Season Schedule

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September 2019

Gone With the Wind: How predictable is weather forecasting?

Sharon Sullivan, Meteorologist, NOAA


Presenter's Essay and Bio

Presenter's Essay

About the Presenter

Sharon Sullivan

The air felt thick and warm. A funnel cloud came down from the sky as I watched from the swing set I was sitting on. With a roaring sound, the funnel cloud disappeared almost as fast as it had formed. While most of my classmates were frightened, I was fascinated by what I had seen. I am a meteorologist with the U.S. National Weather Service in Albuquerque, who’s interest in meteorology was sparked at the young age of 8. Since then, my interest in meteorology has only grown. As an Albuquerque native, I graduated with a Bachelor’s in Applied Mathematics from the University of New Mexico and volunteered at the NWS Albuquerque office during my college years. I went on to complete a Master’s in Atmospheric Science at the University of Wyoming. I’ve been on academic probation and had been suspended from my program more times than I care to admit. I went from barely passing and having to retake several classes over to getting an A in my hardest class. In the same way that my interest in math and sciences was encouraged by my parents and mentors at a young age, I think it is important for students to pursue their passions and know of the opportunities they have within the STEM field, especially among other young female Hispanic minorities. I am particularly interested in the education and outreach aspect of the National Weather Service, involving helping the public understand what meteorology is and instructing people on how to be safe during a severe weather event. Working as a National Weather Service meteorologist combines several of my interests: meteorology, mathematics, education, and helping others. One thing I enjoy about meteorology? The constantly changing environment. No work day is the same and it’s brought me new friends, different opportunities, and travel to several different states. My first entry-level position brought me to the great state of Alaska! In my spare time, I enjoy ballet, fishing, hunting, traveling, and trying new foods. As Confucius once said, “Choose a job you love, and you will never have to work a day in your life”.

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September 2019

The Northern New Mexico Climate Change Corps: Natural Resource Management

Brooke Zanetell

University of New Mexico- Taos


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September 2019

The Search for a Sterile Neutrino: Could the discovery of this ghostly particle solve some of the mysteries of the universe?

William Louis

Los Alamos National Laboratory


Presenter's Essay and Bio

Presenter's Essay

Two of the biggest questions in physics today concern the properties of dark matter and dark energy, which make up approximately 95% of the mass-energy of the universe. In comparison, normal matter made of protons and neutrons make up the remaining 5%. It is thought that dark matter, representing about 25% of the universe’s mass-energy consists of new particles that interact very weakly, if at all, with Standard Model particles.

One possible dark matter particle is the sterile neutrino, which would only interact by gravity and possibly by new interactions with the Dark Sector. Evidence for sterile neutrinos comes from the LSND and MiniBooNE neutrino experiments and from the gallium and reactor neutrino anomalies. Therefore, sterile neutrinos, if they exist, may provide the portal between the Standard Model and the Dark Sector. These sterile neutrinos can be detected indirectly through their oscillations with Standard Model neutrinos and, thereby, can provide a window into the Dark Sector.

In order to test this hypothesis, there are experiments under construction or taking data worldwide that will either confirm or rule out over the next 5-10 years the existence of sterile neutrinos.

About the Presenter

William Louis

I grew up in Atlanta, Georgia and attended university at Georgia Tech as a physics major. During my junior year, I took a particle physics course, which was utterly fascinating. In 1971 the weak interaction was beginning to be understood and the Standard Model of particle physics was beginning to be put together. This interest in particle physics led me to go to graduate school at the University of Michigan and study neutrinos, which only interact by gravity and the weak interaction.

My PhD thesis tested the newly formulated Standard Model with neutrino interactions, where our measurements agreed with the Standard Model, but with very large uncertainties. Following graduate school, I was a postdoctoral research at the Rutherford Laboratory in England, where I worked on charged hyperon experiments at CERN, the European Laboratory for particle physics. Following Rutherford Laboratory, I was an assistant professor at Princeton, working on a dimuon experiment at Fermilab and a rare kaon decay experiment at Brookhaven Laboratory.

Finally, in 1987 I moved to LANL, where I have been extremely fortunate to work on the LSND neutrino experiment at LANL, followed by the MiniBooNE neutrino experiment at Fermilab. LSND took data in the 1990s and obtained the first evidence for electron-neutrino appearance, while MiniBooNE, taking data from 2002-2019, has confirmed this excess of electron-like events. These signals from LSND and MiniBooNE imply the possible existence of sterile neutrinos, which would be new fundamental particles of the universe that only interact by gravity (and perhaps by new interactions associated with the dark sector).

Needless to say, I find particle physics to be a most exciting adventure.

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October 2019

Forecasting Infectious Diseases Using Internet Data: Can we forecast diseases like the weather?

Sara Del Valle. Lauren Castro

Los Alamos National Laboratory


Presenter's Essay and Bio

Presenter's Essay

I know what you did last summer! Did you know that the Library of Congress archives all publicly available Twitter feeds? These tweets can be used to research a variety of topics, including tracking the movement of birds, understanding people’s eating habits, and analyzing information spread.

In early 2009, a new strain of H1N1 influenza (aka swine flu) emerged and the World Health Organization declared it the first pandemic of the 21st century. The reaction to the pandemic on Twitter was overwhelming; there were approximately 10,000 tweets per hour about “swine flu” coming from all over the world. As word spread, people started canceling trips, purchasing facemasks and hand sanitizers, and seeking medical help. In contrast, during the pandemic in 1918, the speed of communication was outpaced by the spread of the disease. As many as 100 million people died!

Technology in the 21st century has transformed the way we communicate; information can now spread all over the world in a matter of minutes. The Internet, smart phones, and social media have empowered the human race by giving everyone a voice. Social media has enabled people to share information in near real time, providing early warnings for new infectious diseases and situational awareness. These data can help scientists model the spread of infectious diseases and identify behavioral patterns in response to a disaster.

The best ways to keep people from contracting infectious diseases are 1) rapid identification, 2) timely treatment, and 3) containment. However, in our very interconnect world, if a disease is not rapidly identified, it can spread around the world in days. Once a disease begins to transmit from person to person, scientists need to estimate its transmissibility, death rate, and the impact of mitigation strategies. For this purpose, scientists use models, which include the demographics of the population, activities people undertake, locations where people gather, positive or negative perception towards the disease, and behavior people may adopt.

This is where social media comes into play; when people “check in” (location), tweet about what they’re doing (activities or behavior), tag who they’re hanging out with (contacts), and share their feelings (perception); scientists can use all this information as data to develop models to help contain the spread of a diseases.

So the next time you tweet about staying home from school because you’re sick, think about the scientists who are using your tweet to learn about how human behavior is related to spread of infectious diseases—and ultimately how to use this information to save lives!

About the Presenter

Sara Del Valle

DelValle

I don’t recall liking mathematics when I was in elementary school, but that changed when I was first introduced to algebra in junior high. I had a teacher who was considered the hardest teacher in the entire school. Eight out of ten students would fail his classes, so when I got an A in his algebra class, I knew I had found my true passion. In high school, I remember having a rush of adrenaline when I took math and physics exams. My cheeks would turn red and it was like a concert in my brain, with all the numbers and formulas coming together in unison.

I was born in Mexico, where my parents were missionaries, but we moved to New Jersey when I was 16. Although no one in my family was a scientist, my dad is good with math and finances—perhaps that's where I inherited the math gene. After I graduated from high school, I attended the New Jersey Institute of Technology (NJIT), where I majored in applied mathematics. I was doing so well that my academic advisor suggested that I enroll in the B.S./M.S. program. I always thought I would become a math professor because that’s what mathematicians do, right? WRONG.

Looking around on the Web for a summer program during my senior year at NJIT, I came across the Mathematical and Theoretical Biology Institute (MTBI)–Research Experience for Undergraduates (REU) program. I applied and was accepted. MTBI was held at Cornell University, so I moved to Ithaca, New York, in the summer of 2000. This REU completely opened my eyes about what one could do with mathematics and introduced me to mathematical epidemiology. I was intrigued by how models could provide decision support for planning and mitigating the spread of infectious diseases. I returned to MTBI for a second summer in 2001, and it was only after this summer that I knew I wanted to earn a Ph.D. in mathematics. One of the presenters during the summer was Herbert W. Hethcote, a pioneer in mathematical epidemiology, including mathematical modeling for childhood vaccination strategies, and professor at the University of Iowa.

I enrolled in the graduate program at the University of Iowa, with a fellowship from the Graduate Assistance in Areas of National Need program of the U.S. Department of Education. Although by this time I had lived in five states and two countries, I wasn’t prepared for the culture shock I experienced when I got to Iowa. (New Jersey was concrete and industry—Iowa was cornfields and cows!). In 2003, the director of the MTBI program received a prestigious appointment at LANL and invited me to join his research team. Although the original plan was to spend only one year at Los Alamos, the landscape, my work, and the people around me enticed me to stay.

After completing my Ph.D. in 2005, I was offered a postdoctoral position, and soon after, I was converted into a permanent staff member. Currently, I work on mathematical and computational models for infectious diseases. I am also interested in understanding and modeling human behavior in response to epidemics and other disasters. Most recently, I’ve been using Twitter feeds to study emergent human behavior during recent disasters, such as the 2009 H1N1 influenza pandemic and the 2011 tsunami in Japan. My goal is to use social media to model and forecast human behavior to better predict the spread infectious diseases. What I love about working on infectious diseases is that everyone can relate to it.

While I’m a scientist, I’m also girly and fashionable. (I don’t think being a scientist means wearing boring clothes and horn-rimmed glasses!)

Lauren Castro

Growing up in Los Alamos as the daughter of a materials science engineer, I was exposed to physics, chemistry, and engineering from an early age. However, I found that my interests lied in biology. I loved reading about how infectious diseases have shaped the course of human history and the global effort during the Cold War to eradicate small pox. I memorized obscure pathogen names, such as Borrelia burgdorferi (the bacterium agent of Lyme disease) and imagined that one day I would work in the highest biosafety level lab, decked out in a positive-pressure suit, handling the world’s deadliest pathogens. At this time, I recall enjoying my math classes in high school, but didn’t see how algebra and calculus would serve this vision.

When it came time to pick a major in college, I knew I wanted to study infectious diseases. At first, I thought that this limited me to studying viruses, proteins, and the immune system. Luckily, I met a senior my first week at Princeton University who told me about a degree program called Ecology, Evolution, and Behavior (EEB), which focuses on the macroscopic aspects of biology. She called herself a disease ecologist, which I learned was the subdiscipline that studies how species-pathogen interactions and environmental conditions affect disease transmission. The part that sounded really cool to me was that she got to do field work in Kenya! In that instant, I changed my mind from majoring in microbiology to EEB. Frankly, I had had experience with laboratory bench work by this time, and my dream of working in a biosafety lab seemed less appealing.

Towards the end of my degree, while doing field work in Panama on Chagas Disease (and realizing that field work also wasn’t as glamorous as I had envisioned), I met a professor who showed me how to model Chagas transmission using differential equations. The fact that you could use math to understand how diseases spread and how different interventions would impact an epidemic’s trajectory blew my mind. As I started looking into mathematical modeling, even completing an extra senior thesis chapter using a model of my own, I learned that modeling groups around the country had helped guide the government responses to the 2009 H1N1 pandemic and 2003 SARS outbreaks, both outbreaks which I could remember. These modelers became idols to me.

After getting my undergraduate degree, I headed home to Los Alamos to spend a year working at LANL and preparing to apply to graduate school. Ultimately, I decided on The University of Texas at Austin (hook em’!), where I learned how to harness both mathematical modeling and the power of computers to study how diseases spread, how they evolve as they do it, and how to track both in real-time. I worked on a range of viruses, including the 2016 Zika 2016, seasonal influenza, and HIV. Over the five years that I was at UT, I realized working at my desk, coding up equations and probabilities into large-scale simulations, I could be transported me to a world that was more exciting to me than any field work or bench work I could imagine.

I completed my Ph.D. in May 2019 and was offered a postdoctoral position at LANL to build forecasting systems, like weather systems, for infectious diseases. Wouldn’t it be useful to know how many cases of flu to expect in the next few weeks? I chose to come to LANL for many reasons, including the mountains and green chile, but also to work with one of those idols, Dr. Sara Del Valle. It’s been a great few months, and I’m looking forward to being at an institution where I can continue to engage in meaningful science.

Contact the presenter - remember to include your email address if you want a response.

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October 2019

Computer Hacking Fundamentals: Learning to think like an attacker so you can be a good defender

Neale Pickett

Los Alamos National Laboratory