H2H8 Explorers

Grant Recipients

Pioneer Club Events

Welcome Explorer Lunch

H2H8 welcome lunch for 2021 Explorers.

Research Talks

Explorers share their research projects with other explorers for discussion, and exchanging ideas. Research talks are typically followed with dinner.

Dinner and lunch social gathering

Explorers getting together for dinner or lunch.

Explorers discuss desired activities

Pioneer Club activities is coordinated by Community Guardians who are graduate researchers. Guardians solicit input from explorers for the type of activities they desire. Guardians then organize such activities. H2H8 funds all Pioneer Club activities.

Annual Special Event - Winery & Climate Change Tour

H2H8 board members organized a special off-campus event each year. For 2022, the event was wine tasting, winery tour at Silver Oak and talk on climate change challenges for winery. H2H8 invited UCB faculties, Explorers, members, and guests to this event.

Welcome Guardian Luncheon

H2H8 welcomes 2022 Guardians at the Faculty Club.

Explorers Categories

Shao-wen Chang

Physics; 2022 Explorer

Study theoretical models for materials

My research is focused on the study of theoretical models for materials, which is the starting point for us to understand material properties. I am interested both in topics that are already promising candidates for a new generation of technology, and in phenomena that are not yet demonstrated and have no clear application in real life. For example, the model for herbertsmithite-like lattices have similar features with twisted bilayer graphenes in terms of their band structures, which govern the behavior of particles in materials. The latter has been of great interest since the demonstration of superconductivity in 2018. By studying the behavior of atoms in our optical lattice, we can get insight on e.g. the critical parameters at which the phase transition to superconducting states occurs. On the other hand, there are predictions of novel phases of matters for our lattice model.

Ziman Wu

EPS; 2022 Explorer

Study marine sediments to learn Earth's surface history

I’m working on understanding the early diagenesis processes of marine sediments and figuring out how recrystallization changed major geochemistry records. My work for now is studying shallow carbonate sediments collected from Bahama and processing simulation lab experiments and would follow with modeling building.

Pietro Federico Vannucci

Environmental Engineering; 2022 Explorer

Reductions in pollution

My research interest is aerosols, or particulate matter (PM). Up until now, I have been working to understand what has historically driven high PM events in urban spaces with the goal of working towards achieving meaningful reductions in pollution going forward. Specifically, I have been studying the effect of temperature on PM levels, and how the relationship between the two has been evolving over time.

Emma G. Berger

Physics; 2022 Explorer

Explorer how electrons can serve as next-generation qubits

I am studying the molecular qubits with a scanning tunneling microscope equipped with electron spin resonance capabilities (STM-ESR). This novel experimental method only demonstrated in 2015 and for which only a handful (<10) groups in the world have the capability of performing, will allow for unprecedented measurement and control of single molecular qubits. The goal of my PhD research is then, in short, to use STM-ESR to demonstrate coherent control of bottom-up designed molecular qubits.

Alexandre E. S. Georges

Environmental Engineering; 2022 Explorer

Natural infrastructures to mitigate impacts of sea-level rise

My research aims to identify and/or promote natural infrastructures, particularly mangrove forests, as a barrier that can be used by small island nations (particularly in Haiti and the rest of the Caribbean) to mitigate the onset and impacts of sea-level rise.

Vivek Kamarshi

Bioengineering undergraduate; 2022 Explorer

Research the Human Immunodeficiency Virus (HIV) in its ability to evade treatment

Originally from near San Jose, CA, I’m a senior undergraduate student studying Bioengineering. In past research projects, I’ve studied the impacts of the gut-brain axis on neurodegeneration in fruit flies, as well as identified cellular pathways involved in the “fusion” mechanism of the varicella zoster virus.

My current work in Iain Clark’s group at UC Berkeley focuses on developing tools to study the Human Immunodeficiency Virus (HIV), particularly its ability to evade treatment by integrating itself into a person’s DNA. The novel method I’m developing aims to rapidly find the single HIV site in an entire human genome and sequence it, bettering our understanding of how HIV persists in patients over long periods of time. I also do community service work through the student club I founded, UpInnovate at Berkeley, which builds connections between under-resourced high schools and academic labs and researchers.

After my undergraduate, I plan to pursue a PhD in the bioengineering field.

Luis Valencia

Bioengineering; 2022 Explorer

Engineer microbes to produce antibiotics or fuels

I’m Luis! I’m a PhD student in the Berkeley BioE department. I engineer microbes to produce valuable molecules such as antibiotics or fuels from plant-derived feedstocks in the Keasling lab. I have recently become interested in the possibility of using microbes to mine metals from water sources.

Yiming Zhang

EPS; 2022 Explorer

Reconstruct history of Earth's magnetic field and tectonic plate configuration

I am a 4th year PhD student at the Earth and Planetary Science department. I integrate original field observations with laboratory data sets to reconstruct the history of Earth’s magnetic field and tectonic plate configuration. In particular, I study Proterozoic intrusive rocks to gain new insights into the long-term evolution of the intensity of Earth’s magnetic field. I also set up a Quantum Diamond Microscope at UC Berkeley Paleomagnetism Laboratory which enables us to characterize rock magnetic properties at micron-scale. Currently I am also working on integrating paleomagnetic data with thermochronology data to study the uplift history of the Adirondack Mountains, NY.

Alicia Tsai

EECS; 2022 Explorer

Optimization, models, & algorithms for Machine Learning

Alicia is a PhD candidate in Computer Science affiliated with the Berkeley AI Research (BAIR) Lab. She focuses on optimization, new computational models, and algorithms for machine learning, with a focus on efficiency and robustness.

Alex Moreno

EECS; 2022 Explorer

Low power wireless radio sensor for fires & natural disasters

Why I’m Here I am a Ph.D. EECS student in Professors Kris Pister’s lab. My research area is low power wireless radios. My vision is to make wireless sensors 5 times smaller than a grain of rice while making it reliable and robust enough to use. I believe that our society could benefit greatly from having small affordable sensors to make informed decisions on fires, natural disasters, etc. About Me I am a Ph.D. student in EECS focused on integrated circuit design for low power wireless radios. I enjoy dancing salsa/bachata, biking, running, rock climbing and playing guitar.

Yoon Lee

IEOR; 2022 Explorer

Local water inventory management for the developing world

I am a fifth year PhD candidate in IEOR at UC Berkeley. I received a BS in applied and computational mathematics from Caltech, and a MS in industrial engineering and operations research from Berkeley. Previously, I was a research scientist intern in Amazon – Digital Privacy Team. My research interests include data-driven decision making, with particular emphasis on addressing inefficiencies and inequalities in health systems.

Marianne Cowherd

Environmental Science; 2022 Explorer

Post-wildfire snow hydrology in the Sierra Nevada

I’m a third year PhD student in Environmental Science, Policy, and Management, where I work with Manuela Girotto and Scott Stephens on post-wildfire snow hydrology in the Sierra Nevada. I also work on global climate modeling of future snow defecits and hydrology applications of machine learning methods. I like running, biking, and trying new foods.

David Any

Mechanical Engineering; 2022 Explorer

Plastic deformation mechanisms in titanium

Born and raised in Toulouse, France, I studied materials and mechanical engineering for my undergrad at Ecole des Ponts ParisTech in Paris. In 2020, I became a PhD student at UC Berkeley in the Mechanical Engineering department. Through my different research projects, I’ve specialized in materials computational theory. Part of Chrzan’s research group, I’m currently studying plastic deformation mechanisms in titanium at the atomistic level through computational simulations.

Alexander Alvara

EECS; 2022 Guardian

Applications for MEMS and 3D Printing

4th year PhD Candidate in Mechanical Engineering working in an Electrical Engineering lab (Pister Group) on multiple applications for MEMS and 3D Printing.

Massimo Pascale

Astronomy; 2022 Guardian

Research dark matter substructure

I’m a fourth year grad student in Astronomy at UC Berkeley, where I work with Liang Dai on gravitational lensing, specifically on dark matter substructure and lensed stars/star clusters. When I’m not doing astronomy, I enjoy powerlifting and spending time with friends!

Emma Turtelboom

Astronomy; 2022 Guardian

Research on exoplanets

I’m a graduate student in the astronomy department at UC Berkeley, and my research focuses on exoplanets, which are planets orbiting stars other than our Sun. I am interested in learning about how similar (or dissimilar) other planetary systems are to our own Solar System. I also enjoy baking and hiking!

Anthony Joseph Fuentes

EPS; 2022 Guardian

Develop a record of the paleoenvironmental and palaeoecological turnover across the KPB

I am the first of my family to attend college and as such I am particularly motivated to help broaden the participation of underrepresented groups in STEM. The Cretaceous-Paleogene boundary (KPB) is associated with one of the five largest mass extinction events in the geologic record and is typified by the rapid loss of taxa such as the non-avian Dinosaurs. The extinction may serve as an analog to the modern ecological crisis. I will work to develop a high-temporal resolution record of the paleoenvironmental and palaeoecological turnover across the KPB using plant and bacterial biomarkers preserved in low grade coals (lignites) in the Hell Creek region of Montana.

Ellianna Abrahams

Statistics; 2022 Guardian

Utilizing deep learning to understand coastal melting at the poles

Ellianna is building and implementing physics-informed machine learning architectures that accelerate discovery and analysis in astrophysical and earth science settings. A coastal polynya is an area of open water, bounded on one side by land ice, and surrounded on all other sides by sea ice. I am working to create a dataset by developing a deep learning image segmentation pipeline that incorporates the geography necessary for the creation of coastal polynyas. This study will help us to understand the rate at which coastal melting is occurring at the poles, which has long term implications for the continued use of the ocean as a natural carbon sink.

Numi Sveinsson

Biomechanics Engineering; 2022 Guardian

Utilizing ML for blood flow simulations for medical purpose

Numi Sveinsson was born in Copenhagen, Denmark but grew up in Reykjavik, Iceland and Miami. My research aims at utilizing machine learning to automatize patient specific blood flow simulations for medical purposes. I am currently implementing a machine learning approach to determine automatically the geometry for blood vessels of interest from medical images.

Samuel Alber

EECS undergraduate; 2022 Explorer

Research single cell datasets for understanding immune-mediated system

I am an undergraduate student studying computer science and physics who is interested in using these two fields to better understand our immune system. I leverage multi-omics single cell datasets from patients with immune-mediated diseases to increase our understanding of pathogenesis in these diseases. Since these datasets are heavily influenced by biases and patient heterogeneity, I am also developing computational methods for analyzing these datasets more robustly. After college, I hope to pursue a PhD in computational biology and continue using computational tools to help treat immune-mediated diseases.

Christian Ikeokwu

EECS; 2022 Guardian

Research AI, mathematical economics to solve societal problems

I’m a 2nd-year Ph.D. student in Computer Science affiliated with the CS Theory Group and the Berkeley AI Research (BAIR) Lab. I do research in theoretical computer science (TCS), artificial intelligence (AI), mathematical economics, and their intersections. Most recently, graph theory, algorithmic game theory, statistical learning, and combinatorial optimization. I also think about how tools and techniques from TCS, AI, and economic design can yield insights about and help solve important societal problems.

I grew up in Lagos, Nigeria before moving to the US in 2017 to attend Oberlin College and Conservatory, from which, I graduated in May 2021 with a BA in Math and Computer Science (Highest Honors). In my spare time, I’m an avid enjoyer of fantasy novels, manga/manhwa, comics, and world history.

Malcohm Spilka Lazarow

Physics; 2022 Explorers

Research gravitational waves

Born and raised in San Mateo, California, Malcolm Spilka Lazarow is currently a physics PhD student at UC Berkeley. For most of his life, Malcolm studied to become a composer for film, television, and electronic arts, but he changed this goal in 2016 when LIGO announced the first ever detection of gravitational waves from the merger of two black holes. After finishing his undergraduate degrees in music and math, he spent a few gap years doing research in theoretical plasma physics at UC Berkeley. He is now a member of Liang Dai’s group, where he studies gravitational waves, the theory of general relativity, and geometric numerical methods. In his spare time, Malcolm still composes and designs sound installations. His favorite genres of music are musique-concrete and grunge.

Alexander James Ehrenberg

Integrative Biology; 2022 Explorer

Neurodegenerative disease vulnerability

Alex started off in the neuropathology core at UCSF’s Memory and Aging Center in 2013 under the mentorship of Prof. Lea T. Grinberg. There, he developed interests in the factors that influence selective vulnerability underlying early Alzheimer’s disease stages and associated neuropsychiatric manifestations. Now a Ph.D. Candidate at UC Berkeley, he is co-advised by Prof. Grinberg and Prof. Daniela Kaufer and continues his focus on neurodegenerative disease vulnerability. He also has research interests in natural history and comparative neurology where he examines the evolutionary framework surrounding neurodegeneration and neurologic aging.

Sean Eisaku Kitayama

Bioengineering; 2022 Explorer

Engineering in vitro, multicellular tumor microenvironment

Sean Kitayama hails from the suburbs of Los Angeles and received his B.S. with honors in bioengineering from UC Berkeley in 2018 as a Regents’ and Chancellor’s Scholar. During his undergraduate career, he worked in the laboratories of Professor Shuvo Roy at UCSF and Professor Mohammad Mofrad at UC Berkeley, using microfabrication techniques to develop implantable medical devices, ranging from bioartificial organs to biosensors. Sean is currently a Ph.D. candidate in the UC Berkeley-UCSF Graduate Program in Bioengineering, working under the direction of Professor Lydia Sohn, where his current projects involve utilizing novel engineering technologies to recapitulate the tumor microenvironment in vitro. He is interested in answering fundamental questions in cancer biology, specifically on the role of extracellular vesicles and cancer-stem cells in the metastatic cascade, which potentially has implications in guiding the development of future targeted therapies for metastatic cancer. Outside of lab, Sean is involved in engineering educational outreach, plays the clarinet in the university orchestra, travels avidly, and enjoys oenology and gastronomy.

Cameron T Kato

Bioengineering; 2022 Guardian

Pharmacological research to treat degenerative chronic illnesses

Originally from Southern California, Cameron Kato first came to UC Berkeley in 2015 as an undergraduate to study Bioengineering. During his undergraduate years, he studied aging and stem cell engineering under the mentorship of Professor Irina Conboy. After earning his bachelor’s degree in Bioengineering, Cameron began study in the UC Berkeley-UCSF Graduate Program in Bioengineering to pursue his PhD. He is continuing his research in the lab of Dr. Conboy, focusing his efforts on pharmacological approaches to treat the degenerative chronic illnesses that often come with advanced age. Specifically, he is researching brain and muscle tissue, and how to restore senescent cell populations to a healthier state. He hopes that eventually his research will be used to help alleviate the immense physical and financial burden faced by many due to debilitating chronic illnesses. Outside of the lab, Cameron enjoys playing badminton and board games with his friends and taking trips around the Bay Area.

Vamshi Balanaga

Physics undergraduate; 2022 Explorer

Quantum materials & plasma physics

I’m a physics student who’s interested in solving climate change. My academic interests range from novel quantum materials to plasma physics. I am a part of Space Enterprise Berkeley, a rocket engineering team on campus. I moved between India and Indiana several times while growing up. I like to spend my free time outdoors, either climbing, hiking, surfing or kayaking.

Ritwik Gupta

EECS; 2022 Explorer

Computer vision for humanitarian assistance and disaster response,

Ritwik is a second year Ph.D. student at UC Berkeley focused on efficient computer vision for humanitarian assistance and disaster response, and technology-policy co-design to ensure the safe and reliable use of these technologies in developing countries. Ritwik’s research has been used widely by over a hundred organizations such as CAL FIRE and the United Nations.

Kevin Joslin

Bioengineering; 2022 Explorer

Technologies to study the central nervous system

I’m a 3rd year PhD student at the UC Berkeley-UC San Francisco Joint Program in Bioengineering and an NSF Graduate Research Fellow. I develop and apply high throughput, single cell, multiomic technologies to study the central nervous system. I currently research in the lab of Iain Clark at UC Berkeley, and I previously received my BS in bioengineering from UC San Diego.

Rowan Duim

Physics; 2022 Explorer

Research ultracold atomic physics

I grew up in Ontario, Canada and moved to sunny Berkeley in 2021 for the physical chemistry PhD program. Working in an ultracold atomic physics group, I do quantum simulation of crystalline materials using laser-cooled atoms in an optical lattice. In particular, we study the Kagome lattice, which exhibits geometric frustration, a property that can lead to exotic states of matter.

Galen Chuang

EECS; 2022 Explorer

Research theoretical visual neuroscience

2nd year Vision Science PhD student, studying theoretical neuroscience advised by Bruno Olshausen.

Samantha Coday

EECS; 2022 Explorer

Power converters to enable electric aircrafts and space travel

I am a PhD candidate in EECS studying next generation power converters to enable electric aircrafts and future space travel.

Daniel Rothchild

EECS; 2022 Explorer

Computational chemistry with Machine Learning

I’m a PhD student in EECS. I currently work on accelerating computational chemistry with machine learning

Chitraang Murdia

Physics; 2022 Guardian

Quantum Gravity and String Theory

I’m a Physics Ph.D. student at UC Berkeley, working on Quantum Gravity. I am particularly interested in the black hole information paradox and the cosmological measure problem for the multiverse. I started my undergraduate education as a CS major at IIT Bombay in India. In my freshman year, I realized that I was really passionate about doing physics research, so I transferred to MIT. During my time there, I worked on how the quantum mechanical properties of an electron can be used to create monochromatic and unidirectional radiation. In my spare time, I like to read fiction and cook with friends.

Michelle Devoe

EPS; 2022 Guardian

Decipher the stress history of Earth's crust

I’m a 4th year PhD student in the Earth and Planetary Science Department. I’m developing a methodology to decipher the stress history of Earth’s crust.

Aliza Gray Beverage

Astrophysics; 2022 Explorer

Research galaxy evolution

I’m a 3rd year PhD grad student studying galaxy evolution. My thesis project is on understanding why galaxies die (when they really should be thriving!!).

Dillion Acker-James

EECS; 2022 Explorer

MEMS technology to create medical devices

I’m a graduate student studying Micro Electro Mechanical Systems (MEMS) who has worked on medical devices and transformative micro switches. I grew up in Santa Barbara and Mariposa: two very different places in California. I didn’t code nor take a physics class until undergrad and actually chose my focus in electrical engineering because I mistakenly thought that my grandpa was an electrical engineer. He did work for HP, but in the marketing department. Nevertheless, I thrived as an EE at UC Santa Barbara, and made the switch from III-V devices to MEMS in graduate school. The physics at the micro scale interests me because so much is counterintuitive, when compared to macro-physics, and can greatly impact our daily lives. I’m striving to make positive impacts with my work and life.

Ali Ameri

EECS; 2022 Explorer

Integrated circuits for biomedical applications

I am a PhD student in EECS working on integrated circuits for biomedical applications. My research focuses on the development of electronic platforms for cancer diagnosis and treatment by utilizing electromagnetic waves for sensing and stimulating biological samples at the single cell and tissue levels.

Austin Patel

EECS undergraduate; 2022 Explorer

Research in micro-robotics as well as computer vision

Austin was born in San Francisco and has grown up in Bay Area. He is a 4th year undergraduate at UC Berkeley studying electrical engineering and computer science (EECS). At Berkeley, he is involved with undergraduate research in a micro-robotics lab as well as a computer vision group. His research interests include deep learning, robotics, and computer vision and especially the intersection of those three subjects. In addition to research, Austin has enjoyed his time as a teaching assistant in an introductory electrical engineering course at Berkeley. Outside of academics, Austin enjoys running, biking, and exploring the outdoors.

Lucas Waldburger

Bioengineering; 2022 Guardian

Using high-throughput molecular technologies and machine learning to decipher natural biological systems

I am a Bioengineering PhD student studying computational and synthetic biology. My undergraduate research focused on developing molecular feedback systems to control synthetic programs using light and native pathways using designer proteins. Before graduate school I worked on engineering microbes to controllably colonize the gut and deliver a therapeutic payload to treat chronic disease. As a graduate student I have worked on optogenetic control of molecular systems, engineering synthetic immune cell circuits, and computational discovery of novel genome editors. I am currently working on using high-throughput molecular technologies and machine learning to decipher natural biological systems. I plan to use this knowledge towards engineering synthetic programs that are robust to complex environments.

Quincy Huynh

EECS; 2022 Guardian

Developing hardware for Magnetic Particle Imaging

I am a Bay Area native, attending UC Berkeley for my undergraduate degree in EECS, my master’s degree in EECS and now as a PhD candidate advised under Professor Steve Conolly. My research is developing hardware for Magnetic Particle Imaging (MPI). MPI is a radiation-free, positive contrast, tracer imaging modality with great promise for a variety of applications: stem cell and immune cell tracking, as well as lung, gut bleed, traumatic brain injury, and tumor imaging. My project is to design and implement an optimized front end hardware and electronics that I hope will enable even higher resolution, higher sensitivity, and quantitative, robust imaging for the clinic. Outside of research, I enjoy moving heavy things at the gym, running, and trying new healthy recipes in the kitchen.

Ando Shah

School of Information; 2022 Explorer

Designs and evaluates information systems and finance mechanisms that monitor and reward climate and biodiversity positive interventions.

Ando designs and evaluates information systems and finance mechanisms that monitor and reward climate and biodiversity positive interventions. He is currently a PhD student at UC Berkeley and an Innovation Fellow at Open Earth Foundation. In past lives, he has worked as a systems engineer, mixed-media artist, virtual reality pioneer, entrepreneur and filmmaker. Trained as a chip designer, he spent his formative years working in silicon valley designing hardware for video streaming and off-grid renewable energy systems for communities in east Africa. He created one of the first 360 video capture cameras, created and directed multiple VR experiences that were selected at Cannes Film Festival, Sundance Film Festival and others. He co-created the world’s first underwater camera trap and software identification system that was used to automatically identify individual manta rays. Ando was the co-founder and Chief Technology Officer of Ballast Technologies and created the field of aquatic virtual reality to study the effects of ‘virtual nature’ on the human brain, and build empathy for the ocean. He holds multiple patents in these fields and has been featured in the New Yorker, CNET, The BBC, Forbes, Discovery, Digital Trends, MIT Technology Review, WIRED, and Freethink amongst others.

Ryan Mei

EECS undergraduate; 2022 Explorer

Research synthetic biology using computational imaging, robotics, and deep learning

I’m a 4th year undergraduate at UC Berkeley studying EECS and Business Administration as a part of the Management, Entrepreneurship, and Technology (M.E.T.) Program. Living systems and light fascinate me, especially at the nano and microscopic scale. My current work concentrates on creating scalable platforms for synthetic biology with techniques from computational imaging, robotics, and deep learning. I work with Professor Laura Waller and previously have worked at Insitro, the Chan Zuckerberg Biohub, and Stanford Medicine.

Jasmine M Jan

EECS, 2022 Explorer

Investigates "Greener" solvents in the processing of organic photovoltaics and photodiodes

Jasmine was born and raised in the city of Diamond Bar in LA County, California. Her journey at Berkeley began as an undergraduate studying Bioengineering with a minor in electrical engineering and computer sciences (EECS). After graduating in 2019, Jasmine started her PhD in EECS with a research focus on printed electronics advised by Professor Ana Claudia Arias. Her thesis project investigates the use of “greener” and less toxic solvents in the processing of organic semiconductor devices. In particular, she is focusing on large-area printed photovoltaics and photodiodes. Outside of research, Jasmine enjoys cooking, hiking, and biking to tasty bakeries in the Bay.

Malte Schwarz

Physics, 2022 Explorer

Studying atoms cooled to just above the absolute zero-temperature

I’m a 3rd year physics PhD student at UC Berkeley studying atoms cooled to a few billionth of a degree above the absolute zero-temperature limit.

Kaylo Littlejohn

EECS, 2022 Guardian

Decoding speech and movement from persons with paralysis using brain-computer interfaces

Kaylo Littlejohn is a 3rd year Electrical Engineering and Computer Sciences Ph.D. student creating speech brain-machine interfaces in the Berkeley AI Research Lab and Chang Lab at UCSF. He is advised by Professor Gopala Anumanchipalli and Professor Edward Chang. His research is focused on decoding speech and movement from persons with paralysis using brain-computer interfaces. Kaylo received his B.S. degree in Electrical Engineering from Columbia University in 2020. During his time at Columbia, Kaylo developed VR 3D real time closed loop brain-machine interface paradigms under Dr. Paul Sajda. Now Kaylo works on the BCI Restoration of Arm and Voice (BRAVO) clinical trial and is broadly interested in real-time speech synthesis and machine learning applied to developing assistive communication devices.

Aniketh Janardhan Reddy

EECS, 2022 Explorer

Deep learning-based gene expression prediction

I am a Computer Science PhD student advised by Prof. Nilah Ioannidis. I work on problems at the intersection of machine learning and computational genomics. More specifically, I am interested in understanding and controlling gene expression by building prediction models that can be used to understand the regulatory functions of sequences and for interpreting the effects of genomic variants. I also work on understanding splicing and its regulation. My broader research goals are to use machine learning to understand, diagnose and treat human diseases. I worked on problems in natural language processing and computational neuroscience before starting my PhD.

Pietro Federico Vannucci

Environmental Engineering; 2022 Explorer

Research processes that drive and control pollution

Hi, I’m Pietro! I’m originally from Milan, Italy, but I’ve spent most of my life (from elementary school to university) in St. Louis, MO. I moved out to the Bay to attend a Master’s program here at Cal in Civil and Environmental Engineering and I’ve since completed it and begun to work on my PhD. My research is at the intersection of Environmental Engineering, Chemistry, and Public Health. I work to better understand air quality, both in terms of the processes that drive and control pollution, and the sensors/data analysis techniques we can use to better make sense of measurements. In my spare time, I like to be outside, whether that is cycling, playing tennis, golf, or soccer

Daniel Lim

Mechanical Engineering; 2022 Guardian

Data-Driven Mechanical Design

Ph.D. student working on Data-Driven Mechanical Design using computer simulation and artificial intelligence. I am really interested in inventing mechanical systems that could be used in real life. My project ranges from developing stealthy material for defense systems, to optimization of the semiconductor fabrication process. Recently, I started looking at ways to license the technology that I developed throughout my graduate studies to implement knowledge not only through the paper, but also to add value to the world.

Daniel Brethauer

Astronomy; 2022 Guardian

Research on supernovae in the final decades to millennia before they explode

I am a graduate student at UC Berkeley studying cosmic explosions like supernovae and kilonovae that provide key insights into fundamental physics and stellar processes. My research on supernovae has focused specifically on stars that have shown signs of expelling substantial fractions of their own mass in the final decades to millennia before they explode as a supernova in an apparent ‘tantrum’ indicating the star somehow knows of its impending doom. While I look at data across the electromagnetic spectrum, my specialty is in X-ray data reduction and analysis with facilities like the Chandra X-ray Observatory and NuSTAR, both of which are space-based telescopes.

Tanja Kovacevic

EPS; 2022 Explorer

Investigate thermodynamic material/transport properties of water-rich exoplanet interiors

Tanja (she/her) is a Ph.D. candidate in the Earth and Planetary Science Department at U.C. Berkeley. She used computer simulations to investigate thermodynamic material/transport properties of water-rich exoplanet interiors. Materials within planets are subjected to extreme pressures and temperatures and highly accurate ab-initio computer simulations offer us a glimpse into their interiors. She is currently working on calculating the equation-of-state for rock and ice mixtures (i.e. the miscibility curve).
On a personal note, Tanja is a refugee and a first-generation college student. She finds it imperative to continue mentorship and outreach efforts as she pursues a scientific career.

Quentin Eric Nicolas

EPS; 2021 Explorer

Tropical precipitation change due to global warming

My project aims to develop a quantitative understanding of precipitation around tropical mountains. Our first step is to develop a physics-based theory for the setting where a steady flow impinges perpendicularly on a mountain ridge; analogous to the Western Ghats of India, during the summer Monsoon. Future developments will consist in complexifying the problem to conform better to real-world mountains, where a complete atmospheric circulation can develop. This work will allow better preparation of the societies depending on freshwater input from mountains to future climate changes.

Thomas Krendl Gilbert

Interdisciplinary EECS Machine Ethics & Epistemology Postdoc CornellTech; 2021 Explorer

Safe, ethical AI systems

Thomas Krendl Gilbert is an interdisciplinary Ph.D. candidate in Machine Ethics and Epistemology at UC Berkeley, and an incoming postdoc with the Digital Life Initiative at Cornell Tech in fall 2021. With prior training in philosophy, sociology, and political theory, he designed this degree program to investigate the ethical and political predicaments that emerge when artificial intelligence reshapes the context of organizational decision-making. His recent work investigates how specific algorithmic learning procedures (such as reinforcement learning) reframe classical ethical questions and recall the foundations of democratic political philosophy, namely the significance of popular sovereignty and dissent for resolving normative uncertainty and modeling human preferences. This work has concrete implications for the design of AI systems that are fair for distinct subpopulations, safe when enmeshed with institutional practices, and accountable to public concerns, including medium-term applications like automated vehicles.

Stephanie Eberly

Mechanical Engineering; 2021 & 2022 Guardian

Physical behavior of neural stem cells

Stephanie graduated Valedictorian from North Carolina State University in the Spring of 2020 with a bachelor’s degree in Mechanical Engineering. During her undergraduate career, she worked on an array of research projects including: helping design a low-cost air quality measurement device for developing countries under Dr. Andrew Grieshop, augmenting the creation of an exoskeleton to improve hand dexterity of stroke survivors under Dr. Katherine Saul, and assisting in the development of an angle-resolved photoemission spectroscopy system under Dr. Darrell Schlom.

Stephanie is now a PhD student and Berkeley Fellow at the University of California, Berkeley. She plans on earning her doctoral degree in Mechanical Engineering with a concentration in Biomechanics and a minor in Neuroscience. Currently, she is part of Sohn Lab which conducts research in the areas of cancer and stem cell biology. Under the guidance of Dr. Lydia Sohn, Stephanie hopes to use brain organoids to enhance the understanding, diagnosis, and treatment of neurodegenerative diseases.

Marius Julius Wiggert

EECS; 2021 Guardian

Seaweed platforms for carbon sequestration

Marius Wiggert is originally from Germany where he studied Engineering Science, Philosophy, and Technology Management during his undergraduate. He is an outdoor enthusiast, enjoys camping on mountain tops, skiing, kitesurfing, and is an avid learner. In his EECS PhD at Berkeley, Marius focuses on developing methods that enhance the type of systems which we can reliably operate in and control. As he feels deeply connected to nature specifically the ocean and mountains, he initiated and won funding for his main research project: developing algorithms to reliably control underactuated seaweed-growing platforms in the ocean. To make seaweed-based carbon-sequestration as affordable as possible the platforms have limited energy and thrust smaller than ocean currents. This inspired the idea of the platforms “hitchhiking” on non-linear ocean currents to achieve steering over distances of hundreds of kilometers.

Julia DeMarines

EPS; 2021 Guardian

Search for Extraterrestrial

Julia DeMarines is an Astrobiologist and science educator. She is currently a PhD student in UC Berkeley’s Earth and Planetary Science dept doing joint research with the Berkeley SETI Research Center and the Blue Marble Space Institute of Science on a project attempting to determine what we “sound” like to an alien observer.  She also teaches with the international team of scientists/educators called the Ad Astra Academy. She is a 2019 AGU Voices for Science advocate, a National Geographic Explorer and a 2018 Grosvenor Teacher Fellow.  She holds a Master’s degree in Space Studies from the International Space University and a Bachelor’s in Astronomy from the University of Colorado. Her research involves biosignature and techno signature detections, the ethics behind messaging extraterrestrials, and the impact of educational activities. Julia also runs her own outreach events called  “Space in Your Face!” – a space variety show involving comedy, local artists, and cover songs. When she’s not doing science and communication she can be found cracking Uranus jokes, trying not to kill her plants, trail running, and hanging with her cat, Bella.

Wilson Oswaldo Torres

Mechanical Engineering; 2021 Guardian

Smartphone biometrics for arthritis

I want to empower older adults and those with manual conditions, like arthritis, to understand how their hand function changes as a result of aging, and/or the progress of their conditions.

Hand grip strength, pinch strength, joint range of motion, and skin tactility, are the most common ways to characterize hand ability, with the additional benefit of being great markers for general well-being. However, these are not frequently measured, and the tools required can be inaccessible to individuals.

My project aims to facilitate access to these hand parameters by merging custom smartphone applications with cutting edge tactile sensors. As a result, I hope that everyday activities of digital living, like sending text messages, accessing the internet, and making phone calls, will be transformed into clinical metrics that can track progress of hand functionality over time, giving individuals ownership and an understanding of their own health.

Guy Nir

Astronomy Postdoc; 2021 Explorer

Detection of Black Holes Binaries; ML

MSc and PhD from the Weizmann Institute in Israel. Led the commissioning of the W-FAST optical observatory, a robotic telescope that takes wide field images (~7 degrees-squared) at a high frame rate (25Hz), looking for fast and rare astronomical phenomena. Developed the software for observatory control, data acquisition and analysis for W-FAST as well as additional image processing algorithms.

Interested in small Solar System bodies and occultation surveys, rapidly changing variable stars such as short-period cataclysmic variables and low mass X-ray binaries, and fast optical counterparts to high energy astrophysical phenomena like GRBs or FRBs. Currently working on SkyPortal, an open source application to store, share, discuss, and process astronomical data, which can be used by small or large collaborations and projects in astronomy.

Nick Choksi

Astronomy; 2021 Explorer

Chondrules Origin Within Asteroids

I am a graduate student at UC Berkeley, studying theoretical astrophysics with a particular emphasis on the formation and evolution of planetary systems (for more details about my research, see here). Before beginning my graduate work, I was an undergraduate at Berkeley, and received my degree in physics in 2019. Outside of research, I like to play tennis, hike, and eat lots of hummus.

Sajant Anand

Physics; 2021 Explorer; 2022 Guardian

2 dimensional and non-zero temperature tensor networks

I am working on Tensor Networks (TN) project on efficient two-dimensional algorithms and approaches to better control quantum computers, I am currently designing and demonstrating a TN algorithm for efficiently simulating systems at finite (non-zero) temperatures. We hope to efficiently and accurately study finite-temperature systems beyond the capabilities of current approaches. Such an algorithm would allow us to accurately investigate physical phenomena, such as the fractional quantum hall effect, that have proven difficult for current methods. This phase of matter has long been conjectured to support novel particles that would facilitate robust quantum computing, and our finite-temperature tensor network algorithm will hopefully move us closer to answering this and many other outstanding questions.

Casey Lam

Physics; 2021 Explorer

First to detect isolated black hole

Casey Lam is a PhD candidate in the Astronomy Department at UC Berkeley. With her advisor Prof. Jessica Lu, she is hunting for isolated stellar mass black holes. Although there are predicted to be 100 million of them floating throughout our own Milky Way galaxy, no detections have ever been confirmed. Casey’s research is focused on using a technique called gravitational microlensing to make a first detection of one of these elusive isolated stellar mass black holes, and her thesis work tackles this problem through a combination of simulation, modeling, and observation. First to detect isolated black hole – https://youtu.be/NwV7rwAvNlg

Nathaniel Weger

Mechanical Engineering; 2021 Explorer; 2022 Guardian

Methane pyrolysis reactor to produce hydrogen

My motivation for much of what I do in life comes from two places: a desire to help other people, and a love for the outdoors. Naturally, this has led to a desire to reduce the impacts of climate change, both to reduce the suffering of other people and to minimize damage done to the environment. This desire is reflected in my research, where I am currently working in clean hydrogen production by methane pyrolysis in order to find ways to switch over to cleaner full sources. I’m also working on high temperature energy storage to ensure the stability of renewable energy, and I’ve previously worked on projects in biomass energy and flood prevention. My work aligns with my intention to do what I can to help other people, and I plan to continue this for the rest of my life.

Jacob Victor Spertus

Statistics; 2021 Explorer

Soil carbon sequestration

I grew up on a farm in Missouri where I learned firsthand the importance of taking care of the earth through sustainable farming. In graduate school, my background inspired me to use my statistical training to study regenerative agriculture and its potential to mitigate climate change. Regenerative agriculture may sequester substantial amounts of atmospheric carbon and restore soil health, making food systems more resilient to a changing climate. My research aims to identify weaknesses in soil carbon surveys, monitoring programs, and experiments, and provide better statistical tools to accomplish these tasks. I hope my work will contribute to more sustainable agriculture and a healthier planet.

Sevan Adourian

EPS; 2021 Explorer

Earth's deep mantle structure

I was born to a French-Armenian family of teachers living in the suburbs of Paris. I was accepted to UCB PhD program in Earth and Planetary Science for the Fall semester of 2017.

Complex interactions between different parts of Earth’s mantle — 3000 km of solid rock beneath our feet — push and pull tectonic plates through mantle convection where hot rock rises and cold rock sinks on timescales of 10s-100s millions of years. To understand processes at the surface, particularly earthquakes and volcanic eruptions, a deeper and wider understanding of Earth’s force balance must be obtained. My project team will use a combined approach of a theoretical framework and numerical modeling in order to retrieve a density model for the deep mantle, which is one of the missing pieces of the global mantle circulation that governs most of the surface tectonic processes.

Andi Gu

Physics undergrad. ; 2021 Explorer; @Harvard Graduate

Quantum Computing

In the field of quantum computing, there still remains a gap between the theory and practical implementation for most algorithms. This gap lies in the number of measurements required to achieve a high-quality result. I am interested in methods to reduce this requirement on the number of measurements. My project demonstrated the potential for certain classical machine learning algorithms to reduce the measurement requirements by orders of magnitude. This work will be key step to realizing the full potential of quantum computers.

Rachel Rex

Mechanical Engineering; 2021 Explorer

Cancer diagnostics & cause

Rachel Rex graduated from Johns Hopkins University in 2018 with a BS in Mechanical Engineering. As an undergraduate and one-year post-graduation, she worked in the Barman Laboratory, where she developed multimodal, plasmonic nanoprobes for prostate-cancer imaging.

Now, Rachel is a second-year PhD student in Mechanical Engineering at UC Berkeley, working in the Sohn Lab. Since beginning her PhD, she has been developing a microfluidic platform for rapid, low-cost diagnosis of Acute Promyelocytic Leukemia. She is also researching the inconsistent efficacy of immune checkpoint blockade, a promising form of cancer immunotherapy, in Triple-Negative Breast Cancer. Beyond her research, Rachel works to facilitate progress in education by promoting social justice in STEM. She is a member of a graduate student organization called Bias Busters, which aims to address implicit and structural bias in UC Berkeley’s engineering departments. Within this group Rachel helps lead workshops on diversity, equity, and inclusion in STEM.

Helen Fitzmaurice

EPS; 2021 Explorer

Air quality & climate change literacy

My research concerns quantifying emissions from the transportation sector using a dense sensor network in the Bay Area. To analyze effective methods that we can use to make inferences and new information about CO2 and particulate emissions from the transportation sector.

Nathan Owen Lambert

EECS; 2021 Explorer

Drone swarm safety

I am a PhD Candidate at the University of California, Berkeley working at the intersection of machine learning and robotics. He is a member of the Department of Electrical Engineering and Computer Sciences, formally advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab. Nathan also has worked extensively with and been advised by Roberto Calandra at Facebook AI Research. Nathan has joined Facebook AI and DeepMind for internships exploring his research interests.

Nathan is an active member of the Graduates for Engaged and Extended Scholarship in Computing and Engineering (GEESE) working to understand how technology interfaces with society, writing frequently at [https://robotic.substack.com]. During his Ph.D., he was awarded the UC Berkeley EECS Demetri Angelakos Memorial Achievement Award for Altruism.

Micah Carroll

EECS; 2021 Explorer

AI safety

I’m a second year PhD student at UC Berkeley’s [BAIR](https://bair.berkeley.edu/) and [CHAI](https://humancompatible.ai/), working with [Anca Dragan](https://people.eecs.berkeley.edu/~anca/) and [Stuart Russell](http://people.eecs.berkeley.edu/~russell/).

I’m broadly interested in ensuring human-AI systems work as intended and can be beneficial for the people involved: specifically, I’ve worked on improving the quality and robustness of agents trained to collaborate with humans, and am interested in the effects of recommender systems on users’ preferences and beliefs.

Caleb Xavier Bugg

IEOR; 2021 Explorer

Collective intelligence for machine learning

Caleb Xavier Bugg is a graduate student in the Department of Industrial Engineering and Operations Research (IEOR) at The University of California, Berkeley. We create mathematical models to optimize decision-making processes, using all the information and resources available at the time of decision. Ultimately, we hope to move Our society towards the equitable distribution of raw materials and production means.

Armando Avevalo

Physics undergraduate; 2021 Explorer

Spin Liquids

I study electronic structure, and from these calculations and other design principles known from this phenomena, I will be synthesizing new classes of honeycomb Kitaev quantum spin liquids,. The focus of this work will be in spin transport measurements of these materials.

Andre Lai

Bioengineering; 2021 Explorer

Low cost cancer screening & study

Born and raised in the eastern-most suburbs of LA county, Andre first started engineering microfluidic systems under the direction of Professor Aaron Streets at UC Berkeley, where he completed a Bachelor’s in bioengineering. He is now pursuing a PhD with the UC Berkeley-UCSF Graduate Program in Bioengineering, working in the lab of Professor Lydia Sohn, where his current projects focus on the design and development of new microfluidic platforms for single-cell mechanical phenotyping. The importance of cell biomechanics has garnered considerable attention as studies show the relevance of mechanical phenotypes in cell function, fate and disease. Consequently, it is necessary to have efficient, high-throughput systems capable of quantifying cellular biomechanics. Andre hopes to bring forth new label-free microfluidic platforms that could perform just that in order to create new tools for cancer diagnostics. Outside the lab, Andre loves to explore east bay on his bike, casually plays the piano, and enjoys dabbling in the kitchen.

Nathaniel Eli Tarshish

EPS; 2021 Guardian

Climate impact from mega plumes

Nathaniel is a graduate student studying the physics of climate in the Earth and Planetary Science department at UC Berkeley. Prior to graduate school, he earned a B.Sc. in Mathematical Physics from Brown University and investigated ocean fluid dynamics as a researcher in Princeton University’s Department of Geosciences. He has broad interests in understanding how the climate changes from human activity, including carbon emissions and nuclear war. He is researching if historical carbon emissions commit us to future warming, and if firestorms ignited by acts of nuclear war could trigger severe global cooling.

Amanda Katherine Glazer

Statistics; 2021 Guardian

Nonparametric statistical methods to improve societal bias

I am a fourth year PhD candidate in the Statistics department at UC Berkeley. My research focuses on causal inference with applications in education and political science. I earned my Bachelor’s degree in mathematics and statistics, with a secondary in computer science, from Harvard. At Berkeley, I am co-chair of the Statistics Graduate Student Association’s Diversity Committee, am a Union (UAW 2865) Departmental Steward, and have a monthly column in the Berkeley Science Review blog, “STEMinism in the Spotlight,” where I interview women in STEM fields at UC Berkeley. Outside of Berkeley, I enjoy seeing live music, baseball and crafting (knitting, crocheting and weaving).

Yi Chuan Lu

Physics; 2021 Explorer

Human survivability under climate heat change

I am a physics graduate student working on climate science. We try to answer the questions such as:

  1. When and where is the first place on Earth that will become uninhabitable with global warming?
  2. How much outdoor-activity time has to be reduced to protect human from heat stress?

Combining climate science and the existing study of human physiology, we hope to understand how human will be impacted in the future, and to give some guild to protect outdoor workers. We believe humanity can be supported by science!

Naomi Grace Asimow

EPS; 2021 Explorer

Urban air pollution

Naomi Asimow is a graduate student in Earth and Planetary Science interested in energy technology and policy to achieve equitable solutions to the climate crisis. Her research with Professor Ron Cohen focuses on source attribution of urban emissions by inverse modeling, with the goal of helping municipalities better understand their emissions and meet their climate and air quality goals. Naomi previously worked at the non-profit Strategic Energy Innovations (SEI). In this role, she tackled renewable energy solutions from varied angles: from working with government stakeholders on energy resilience solutions to developing curriculum on energy technology for high school and college students. As an undergraduate, Naomi researched porphyrin-catalyzed electrochemical reduction of carbon dioxide for energy and carbon storage.

Paul Nicknich

EPS Undergraduate; 2021 Explorer

Climate & atmospheric dynamics

Paul Nicknich graduated from UC Berkeley in spring of 2021 with a degree in applied mathematics with an emphasis in atmospheric science. What began as a casual interest in meteorology and snow forecasting has evolved into a passion for climate and atmospheric science and trying to understand the implications of a changing climate for our world. He is currently working with Professors Bill Boos and John Chiang doing research on tropical and extreme precipitation changes in a warmer climate. Outside of scientific work, Paul enjoys playing jazz and classical bass and spending time in the mountains skiing and running.

Shane Russett

EPS Undergraduate; 2021 Explorer

Reduce greenhouse gas emissions from farmland

I am a fourth year undergraduate studying Atmospheric Science. My research is in the field of biogeochemistry, and it concerns the ability of farmland to sequester greenhouse gases. I have applied ground rock (encouraging bicarbonate storage) and compost (allowing biomass growth) to the soil of Marin county farmland, and have been sampling soil in order to determine changes in the amount of soil carbon. I am hopeful that my research will provide farmers with a low-cost method to contribute to climate change mitigation

Andrew Shi

Mathematics; 2021 Explorer

Numerical methods for shock tracking

Andrew Shi is a PhD student in the department of mathematics. His research is in numerical methods for partial differential equations in the application area of computational fluid dynamics. In particular, his main project is on the subject of high-order shock tracking, which encompasses many fields in applied and computational mathematics such as numerical optimization and mesh generation. Prior to graduate school, he was a financial analyst in New York City. His Bachelor’s degree was also earned at UC Berkeley and he is originally from Dallas, TX.

Daria Balatsky

Physics; 2021 Explorer

MAX magnetic materials for electronic devices

As a physical chemistry graduate student, I am currently working on the growth and measurement of various materials. Of current interest is researching materials towards Maxtronics or magnetic MAX phases for spintronic applications. Materials of this group, have unknown mechanisms for electrical manipulation of the spin textures, which allows us to study their use in electronic applications while also facilitating a better understanding of the fundamental physics. The goal would be a device in which we can use the materials for information storage (similar to antiferromagnetic spintronic devices) that is more robust due to the remarkable physical properties of MAX materials.

Shannon Claire Haley

Physics; 2021 Explorer

Antiferromagnet material for data storage

I’m a condensed matter physicist studying weird magnets. On the physics side, I get to learn about what is going on inside of these magnets on a microscopic scale, and to see how interactions individual atoms have with one another translate into macroscopic properties. On the applied side, this work might factor into the next generation of spintronic devices, leading to faster and more efficient computing! A typical day for me involves melting elements together to form new magnets, cutting tiny patterns into crystals using a focused beam of ions, and painting conductive paths using an eyelash glued to a wooden stick.
shannon haley-Hearts to Humanity Eternal