Benjamin Thelonious Fels excels at leading the development of technology that learns in complex, real-world settings. Prior to starting Pendulum, he worked as a derivatives trader in Chicago and London, where he supervised quantitative, technological, and successful market teams that created and ran trading systems that learned in real-time in financial markets. Benjamin has advised the World Health Organization on AI and the Financial Times published his op-ed on AI and healthcare. Has been invited to speak on applied AI at the University of Washington and Northwestern University, to physician-scientists at Penn Medicine, and to clinical leaders in Alaska and Oregon.

Bereket is a Java, Spring Framework, and JavaScript expert with a passion for Microservices architecture and DevOps. He has extensive expertise developing corporate apps for the smart utilities, fintech, and healthcare industries. Bereket graduated from Addis Ababa Institute of Technology with a bachelor's degree in computer engineering. Bereket formerly worked as a Senior Software Developer at Paga Group Ltd. before joining Pendulum Systems.

Carl is a results-driven software engineer with a keen focus on leveraging data to solve complex problems. Holding a degree in Business Administration from Arizona State University's W.P. Carey School of Business, he possesses a unique blend of technical and business acumen. Throughout his career, Carl has excelled in roles spanning data analytics and data engineering within the non-profit, financial, and online retail sectors. His expertise in data-driven solutions has earned him a reputation for delivering exceptional results.

Drew Arenth has vast experience in supply chain modernization. Previously, he worked as a research consultant for Intellectual Ventures/Global Good and as a Principal at Providence Health and Services, where he was responsible for the design and implementation of strategic organizational projects. As Director of International Business Development at Foss Maritime, Drew guided negotiations with the largest organizations in the world and was a founding board member of the business development board for Saltchuk Resources, Inc., a multi-billion dollar privately held logistics company.

Eva is a highly-driven, innovative thinker, active collaborator and problem-solver who has spent her early career developing and implementing systems and processes for operational efficiencies. She is exceptionally skilled at providing cross-functional team coordination. Prior to joining Pendulum Systems, she worked as an Associate at a real estate consulting firm focused on new development residential real estate primarily in New York City.

Fernando Gama has received a Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania (2020), and an M.A. in Statistics from the Wharton School (2017). He had postdoctoral stints in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley (2020-21), and the Electrical and Computer Engineering department at Rice University (2021-22). He has also been a research intern at Facebook Artificial Intelligence Research in Montréal (2018), and a visiting scholar at TU Delft in the Netherlands (2017). Before joining Pendulum, he worked as a Machine Learning Researcher at Morgan Stanley (2022-23). The core of his published research is related to machine learning and signal processing for graph-structured data, with applications in power grids, sensor networks, multi-agent robotics, and distributed control. He has a background in statistics, time series analysis, and signal processing.

Fin is a communications specialist adept in building brand identity through digital content. He joins Pendulum from Palantir Technologies, where he facilitated strategic communications efforts across the commercial business. Prior to entering into data and analytics, Fin trained and worked as a journalist, writing for news outlets including the Times and the Telegraph. He has an MA in the field, alongside an undergraduate degree from the University of Oxford.

Hamsa Bastani is an Associate Professor of Operations, Information, and Decisions at the University of Pennsylvania's Wharton School. Her research is focused on the development of unique machine learning algorithms for data-driven decision-making, with applications in healthcare operations, social good, and revenue management. Her work has earned her the Wagner Prize for Excellence in Practice (2021), the Pierskalla Award for the best paper in healthcare (2016, 2019, 2021), the Behavioral OM Best Paper Award (2021). She completed her PhD in Stanford's Electrical Engineering department under the supervision of Mohsen Bayati. She graduated summa cum laude from Harvard in 2012 with a A.M. in physics, and a A.B. in physics and mathematics.

Jeni is a global development expert with a career that spans national health, defense, and information technology industries. She has spent over a decade deploying strategic innovations to varying political and social environments across industries to ensure service delivery is efficient, effective, and accepted. She brings a broad perspective on human behavior and experience to her work, and challenges the status quo to adapt where possible and to change meaningfully where inevitable. Her wide interests have helped her develop deep technical and operational knowledge across whole systems.

With over two decades of experience ranging from tactical to strategic, Jim's work prototyping, testing, and implementing cutting-edge technology on behalf of the US Government has taken him across six continents, from the Arctic Circle's outskirts to the South Pole and everywhere in between. His background in cooperatively designing unique technical solutions was honed at DARPA, the Multi-National Corps - Iraq, US Forces - Afghanistan, the Army Engineer Research and Development Center, as a liaison to the US TENTH Fleet, and a variety of other government agencies.

LTG (R) Ostrowski is a well-known figure on Capitol Hill, with extensive experience in Congressional and Government relations. He has a strong background in federal acquisition and contracting strategies, as well as strategic planning for major defense research, development, test, evaluation, and procurement programs. Notably, he served as the Deputy Chief Operating Officer and Director of Supply, Production, and Distribution for Operation Warp Speed/Countermeasures Acceleration Group, playing a critical role in managing efforts related to pandemic response. LTG (R) Ostrowski graduated from the United States Military Academy at West Point and holds a Master of Science in Systems Acquisition Management from the Naval Postgraduate School, as well as a Master of Science in National Resource Strategy from the Industrial College of the Armed Forces/ Eisenhower School.

Laila is an Android developer with more than a decade of experience designing, implementing, and supporting creative solutions across several domains such as smart home, IoT, cloud, and healthcare. She holds a degree in Informatics and Linguistics and is passionate about developing user-friendly software that improves people's lives and experiences.

Lester is a Stanford University adjunct professor and a Microsoft Research New England statistical machine learning researcher. Before joining Microsoft, he was an assistant professor of statistics and, by extension, computer science at Stanford for three years. His current research interests include statistical machine learning, scalable algorithms, high-dimensional statistics, approximation inference, and probability. He received his Ph.D. in Computer Science (2012) and M.A. in Statistics (2011) from UC Berkeley and my B.S.E. in Computer Science (2007) from Princeton University. His Ph.D. advisor was Mike Jordan. As an undergraduate at Princeton, Lester’s team was ranked second for the legendary $1M Netflix Prize, competing against 2000 of the world’s best forecasters.

Professor Marc Deisenroth is the DeepMind Chair in Artificial Intelligence and the Deputy Director of UCL's AI Centre. He also holds visiting faculty positions at the University of Johannesburg and Imperial College London. Marc leads the Statistical Machine Learning Group at UCL. His research interests center around data-efficient machine learning, probabilistic modeling and autonomous decision making with applications in climate/weather science and robotics.

Martin is a Managing Partner at Fine Capital Partners, a hedge fund based in New York City. He is the Chair of IDEO.org's Board of Directors and the Board Treasurer of Population Services International (PSI). He is the Founder and former President of Health Pages, a consumer website devoted to providing consumers with background, experience, and quality information about health care providers. He is also the Founder and former President of Physician Hospital Alliance, a company that provided out-patient medical services. He received a BA from Amherst College, an MBA from the University of Chicago, and a MSc from The London School of Economics.

Mesay is highly skilled in image processing techniques aimed at establishing resilient and streamlined supply chain systems. He holds a Ph.D. in Information and Communication Technology from the University of Trento, Italy. His research is primarily centered around the application of cutting-edge technologies such as Generative Adversarial Networks (GANs) and domain adaptation methods, specifically for the classification of multispectral/hyperspectral images. With a wealth of experience, Mesay has played a crucial role in the development of sophisticated deep learning models tailored for the analysis of remote sensing images.

Misha Sra is the John and Eileen Gerngross Assistant Professor in the Computer Science department at the University of California Santa Barbara where she directs the Perceptual Engineering Lab. She is a member of UCSB’s Center for Responsible Machine Learning (CRML) and Center for Interactive and Visual Computing (CIVC). She received her PhD from the MIT Media Lab and her current research focus is on using AI for Good.

Stefanie is an Associate Professor at MIT EECS, and a member of CSAIL, IDSS, the Center for Statistics and Machine Learning at MIT. She is also affiliated with the ORC. Her research focuses on algorithmic machine learning, which spans modeling, optimization approaches, theory, and applications. Her work has been supported by a Sloan Research Fellowship, an NSF CAREER Award, a DARPA Young Faculty Award, an NSF BIGDATA award, an ONR MURI, Google, Two Sigma, and Adobe faculty research awards, an STL award, and other awards by NSF and DARPA. Stefanie has received Germany's highest academic honor, the €5 million Alexander von Humboldt Prize for Artificial Intelligence.

Stephen has extensive expertise in augmented reality solutions for the US government. He received his PhD from the Massachusetts Institute of Technology's (MIT) Department of Electrical Engineering and Computer Science (EECS), where his research focused on semiconductor devices and solid state physics. Akintunde Ibitayo Akinwande served as Stephen's advisor, and his work was highlighted at the International Electron Device Meeting (IEDM).

Suvrit Sra, Ph.D., is a large-scale machine learning and optimization expert. He is an MIT Career Development Associate Professor of Electrical Engineering and Computer Science and an MIT Institute for Data, Systems, and Society member. Suvrit is the author of multiple peer-reviewed papers in machine learning, data mining, statistics, optimization, and mathematics, and the editor of Optimization for Machine Learning (MIT Press). Additionally, he has been awarded and recognized by major institutions such as the National Science Foundation, NSF BIGDATA, and NSF TRIPODS+X grants, for his contributions to the advancement of ML in the real world.