about scale. Like sure. Like instead of in the previous example where I mentioned time, this is in like, you know, intensity.

Angus Stocking – Host (30:23.628)
Very good. Thank you. That’s a perceptive answer and broadens my understanding quite a bit. So thank you for that. Newton, looking forward, when I was interviewing Brandon, I made the comment that it f feels like in terms of what’s coming down the pike and increasing accessibility for the visually impaired into these fields, his field and yours; we’re at the beginning of what it seems to me that you’re at the beginning of a hockey stick curve and things might be changing pretty quickly. What do you see happening over the next five to ten years that would make life increase your powers as a scientist in this field?

Newton Nguyen (31:15.158)
I think we’re past the point of like understanding what is being graphed or what is being kinda argued in a figure now. So we’re done with that. That problem’s a solved problem. Now it’s interacting and extrapolating. So like for example, when we you know, when when I could see that like, you know, there’s like a there’s like a you know a spot on this on this you know heat map that shows like high intensity. I can now like you know prompt, you know, the AI to be like, okay, let’s zoom in here. Now let’s overlay a different variable on top of it. Right. so being able to like interact with that data now and enables me excuse me, being able being able to interact with the data.

And being able to like have back and forth conversations about the data on my own has been actually pretty revolutionary in the way I interact. I understand the data. so that’s one thing. I think another thing is just customized accessibility. And by that I mean like right now it’s sort of a everything, all accessible technology is essentially a slate, just like a very I don’t know, fixed, configured, like, hey, take it or leave it. and that’s the way you interact with it. It’s prescribed for you. But I think that in with the advent of like AI and like audio and these other tools, we are now more able to customize the way that we want to interact with with…

Newton Nguyen (33:13.944)
…like non-accessible things with like visual like visual things or other types of data. And so that so those two things together will I think will really change a lot of you know desire for people like me to get into these spatial fields.

Angus Stocking – Host (33:35.734)
Newton has a kind of a final question.

What about your life outside of work? you seem like a person who’s probably has a a great deal of hobbies, personal interests, family life maybe I I don’t know. what’s a day in the life outside of work like for you? and is that are you making gains there in terms of the way technology is helping you to pursue personal interests?

Newton Nguyen (34:07.192)
There’s like a good question. I I I think there’s a distinction between like living like having an accessible life and having a like a fulfilling life, right? Like a fulfilling life has to be accessible, but an accessible life is not necessarily fulfilling. So like for me, like outside of outside of work, outside of like what I do on a daily basis, or excuse me, outside of my professional life, I try my best to actually interact with people as much as I can and not try to rely on technology as much.

So for example, I’m actually a pretty intense marathon runner and triathlete. I’ve run like fifteen marathons, and to do that, I actually run with people. Sure, there’s like been a lot of like technology for like I don’t know using AI glasses or something to help blind people run, enable them to run and stuff. But I just really like running with people and being guided and having that kind of literally a tether that connects me to the another person and can feel where they are. And that actually like is something that I I don’t intend on replacing with accessible technology.

But in general, like I really try to interact with people as much as possible, both in my personal and professional life. just like do fr like I could like, you know, prompts the AI like to like this right describe figures or read things to me. But in the end, I’m trying to communicate to another person. Like when I generate these figures, when I you know, do science, I try to communicate it to people. So having that kind of interaction and seeing what their perspectives are, if especially there’s perspective are different than me and the AI on the data, I want to hear it and I want to interact with that. so yeah, making sure that people stay centered there.

Angus Stocking – Host (36:13.818)
And thank you for entertaining that very personal question. That was a wonderful answer. And this has been a tremendous conversation. I learned a lot and appreciated getting to know you, your and your work. I guess we’re drawing to a close. Is do you have any closing statements or anything the audience might want to know about you or where they can follow up on your work or some of the things we’ve been talking about.

Newton Nguyen (36:46.458)
Yeah, I think in general, like just be on the lookout for more more blind people in in the geospatial like mapping world. and I think that like having literally a different viewpoint, different perspective is gonna be pretty valuable for us to understand.

Like what’s going on in the world around us.

Angus Stocking – Host (37:19.138)
Been noticing as we talk it’s very hard to avoid language like viewpoint or looks like or images and there’s really not a sense neutral language.

Newton Nguyen (37:34.094)
Yeah. It’s you know, seeing is knowing, right? As the Greeks would s ancient Greeks would say. So yeah.

Angus Stocking – Host (37:41.71)
Well, thank you very much and have a great afternoon and goodbye from now.

Newton Nguyen (37:49.263)
Thank you.