Daniel Pedraza

Daniel Pedraza

Project Manager

Daniel Pedraza is an engineer, entrepreneur, and technologist from Mexico. He is passionate about leveraging technology at scale, has danced across several disciplines, and deeply relates to techno-optimist philosophies. Daniel is currently a Data Strategist at UNICEF. In addition, he recently co-founded Veilos, a deep-learning startup rethinking global insights for development & security. Daniel's energy is full of optimism and a youthful naïveté, however he is fully aware there are inherent risks with all new technology. He has spent time looking at the open challenges to harnessing technology for public good, previously serving the United Nations as Data Innovation Specialist at Global Pulse, an innovation initiative harnessing big data for sustainable development and humanitarian action. Daniel is most inspired by working on solutions to intractable challenges that face humanity. As a child Daniel dreamt of becoming an astronaut, leading him to study aerospace engineering, focusing on computational methods and aerodynamics. He never made it into space.

Dhaval Adjodah

Dhaval Adjodah

Machine Learning Engineer

Dhaval is a 4th year PhD student at the MIT Media Lab doing r esearch in AI, computational social science and finance. He previously worked in finance after doing his masters in the MIT Technology Policy Program, and undergraduate in Physics also at MIT. He is interested in understanding how to optimally organize networks of human and AI agents, and how large groups of people can sense new information, and take action collectively. His work is relevant to improving deep reinforcement learning algorithms, improving financial trading, rewiring collaboration networks, crowd-sourcing, voting, and innovation. He grew up in Mauritius, and greatly enjoys cooking and running.

Gretchen Greene

Gretchen Greene

Machine Learning Engineer

A former ship designer, national lab mathematician and Hollywood special effects artist, Gretchen Greene is a computer vision scientist and machine learning engineer working with Cambridge startups on everything from autonomous vehicles to QR codes in wearables. Also an attorney, Greene has worked on international energy, water and transportation policy, complex corporate tax transactions and criminal and civil litigation. Greene has a CPhil and MS in math from UCLA and a JD from Yale.

Josh Joseph

Josh Joseph

Machine Learning Engineer

Josh has over a decade of experience solving real-world problems using the tools of machine learning in both academia and industry. The majority of his past ML work has been in finance from time co-founding a fully-automated, proprietary trading company, as a machine learning consultant, and as Chief Science Officer at Alpha Features. In addition to a wide breadth of experience in strategy discovery and validation using structured and unstructured data sources, he has also performed technical due diligence on over a hundred AI/ML hedge funds for an asset allocator. As a consultant and during his time as a graduate student, he also worked on projects such as an autonomous cell identification system for a life sciences company, pricing of co-working office spaces, modeling iRobot Roomba battery degradation, predicting taxi routes, and autonomous robot interaction with turbulent water flow. He received a B.S. in Applied Mathematics and a B.S. in Mechanical Engineering from Rochester Institute of Technology and a S.M. and Ph.D. in Aeronautics and Astronautics from Massachusetts Institute of Technology.

Thom Miano

Thom Miano

Machine Learning Engineer

Thom Miano is a research data scientist in the Center for Data Science at RTI International. He is currently working on several deep learning projects in computer vision and multimodal sensing. Thom studies Artificial Intelligence as a multifaceted discipline, investigating the development of algorithmic architectures, the practical application of machine learning in health, education, and the arts, and the ethical implications of AI and data-driven technologies. Thom has a rich interdisciplinary background as an artist, musician, writer, and lecturer. He received an MS in Data Science and a BA in Political Philosophy, Policy, & Law from the University of Virginia.

Francisco

Francisco

Machine Learning Engineer

Francisco has a very eclectic background gained through his extensive international academic and professional career with studies in Spain, Sweden, Japan, Australia and USA. He also worked in Japan for 6 years developing a deep understanding of the business culture there, has been exposed to large international projects and has managed international teams. These days he is working in projects that touch very diverse fields like Data Science, AR/VR, Physics and cybersecurity. He is also an avid traveler and adventurer that so far have visited more than 60 countries across the globe.