Our Mission is Simple:
We help clients measurably improve their
business processes, decisions, and outcomes
Founded by MIT Data Scientists in 2016, we at Teranalytics developed and refined the science of applying AI and machine learning to solve complex business challenges. We have applied our proven methodolgies to a wide spectrum of applications, spanning process optimization, dynamic forecasting, supply chain, logistics, product development, and more. Our unique approach of coupling business analysis, data modeling, and bespoke AI algorithms consistently delivers exceptional results to our clients.
Meet Our Data Scientists
Tomasz M. Grzegorczyk
CEO and Founder
Tomasz M. Grzegorczyk (PhD, MBA)
CEO and Founder
Tomasz M. Grzegorczyk received his Ph.D. from the Swiss Federal Institute of Technology in Electrical Engineering (2000), and his MBA from the Massachusetts Institute of Technology (2016). From 2001 to 2008 he was with the Research Laboratory of Electronics, Massachusetts Institute of Technology, where he developed several optimization algorithms to simulate the propagation of electromagnetic waves in complex media. During this tenure he co-authored more than 100 peer reviewed papers, supervised more than 10 PhD and Master theses, and co-authored a book on the physics and application of metamaterials. He subsequently joined BAE Systems as Chief Scientist where he worked on data analysis and optimization algorithms for remote sensing applications.
Throughout his career, Tomasz used and developed algorithms to solve complex problems using large amounts of data. This led him to realize that companies often overlook or under tap the value of their data, leading to underperformance. Knowing that Artificial Intelligence and Machine Learning offer opportunities for businesses to turn data into impactful, actionable insights that can deliver significantly improved performance, he founded Teranalytics, his third startup. Currently Teranalytics solves complex business problems with custom algorithms, delighting its customers. Prior to Teranalytics, Tomasz co-founded NutriCount, Inc., an award-winning health analytics company that helped health organizations monitor patients and drive balanced nutrition, and founded Delpsi LLC, a medical microwave imaging company. His collaboration with Dartmouth College led to the fastest 3D microwave imaging system, delivering results in under 10 minutes compared with 10 hours for competing products. Delpsi also worked with the US Government to improve detection of unexploded ordnance.
Joe Pacheco
VP, Data Science and Analytics
Joe Pacheco (PhD)
VP, Data Science and Analytics
From 2004 to 2013, he was a member of the Technical Staff in the Advanced Capabilities and Systems group at MIT Lincoln Laboratory where he led the development of several novel sensor technologies for tactical situation awareness. His contributions spanned all phases of the development from system analysis to simulation and modeling to implementation. He also led several test campaigns where he coordinated the efforts of multiple teams from MIT Lincoln Laboratory as well as government and industry partners. Several of the technologies he developed were successfully deployed and officially recognized as significant contributions by the corresponding government partners.
In 2014, he co-founded Netra Health LLC, a company dedicated to developing data analytics-based solutions for health and well-being applications. The company was founded by a team of physicians, scientists, engineers, and business strategists to leverage advancing mobile and wearable technology to fulfill unmet needs in an evolving healthcare system. Currently, he is leading several efforts related to the use of data analytics to increase the independence and well-being of individuals with chronic diseases.
Since 2016, he has worked with Teranalytics as a consultant leveraging his experience in translating state of the art AI and machine learning approaches to help corporations across a variety of industries such as retail, pharma, healthcare, IT, and service optimize their operations and business decisions. Within those industries, applications have included forecasting, ROI estimation, revenue management, customer segmentation, and predictive estimation.
Saul Salinas
Senior Data Scientist
Saul Salinas (MS)
Senior Data Scientist
Saúl Salinas Treviño (MS) received a double master degree in engineering physics and renewable energy from Monterrey Institute of Technology (ITESM). His initial work focused on computational physics applied to photovoltaic systems and wind resource assessment, where he developed a framework to analyze the performance of hybrid solar collectors (PVT). He joined Teranalytics where he has been working on distribution network optimization with major impact on ground logistics, demand forecasting using time series and machine learning analysis, and mathematical optimization of manufacturing processes.
Piotr Ciolek
Data Scientist
Piotr Ciolek (MS)
Data Scientist
Piotr Ciołek (MS) received his master degree in mathematics with high honors from the Wrocław University of Science and Technology, Poland. He started his career as data scientist working for Datarino startup company where he focused on analyzing mobile users geospatial data and creating foot traffic models. In 2019 he became Data Science Project Manager, working on models and products development supporting data migration and tools management processes. In 2020 he joined Teranalytics where he has been focusing on distribution network optimization, routing optimization, and scheduling.
Dariusz Komosiński
Data Scientist
Dariusz Komosiński (MS)
Data Scientist
Dariusz Komosiński (MS) received his master degree in mathematics with high honors from the Warsaw University of Technology, Poland. He joined Ionair where he worked as data scientist assessing air quality parameters using ML techniques. He developed several tools in R/Python that were used by the team to predict bacteria concentration in the room air and to estimate energy consumption of HVAC installations. He also developed optimization algorithms for system configuration. He joined Teranalytics where he has been working on mathematical optimization of manufacturing processes. His interests include explainable AI, data visualization, and linguistic.
Michał Maciąg
Data Scientist
Michał Maciąg (MS)
Data Scientist
Michał Maciąg (MS) received his master’s degree in mathematics with high honors from the Warsaw University of Technology in Poland. His work focused on numerical simulations of electronic circuits and data interpretation. He subsequently joined EurosEnergy as a junior data scientist, where he developed predictive maintenance models for heat pumps based on telemetry data. In 2021, he joined Teranalytics where he has been working on machine learning and optimization algorithms for logistics applications, network optimization, and forecasting. His interests include AI, physics and astronomy.
Daniel Contreras
Data Engineer
Daniel Contreras (MS)
Data Engineer
Daniel Contreras (MS) received his master’s degree in Management Information Systems with a focus on Business Analytics from the Oklahoma State University. He is an experienced agile coach and software engineer with experience in projects related to data visualization, data analysis, user experience design, and mobile and web development. In 2020, he joined Teranalytics as a data engineer where he has been working on front end development and customer-facing applications.
