Industrial machine learning software

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Our mission at Fero Labs is to bring actionable machine learning to the industrial sector. We believe that factories around the world can use machine learning to optimize production, reduce waste, and improve quality. We are building Fero to support the next leap in industrial productivity.

Berk Birand


Chief Executive Officer

Berk holds a Ph.D. in electrical engineering and computer science from Columbia University. His academic research focused on optimizing wireless and optical networks with efficient cross-layer algorithms. He developed scheduling algorithms for LTE-A and fiber-optic networks. He holds a patent in IoT systems for resilient fiber-optic networks.

Alp Kucukelbir


Chief Scientist

Alp is an expert in machine learning and probabilistic programming. He has published multiple papers with David Blei and Andrew Gelman. He is also an adjunct professor of computer science at Columbia University. Alp received his Ph.D. from Yale University, where he won the best thesis award.

Pamir Ozbay

Head of Operations

Pamir has worked as a strategy consultant and sales engineer for industry leaders including Toshiba-Mitsubishi-General Electric and Siemens. He has extensive international experience supporting customers in the metals, paper, mining, oil and gas, renewables, logistics, and transportation industries. Pamir holds an MBA from the London Business School and an M.S. in electrical engineering from Columbia University.

Todd Gardner

Head of Engineering

Todd is a veteran software engineer with experience leading companies from their early stage to acquisitions by sector giants, such as Dropbox. He previously led infrastructure teams at Google, where he was responsible for managing big data storage. Todd is excited about the application of machine learning in industrial IoT.

Matthew Henderson

Director of Sales

Matt is a seasoned software and technology sales executive having helped some of the technology sector's most recognizable brands grow their bottom line. Most recently, Matt spent the last 5+ years at Greenhouse Software as the company’s first sale hire and where he helped grow the business to over 400 employees and $70 million in revenue. He believes the industrial sector is ripe for innovation and is excited to see how machine learning technology will impact the way companies operate. Matt is also a die-hard fan of Manchester United.

Tim Eschert

Business Operations Lead, EMEA

Tim has extensive experience in the automotive and robotics sector, ranging from startups to Fortune 20 companies. He holds a joint Bachelors and Masters degree in mechanical engineering and business administration from RWTH Aachen University. He is also a lecturer in Industrie 4.0 and the application of machine learning to this field.

William Brinkerhoff

Senior Software Engineer

Will is a senior software engineer with over a decade of experience working with data in organizations ranging from small startups to the US government. During this time he has created tools to make data in fields as diverse as signals intelligence, finance, and network security understandable and useful. He is looking forward to applying this expertise to industrial processes and machine learning.

Theodore Brundage

Senior Software Engineer

Ted is a senior software engineer with experience building clean engineering solutions to support explicable data models for machine learning systems in the financial and data sectors. Ted received a M.S.E. in Computer Science researching sparse Bayesian regression and an A.B. in Physics researching experimental quantum computing from Princeton University.

Paris Leach

Software Engineer

Paris is a software engineer at Fero Labs, where they implement new features and are constantly working with the team to improve Fero. They were previously at Blizzard Entertainment, where they gained experience in both writing tests and lending design insight so as to improve the experience of products for users. At Fero, they are able to fully actualize on their passion for creating intuitive tools to process, analyze and manage data.

David Blei

Professor of Computer Science and Statistics at Columbia University

Noah Goodman

Professor of Computer Science and Psychology at Stanford University

Chris Wiggins

Associate Professor of Applied Mathematics and Statistics at Columbia University

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