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
CEO and Founder
Tomasz recognized that businesses often overlooked or under tapped the value of their data, leading to underperformance. He realized that Artificial Intelligence and Machine Learning offered opportunities for businesses to turn data into impactful, actionable insights that would deliver significantly improved performance. For this purpose he founded Teranalytics, his third startup, to solve complex business problems with custom algorithms, delighting his clients. Prior to Teranalytics, Tomasz co-founded NutriCount, Inc., an award-winning health analytics company that helped health organizations monitor patients and drive balanced nutrition. Before NutriCount, Tomasz was a Chief Scientist at BAE Systems, where he teamed with IARPA on data gathering and processing for Over the Horizon Radar systems. Prior to BAE, Tomasz founded Delpsi LLC, a medical microwave imaging company. His collaboration with Dartmouth College and the South Korean Electronics and Telecommunications Research Institute 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 ordnances.
Joe Pacheco
VP, Data Science and Analytics
Joe Pacheco
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
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
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
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.
Dominik Sepiolo
Data Scientist
Dominik Sepiolo
Data Scientist
Dominik Sepiolo (MS) received his master degree in computer science from the AGH University of Science and Technology, with a specialization in Intelligent Systems. He joined ABB Software Development Center where he worked on electricity market modeling using machine learning and statistical techniques. He later joined Teranalytics where he has been working on demand forecasting using time series analysis, data visualization, and process optimization. He is currently pursuing his PhD in Explainable Artificial Intelligence.
Daniel Contreras
Data Engineer
Daniel Contreras
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.
