Fellowship class of 2020

The Foresight Fellowship is an exclusive one year supportive program committed to giving change-makers the support and mentorship to accelerate their bold ideas into the future.

Our mission is to catalyze collaboration among leading young scientists, engineers, and innovators who are working on emerging new technologies that have the power to transform society. Since 1993 Foresight Institute has been rewarding those who are making strides in the field of Nanotechnology with the Feynman Prize. In 2016, one of our former Feynman Prize winners, Sir J. Fraser Stoddart, was awarded the Nobel Prize in Chemistry for his work with molecular machines. Foresight Institute recognizes that providing a strong network and knowledge base for new fellows to access will accelerate their missions and reflect our goals to further support those making important strides in a variety of fields.

During the 1 year program, Fellows will be invited to engage in events, connect to fellows and mentors, and increase their skills to succeed with their endeavors. See our 2020 Fellows in action.


Felix Andreas Faber

2020 Foresight Fellow in Machine Learning accelerated Drug- and Materials discovery

I received a B.Sc. and a M.Sc. in physics at Linköping University in Sweden, followed by a Ph.D. in chemistry at the University of Basel.  My master’s thesis, which was later published in the International Journal of Quantum Chemistry, was one of the first works that demonstrated successful learning of crystal formation energies.

In my Ph.D. I developed machine learning techniques for modeling fundamental quantum mechanical properties.  Such properties include energies, forces, and dipole moments of crystals and molecules. In one of my first Ph.D. projects, which was published in Physical Review Letters, we used a machine learning model to predict formation energies of almost 2 million Elpasolite crystal structures. We also used this model to identify around 90 potentially thermodynamically stable structures.I was also among those who pioneered the use of quantum mechanical operators directly on machine learning models, which results in improved performance and is a stepping stone towards universal machine learning modeling of quantum mechanical properties.

Additionally, I dedicated parts of my Ph.D. to benchmarking and comparing the performance of different machine learning models. In one such example we, in collaboration with scientists from google, performed one of the most comprehensive comparisons of different machine learning models to date.

I envision a research framework where these techniques could be harnessed to understand and model biological and materials systems of varying complexity. Such fundamental models could be used to develop therapeutics, as well as new materials tailored for exhibiting specific properties. To those ends, I recently started a postdoctoral fellowship at the University of Cambridge, where applying the models that I developed during my Ph.D. to discover new drugs and materials.

Matthew R Ryder

2020 Foresight Fellow in Molecular-Scale Engineering

Originally from the Shetland Islands in the North of Scotland, Matthew graduated with First Class Honors in Chemistry with Computational Chemistry (M.Chem.) from Heriot-Watt University in Edinburgh. He then completed his graduate studies (D.Phil.) at the University of Oxford before being awarded an EPSRC Doctoral Prize Fellowship to continue his research at the University of Oxford. He was recruited soon after by the U.S. Department of Energy to work at Oak Ridge National Laboratory (ORNL) as the “youngest person ever to be offered the prestigious Clifford G. Shull Fellowship.” He has published 28 research papers and been awarded numerous prizes, including being named “one of the most promising scientists in the U.K..”

Matthew’s research focuses on understanding materials at the molecular level using quantum mechanics in conjunction with synchrotron and neutron experiments. His work aims to reveal the structural possibilities of next-generation porous materials and explain the fundamental mechanisms responsible for anomalous behavior. He sits on the editorial boards of two journals, and was the co-editor of a special issue on ‘Computers in Neutron Science.’ He is the lead principal investigator (PI) on multiple projects involving highly porous materials and Co-PI of a multidisciplinary project recently awarded $1.45M to tackle waste plastics by upcycling to performance-advantaged polymers.

Daniel Bojar

2020 Foresight Fellow in Health & Longevity

Daniel’s background in structural biology, strengthened by a B.Sc. in biochemistry (University of Tuebingen, Germany, 2014) and a M.Sc. in biophysics (ETH Zurich, Switzerland, 2016) with distinction, enabled him to understand biological processes down to the atomic level. During his doctoral work with Dr. Martin Fussenegger at ETH Zurich, Daniel employed these fundamental insights to genetically re-engineer human cells for therapeutic purposes. Creatively using the principles of synthetic biology, he designed new proteins with a dedicated function – such as a novel caffeine receptor – and used these intricate tools to develop potent new cell-based therapies for diabetes mellitus and Parkinson’s disease. Further, Daniel was distinguished by several prestigious fellowships, such as the Excellence Scholarship and Opportunity Program of ETH Zurich and by the German Academic Scholarship Foundation, as well as in the form of a Selected Young Scientist at the 68th Lindau Nobel Laureate Meeting, an honor extended to the 600 most promising biomedical scientists worldwide. As a postdoctoral fellow with Dr. James J. Collins at the Wyss Institute for Biologically Inspired Engineering at Harvard University, Daniel harnesses the potency of cutting edge machine learning techniques to elucidate the biological functions of glycans since September 2019. Often described as the “third language of life” after DNA and proteins, glycans are by far the most complex and plastic biopolymer in humans. While these macromolecules are crucial to every human disease, glycobiology is still a predominantly experimental, and severely neglected, area of research. Daniel was the first researcher to devise, develop, and apply methods derived from artificial intelligence to glycans and begin to tame their astounding complexity. His research could therefore pave the way for exciting new insights and novel therapies for grueling human diseases.

In 2020, Daniel, was selected to be part of the prestigious Branco Weiss Fellowship – Society in Science 2020 Fellows, and as such was awarded $106,000 annually for five years to work on connecting machine learning and glycobiology, towards unveiling the inner workings of biology and facilitating biomedical therapies of tomorrow.

Giuliana Rotola

2020 Foresight Fellow in Space Studies

Giuliana holds a joint bachelor and master’s degree from the University of Trento in Comparative, European and Transnational Law. During her studies, she was a research intern in the European Centre for Space Law (ECSL – ESA), and she conducted independent researches in the Institut du Droit de l’Espace et des Télécommunications (IDEST) for her final dissertation on militarization, weaponization and the prevention of an arms race in outer space. In September 2018, Giuliana attended the 27th Summer Course in Space Law and Policy organized by ECSL. In February 2019, she joined the Leuven Centre for Global Governance Studies as a research intern. There, she worked, among the others, on publications on Space Archaeology, and space contribution to the UN SDGs. During the ECSL Young Lawyers’ Symposium 2019, she presented her work on the protection of cultural heritage sites on the Moon. She later contributed to the creation of the first digital registry of items on the Moon, with For All Moonkind. Moreover, her research on the relation between SDG 6 – Clean water and sanitation and space technologies was presented as a Conference Room Paper at the 62nd session of COPUOS within the framework of the “Space for Youth Competition“.

From September 2019, Giuliana is taking a Master of Space Studies at the International Space University. There, she is carrying out a team project on the Search for Extraterrestrial Intelligence, and an individual research project on the collection of genetic data and human genetic engineering in the space realm.

Caroline Jeanmaire

2020 Foresight Fellow in Artificial Intelligence Governance

Caroline researches international coordination models to ensure the safety and reliability of Artificial Intelligence systems at UC Berkeley Center for Human-Compatible AI (CHAI). She also leads CHAI’s partnership and external relations strategy, focusing on building a research community around AI safety and relationships with key stakeholders. Before working at CHAI, she was an AI Policy Researcher and Project Manager at The Future Society, a think-tank incubated at Harvard’s Kennedy School of Government. She notably supported the organization of the first and second Global Governance of AI Forums at the World Government Summit in Dubai. In the 2019 edition, she managed two committees: Geopolitics of AI and International Panel on AI research. She published articles and reports on the Geopolitics of AI, US-China industry levers of cooperation on AI and the results of a global civic debate on AI governance. Before this, she participated in numerous climate negotiations and technical intersessions since 2015, including with the French Delegation for COP23 and COP24. Caroline speaks English, French, Spanish and Mandarin Chinese. She has a Master’s degree in International Relations from Peking University and a Master’s degree in International Public Management from Sciences Po Paris. She received her Bachelor’s degree in political sciences from Sciences Po Paris. She also studied at the Graduate Fletcher School of Law and Diplomacy and at Tufts

Daniel Elton

2020 Foresight Fellow in Artificial Intelligence

Daniel Elton is a Staff Scientist at the National Institutes of Health Clinical Center working on applications of artificial intelligence to medical imaging. Much of his recent work is on improving automated measurements in CT and MRI scans using deep learning. He also works on theoretical issues surrounding robustness, explainability, and transparency.  While his work mainly touches on issues relevant to near-term AI safety, he maintains an interest in long term AI safety research and existential risk reduction more generally.  

Originally from a small town in upstate New York, he received a bachelor’s degree physics from Rensselaer Polytechnic Institute in 2010 and earned a Ph.D. in physics from Stony Brook University in 2016. During postdoctoral work at the University of Maryland he worked on deep learning for molecular property prediction, generative AI models for molecular design, and applications of natural language processing to the chemical domain




Alevtina Evgrafova

2020 Foresight Fellow in Sustainable Agriculture

Dr. Alevtina Evgrafova is a PostDoc at the Leibniz Centre for Agricultural Landscape Research in Germany. Her research focuses on future integrated scenarios of soil management for sustainability impact assessment. Alevtina is particularly working on the development of participatory transdisciplinary science-driven scenarios of soil management at the German national level within the BonaRes initiative. Her interests encompass a range of different topics such as sustainable land management, policy-making, urban and rural development, environmental impact assessment as well as technologies & innovations. During her involvement in both academic and industrial projects, Alevtina has been actively encouraging the support for early-career researchers and international cooperation.   

Alevtina is originally from Russia, where she obtained her double Diploma (with honors) in Soil Science (MSc) and Pedagogy (MA) from Lomonosov Moscow State University. Afterwards, she obtained a joint MSc in Environmental Protection and Agricultural Food Production from Wageningen University, Netherlands and University of Hohenheim, Germany in 2013. Recently, Alevtina has completed her PhD in Geography (magna cum laude) with the focus on permafrost-affected soils from University of Bern, Switzerland.

Tony Lai

2020 Foresight Fellow in Legal Engineering for the Biosphere

Tony Lai is a Fellow and Chair of the Blockchain Working Group at CodeX, the Stanford Center for Legal Informatics; a Senior Research Fellow at the National University of Singapore’s Center for Technology, Robotics, AI, and the Law; and a founding Editor of the Stanford Journal on Blockchain Law and Policy, and of the MIT Computational Law Report. Tony runs world-building experiments focused on legal engineering, convening interdisciplinary academic, governmental, and professional collaborations to test and deploy models of interoperable governance.

Jeffrey Ladish

2020 Foresight Fellow in Biosecurity

Jeffrey is a security and research consultant focused on addressing systemic risks from emerging technologies. His research areas include nuclear proliferation and deterrence, engineered organisms, and frameworks for international cooperation. With a background in evolutionary theory and information security, Jeffrey believes personal bios are not to be trusted.

Tessa Alexanian

2020 Foresight Fellow in Responsible Biotechnology

Tessa Alexanian spends her weekdays wrangling robots to accelerate biological engineering and her evenings trying to make sure biologists engineer the right things.

She has been organizing biosecurity events in the San Francisco bay area since 2018, first as a founder of East Bay Biosecurity Group and recently as the instigator of the Catalyst collaborative biosecurity summit.

She is a member of two of the organizing committees for iGEM, an international synthetic biology competition that brings together thousands of students from dozens of countries each year. The Safety and Security committee reviews risk assessments submitted by iGEM teams, while the Human Practices committee nudges students to consider the broad impacts of their projects through ethical analyses, stakeholder interviews, and other public engagement.

Tessa has recently begun volunteering with a team working on privacy-preserving contact tracing for COVID-19.