Ice Penetrating Radar: A Window into the Physical Processes of Ice Sheets
Dr. Dustin Schroeder, Assistant Professor, Department of Geophysics and (by courtesy) of Electrical Engineering, Stanford
Radio echo sounding is a uniquely powerful geophysical technique for studying the interior of ice sheets, glaciers, and icy planetary bodies. It can provide broad coverage and deep penetration as well as interpretable ice thickness, basal topography, and englacial radio stratigraphy. However, despite the long tradition of glaciological interpretation of radar images, quantitative analyses of radar sounding data are rare and face several technical challenges. These include attenuation uncertainty from unknown ice temperature and chemistry, clutter and losses from surface and volume scattering, and a lack of problem-specific radar theory. However, there is rich, often under-exploited, information in modern radar sounding data, which is being collected over terrestrial and planetary ice at an unprecedented rate. The development and application of hypothesis-driven analysis approaches for these data can place observational constraints on the morphologic, hydrologic, geologic, mechanical, thermal, and oceanographic configurations of ice sheets and glaciers. These boundary conditions and the physical processes which they express and control – are filling a fundamental gap our ability to understand the evolution of both marine ice sheets and icy moons. These include the subglacial hydrology of marine ice sheets and the thermophysical structure of planetary ice shells.
Shining a Light on Health Using Color-Changing Nanoparticles
Alice Lay, PhD Student, Applied Physics, Stanford
Imagine a future in which you can shine a light to diagnose and treat cancer, see neurons fire in real time, and sort molecules. Nanotechnology is making that future possible by means of particles as small as a few DNA base pairs. These nanoparticles can be deployed with minimal invasiveness through the bloodstream, ingested, or even taken up by the roots of a plant. In my research, I design luminescent nanoparticles that emit visible light when excited with near infrared light. In the presence of a mechanical stimuli, like a push or a squeeze, they change color, allowing us to see differences in mechanical environments or track force-dependent behavior like chewing. In this way, we would be able to distinguish diseased cells or organisms from healthy ones; cancer cells, for example,are typically stiffer than normal cells. We envision these nanoparticles becoming next generation tools in medicine, allowing us to better monitor our health with a simple flash of a light.
Listen Up: Learning About Whale and Human Behavior in the Oceans Using Acoustics and Machine Learning
William Oestreich, PhD Student, Biology/Hopkins Marine Station, Stanford
The ocean, much like the world we experience on land, is a noisy place. In contrast to the perception of the ocean as a “Silent World,” popularized by Jacques Cousteau in the 1950’s, we have come to know the oceans as a magnificent soundscape full of noises from wild animals, weather, and human activities. Sound is of particular importance to marine animals, such as whales, that have evolved to use sound as their means of communication. Over the decades, scientists have learned a great deal about whale call types, associated behaviors, and the influence of human generated noise on these behaviors. However, much of this work has been limited by the logistical challenges of making long-term recordings underwater and the difficult task of analyzing massive amounts of acoustic data. The growing footprint of human-generated noise in the ocean (a roughly tenfold increase over the last 50 years), has only added to the complications, and intrigue, of such research. Using cutting edge approaches in under-water recording, also known as passive acoustic monitoring or PAM, and machine learning, we are uncovering new insights on both whale and human behavior in the oceans. The potential impacts of human-generated sounds on whales have caught the attention of scientists, conservationists, policy makers, and increasingly, the broader public. Better understanding the ways in which both humans and whales use the ocean, and the sounds they make doing so, is essential to making sure the ocean is enjoyed by the next generation of humans and whales alike
Changing the Gut Feeling in Medicine: The Microbiome in the Clinic
Jessica Ribado, PhD Student, Genetics, Stanford
The collection of the millions of microbes that live on the inside and outside of our body is referred to as the microbiome. Despite there being 10x more microbial cells than human cells and 150x more microbial genes than human genes within our microbiome, its roles in health have been vastly underappreciated due to limitations in technology. These communities is traditionally difficult to study due to issues in culturing them and the prioritization of studying disease causing organisms. However, using next generation sequencing technologies, we now have the ability to identify which microbes are present in these communities. In my Ph.D., I study how the gut microbiota affects blood cancer treatments and outcomes. My research focuses on the role of microbiome interventions to improve the severity of gut associated treatment complications in mouse models. I will cover methods used to manipulate the gut microbiome both in my research and the clinic – including antibiotics, fecal matter transplants, and prebiotics – their broader implications on future treatments.
CMB-Stage 4: The Next Generation Ground-Based Experiment for the Cosmic Microwave Background
Cyndia Yu, PhD Student, Physics, Stanford
Since its discovery by Penzias and Wilson in 1964, the leftover light from the Big Bang has been measured to stunning precision by generations of experiments. These observations of the cosmic microwave background (CMB) have yielded great triumphs for the Standard Model of Cosmology, our current best model for the origin and evolution of large scale structure of the universe. Current CMB ground-based experiments each have thousands of pixels that allow us to detect changes in temperature smaller than one millionth of one degree. CMB-S4, the next generation ground-based experiment, will unite scientists from dozens of institutions to build telescopes with hundreds of thousands of detectors on the sky. In addition to conclusively constraining some of the most favored models for general relativity, inflation, and dark energy, this data will provide a wealth of information about the fundamental nature of our universe and its origins. I will discuss the history of CMB cosmology from its humble origins of a single antenna receiver in the field of New Jersey to my work building tools that will enable us to put a half million detectors into telescopes around the world. Along the way, I will cover how insights from CMB data have enabled us to build our modern understanding of the history of the universe.
Chytrids: Taming an Emergent Pathogen
Dr. Krishnakumar Vasudevan, Postdoc, Biology, Stanford
Chytridiomycosis is an emerging infectious disease responsible for a global decline in the population of frogs and other amphibians. It is caused by two members of a very interesting group of fungi called chytrids. Chytrid fungi are different from other well-known fungi such as yeast, in that they share many features with animal cells, such as motility. Although much effort has been directed towards understanding the distribution, ecological impact, and mechanism of infection of these pathogens, there is no established method for growing chytrids in the lab in order to understand their basic biology and pathogenic mechanisms. My goal is to “tame” a wild chytrid species so that we can learn about it at the cell and molecular level. We have identified a species of chytrid that is non-pathogenic but grows well in the lab. So far, we have sequenced the genome and have observed several interesting features of their life cycle pertaining to cell motility and division. We are currently developing a method to alter genes that might be involved in regulating the chytrid life cycle. Using this knowledge, we are hoping to identify a way to target chytrid fungi, or even the pathogenic chytrids, in order to save the frogs and other amphibians. We are also working to make the tools necessary for studying chytrid fungi widely available so that the next generation of scientists will get involved in research on this fascinating group of organisms.
Move Over Tesla!: Using Genome Editing Technologies to Create Next Generation CARs That Will Drive Through and Kill Solid Cancers
Lashawn Peña , PhD Student, Immunology, Stanford
In my laboratory, I am able to isolate immune cells from your blood and create next generation CARs that can potentially target and kill the worst cancers known to humankind! Yes, I can create CARs, but no, not the Ford or Tesla kind you’re perhaps thinking of! I am referring to the next generation of cancer hallmarks, Chimeric Antigen Receptor (CAR) T cells, which are T cells with engineered receptors on their cell membrane that allows it to recognize and kill cancer cells. A T cell is a type of lymphocyte (white blood cell) that are the killer cells of your immune system and CAR T cells is currently revolutionizing how cancer is treated, with clinical trials showing huge remission (loss of cancer) rates of up to 94% in severe cancer types. Despite CAR T cells therapy being hailed as the cure for cancer, it is far from perfect. There are several challenges, which include the nasty environment tumors create around themselves to stop CAR T cells from killing them. Tumors can release molecules called cytokines that cause the CAR T cells to stop working and die! To make them resistant to these malicious attacks, I am utilizing next generation genome editing technologies such as megaTAL and CRISPR-Cas9 to remove the CAR T cells’ ability to be suppressed by these cytokines. If successful, my thesis project has the potential to expand the utility of CAR T cells to fight against solid tumors, which thus far have been unsuccessful.
How to Succeed in a Summer Research Internship
Dr. Katherine Alfieri, Scientific Program Manager, Stanford
Have you landed a summer research internship this year and don’t know what to expect? Are you thinking about trying summer research next year, but not sure if it’s for you? Come to this workshop! We’ll talk about the value of doing a summer
research internship, what to expect, and how to make the most of it. Come with questions!
How a New Neuron Finds Its Place in the Growing Brain
Dr. Georgia Panagiotakos, Sandler Faculty Fellow, UCSF
In the normal developing brain, new neurons are generated from the division of less specialized cells called neural stem cells. Neurogenesis, the process by which new neurons are born and integrated into the developing brain, involves a series of precisely timed events that are essential both for making neurons of the correct type in the appropriate place and time, and for ensuring that new neurons properly connect to one another to form brain circuits that control behavior. When any of these cellular events go awry, the consequences on brain function can manifest as neuro-developmental disorders like intellectual disability and autism. In this lecture, I will review the different types of research being done in the field of brain development, with an eye towards identifying major unanswered questions. I will also describe my lab’s specific area of interest, which is understanding how electrical signals in the embryonic brain regulate the development of specific types of neurons.
Big Data Meets Art: Using Visualizations to Unravel the Mystery of Drug Resistance in Cancer
Melissa Ko , PhD Student, Cancer Biology, Stanford
Despite our efforts to understand cancer, how many commonly used cancer treatments work remains a mystery. This mystery makes it especially difficult to fix therapies that no longer work. To develop better treatments, we need to understand how some cancer cells resist treatment when most die. Using new technologies, we try to ask: what is happening inside cells after drug treatment? What makes certain cancer cells drug-resistant? I survey millions of cancer cells: measuring molecules in these cells that describe whether they are alive or dead, whether they are dividing or inactive, etc. My data profiles 30+ features in each cell, corresponding to an individual data point in 30-dimensions, which we cannot even imagine. In this new generation of “big data,” there is too much info for any one person to sift through to find the answer. We must use computers to reveal patterns in this data that explain how a cancer treatment does or does not work. I can summarize important patterns in my data using graph-based visualizations, a tool that can represent the power grid that keeps the lights in your house on or the network of your friends on Facebook. From these images, I have identified key molecules driving drug resistance in cancer. In patients, we have shown that treating in combination (i.e. using the first drug plus another drug that targets these key molecules) can effectively kill a patient’s cancer cells. Ultimately, using computers to make sense of our data may guide us to long awaited discoveries for cancer treatment.
A Quick Guide to Observing Invisible Matter
Matthew Solt, PhD Student, Physics, Stanford
Modern cosmology has a big problem – our current understanding of matter and gravity cannot account for velocity measurements of stars in galaxies. They are traveling too fast! This and a few other cosmological measurements reveal compelling evidence that our universe is dominated by an invisible matter called “dark matter.” This dark matter has left a profound impact on our universe from cosmic evolution to potentially being indirectly responsible for the extinction of the dinosaurs. We know regular matter is made up of protons, neutrons, electrons, etc. and interacts through a few basic fundamental forces such as electromagnetism and nuclear forces. Unfortunately, the fundamental nature of dark matter remains elusive even after several decades of searching. One method that is being used to probe dark matter is large particle accelerators which collide subatomic particles near the speed of light in an attempt to create dark matter and observe its interactions. Hidden sectors is one particular model of dark matter that can be probed with accelerators and proposes an entire zoo of exotic invisible particles that do not interact directly with regular matter but can have self-interactions as complex as regular matter. This means the universe could have another hidden physical sector which contains dark matter, dark electromagnetism, or even dark nuclear forces. I work on an experiment called the Heavy Photon Search that attempts to probe such a hidden sector using a particle accelerator. Although nearly completely hidden from us, we can detect hidden sectors through a striking experimental signature.
Watering Plants With Ocean Water… The Next Generation of Agricultural Plants
Ying Sun, PhD Student, Biology, Stanford
As the human population increases, we will require more food and water to ensure our survival. Current agricultural supplies are struggling to meet our increasing demands. In order to grow more sustainable sources of food, we need to find innovative ways to grow our crops. Evolution is the ultimate innovator. Many plants in the wild have already evolved traits like drought resistance or tolerance to soil toxins to survive in their native environment. We can borrow these traits to generate the next generation of crop plants that are tolerant to climate change. My project aims to understand how genetic mutations bestow selective advantages to particular species. I identify genes in wild plants that give them stress tolerance traits and put those genes into agricultural crop plants to test their effect. Crops 2.0 will help feed the next generation of humans.
Smaller, Faster, Cheaper: A Lithographer’s View on the Future of Electronic Devices
Maryann Tung, PhD Student, Electrical Engineering, Stanford
In 1965, Intel co-founder Gordon Moore famously predicted that the number of transistors in an integrated circuit would double every eighteen months. For decades, Moore’s Law has driven research in semiconductor manufacturing towards smaller, faster, and cheaper devices for consumer and industrial electronics. In recent years, however, we have witnessed a steady drop-off in the pace of device scaling, causing widespread predictions about the end of Moore’s Law. One of the major bottlenecks for continued device scaling is the technology used to print the assorted lines and holes that make up integrated circuits. This process, called lithography, uses light to transfer geometric patterns onto a substrate; traditionally, as the patterns shrank to make smaller devices, the wavelength of the light used would shrink as well. However, we have already reached the shortest wavelength of light compatible with traditional lithography systems, so we need to explore other options to print the densest features in the next generation of state-of-the-art computer chips. Currently, the landscape of successors to optical lithography has four primary candidates: multiple patterning, extreme ultra-violet lithography, electron-beam lithography, and block copolymer directed self- assembly. In this talk, I will lay out the patterning requirements for small devices, compare how each of these candidates stacks up in relation to the needs of industry,and discuss my work in pushing directed self-assembly toward industry viability.