About Us

No matter where you are in your development, Mobius Logic delivers the AI ideas, innovation, and expertise that enables your fast growing company to create profitable, compliant, cloud based, systems and products around your data.

 

Founded on the love of solving complex problems, Mobius Logic’s team delivers the AI expertise that create profitable, compliant, cloud-based systems and products around your data. Whether you want to identify patterns of behavior that impact pandemics, route your drones responsibly, eliminate loss in financial transactions or reduce violence in disadvantaged communities, Mobius Logic’s team provides the needed ideas, innovation, and expertise.

 

A provider of solutions and products across 5 key industries, Mobius Logic continually explores and expands its understanding of how data and AI can solve the most pressing problems and create the greatest opportunities in finance, life sciences, litigation, government, software and manufacturing, and in our day to day lives.

 

For more information about Mobius Logic, our people, products, solutions, and expertise, contact us.

Our Team

Nathaniel Bade

Education: Ph.D Mathematics, Northeastern University, M.S in Mathematics, Northeastern University

Nathaniel’s passion lies in spatial questions at the intersection of mathematics, statistics, and computer modeling. He has directed graduate programs in applied mathematics and operations research. He has advised on and implemented several agent-based models across a variety of use cases including conversational systems, pandemic management, and urban violence.

Jared Bennett

Education: Ph.D Biophysics, University of California Berkeley

Jared is a computation and genomic biology expert with data science skills. He has implemented several neural network models for predicting and managing pandemics. His most recent work is in the field of agent-based simulation for analyzing the spread of violence as a disease and predicting the effect of neighborhood revitalization measures on disadvantaged communities.

Sarani Chakraborty

Education: Ph.D Theoretical and Mathematical Physics, Assam University Silchar, M.S. Physics Assam University Silchar

Sarani is an expert in deep neural networks and NLP systems. She has implemented several machine learning models for financial tech solutions and advanced text-based search engines and chat-bots including conversational and cognitive AI systems.

Christian Manasseh

Education: Ph.D. Systems Engineering, University of California Berkeley, M.Eng. Information Technology, Massachusetts Institute of Technology

Christian is a technology leader across a variety of industries. He has extensive experience in software engineering, team leadership, business development, and technology product commercialization across consumer apps, healthcare services, financial services, manufacturing and non-profits. He is the first to use machine learning to quantify fraud in healthcare claims in 2007 and the first to use machine learning to create driver safety profiles from GPS traces in 2009. He is a principal investigator and advisor on several deep learning AI projects involving autonomous robot swarm technology, cognitive systems and smart pandemic management.

Christine Tang

Education: M.Eng. Massachusetts Institute of Technology

Christine is an expert in enterprise IT and AI solutions. She has advised, implemented and delivered several machine learning models for financial services, inspections and intelligence systems.  She is an expert in text-based NLP systems, sensor and financial data.

Razvan Veliche

Education: PhD. Mathematics, Purdue University

Razvan is a results-driven Analytics leader with a solid record of problem solving, data mining, developing and implementing predictive models. Passionate about customer experience, process improvement, new technology and team development. Mathematician focused on finding the right balance between accuracy and complexity. He has advised, consulted and implemented on various data modeling, analytics and machine learning projects including agent-based simulations, synthetic data generation and deep neural networks.