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SAN MATEO, Calif.--(BUSINESS WIRE)-- Roblox Corporation (NYSE: RBLX), a global platform bringing millions of people together through shared experiences, released its first quarter 2022 financial results today and separately posted a letter to shareholders and supplemental materials on the Roblox investor relations website at ir.roblox.com.

Roblox will host a live Q&A session to answer questions regarding their first quarter 2022 results on Wednesday, May 11, 2022 at 5:30 a.m. Pacific Time. The webcast will be open to the public at ir.roblox.com or by clicking here.

The forward-looking statements included in this press release represent our views as of the date of this press release. We anticipate that subsequent events and developments will cause our views to change. We undertake no intention or obligation to update or revise any forward-looking statements, whether as a result of new information, future events or otherwise. These forward-looking statements should not be relied upon as representing our views as of any date subsequent to the date of this press release. Past performance is not necessarily indicative of future results.

Bookings is defined as revenue plus the change in deferred revenue during the period and other non-cash adjustments. Bookings is equal to the amount of virtual currency purchased by users in a given period of measurement. We believe bookings provide a timelier indication of trends in our operating results that are not necessarily reflected in our revenue as a result of the fact that we recognize the majority of revenue over the estimated average lifetime of a paying user. The change in deferred revenue constitutes the vast majority of the reconciling difference from revenue to bookings. By removing these non-cash adjustments, we are able to measure and monitor our business performance based on the timing of actual transactions with our users and the cash that is generated from these transactions. Free cash flow represents the net cash provided by operating activities less purchases of property, equipment, and intangible assets. We believe that free cash flow is a useful indicator of our unit economics and liquidity that provides information to management and investors about the amount of cash generated from our core operations that, after the purchases of property, equipment, and intangible assets, can be used for strategic initiatives, including investing in our business, making strategic acquisitions, and strengthening our balance sheet. Adjusted EBITDA is a measure of operating performance used in certain covenant calculations specified in the indenture governing our senior notes due 2030 that is not calculated in accordance with GAAP and may not conform to the calculation of EBITDA in other circumstances. Adjusted EBITDA should not be considered as a substitute for net loss as determined in accordance with GAAP. We believe that, when considered together with reported amounts, Adjusted EBITDA is useful to investors and management in understanding our ongoing operations and ongoing operating trends for purposes of analyzing the covenants specified in the indenture governing our senior notes due 2030.

A reconciliation table of the most comparable GAAP financial measure to each non-GAAP financial measure used in this press release is included at the end of this release. We encourage investors and others to review our business, results of operations, and financial information in their entirety, not to rely on any single financial measure, and to view these non-GAAP measures in conjunction with the most directly comparable GAAP financial measure.

The Roblox Research scientists publish findings in academic conferences, release open source and data, collaborate with universities, and bootstrap transferring results into production. Here are the team members responsible for that innovation.

He was a faculty member for twenty years, most recently as a full professor leading the Visual Computing Division of the School of Computing at Clemson University, where he continues to hold an adjunct research faculty member position. He received his PhD in Computer Science from the Georgia Institute of Technology.

Maneesh received an Okawa Foundation Research Grant in 2006, an Alfred P. Sloan Foundation Fellowship and an NSF CAREER Award in 2007, a SIGGRAPH Significant New Researcher Award in 2008, and a MacArthur Foundation Fellowship in 2009. He is an associate editor of ACM Transaction on Graphics as well as an advisor for the Human Computation Journal.

Prof. Guha has broad interests in programming languages and systems and researches problems that arise in web security, software-defined networking, distributed systems, and robotics. At Roblox, Arjun is working to make the platform dramatically more scalable and easier to program.

Prof. Phan works on real-time systems, cyber-physical systems and distributed systems. Her research focuses on theoretical foundations and systems techniques for building efficient large-scale systems with guaranteed performance, fault tolerance, safety and security. Her recent work includes real-time clouds, real-time resource allocations, compositional scheduling, timing-aware fault-tolerance, and methods for defending distributed systems against DDoS and Byzantine attacks.

Sheldon is currently a professor of Software and IT Engineering at the École de technologie supérieure (Université du Québec) in Montreal, Canada. He received his Ph.D. in Computer Science in 2015 from McGill University under the supervision of Paul Kry, and later was a postdoctoral researcher at Disney Research (2014-2015) and CM Labs Simulations (2016).

Dr. Lorido-Botrán is currently a Research Scientist at Roblox. Prior to that, she worked at Microsoft and the Pacific Northwest National Laboratory. Her research interests lie across machine learning, systems, and optimization.

Derek obtained his PhD at the University of Toronto, partially supported by an Adobe Research Fellowship. During his PhD studies, he interned at Adobe Research and NVIDIA Toronto AI lab. He was a visiting scholar at École Polytechnique in France and a consultant at Urus Entertainment. Previously, he received his MS from Carnegie Mellon University and BS from National Taiwan University.

Tony Liu researches mental wellness, healthcare, and digital civility by combining techniques from causal inference and machine learning. He previously worked at IBM Watson Health and has published in Nature Computational Science as well as ICML and AAAI workshops. He coordinates academic collaboration, technology transfer, and external communication for Roblox Research.

Mitesh Shah is the Senior Director of Programming Languages for the Game Engine product and directly manages research and development of languages and programming models that power the creation of millions of experiences on Roblox. Previously, he built and led high-performance R&D teams at Meta, Synopsys, and start-ups delivering state-of-the-art solutions in the PL domain. Throughout his career, Mitesh developed compilers and programming models for a vast variety of processor architectures including massively parallel processors, network processors, highly embedded RISCs, Vector DSPs, VLIW machines, and neural network ML accelerators.

Mitesh holds an MS in computer science from Texas A&M University and his research interests include parallelizing compilers and processor architecture, along with exploiting perf, efficiency, reliability, and security through PL and runtime.

Alan has over 30 years of experience with research in programming languages, including publishing papers and serving on the program committees of Principles Of Programming Languages (POPL), International Conference On Functional Programming (ICFP), and Logic In Computer Science (LICS). He has served on the Steering Committee and Organizing Committee of ICFP, and as General Chair of LICS. He has been an active member of open source software projects such as LaTeX, Agda, Servo, and Luau.

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