Company

Prism Informatix is an advanced analytics technology startup out of MIT operating in the greater Boston area. The company was founded to offer a new way of realizing value and managing complexity with distributed Big Data. 

Prism is privately held and fully owned by its two co-founders.

The company was bootstrapped on Government-funded research contracts to investigate concept viability and reduce technical risk.  It now operates wholly as a commercial product enterprise.

Vision:        

Our vision is to revolutionize decision making from distributed big data by enabling cost-effective predictive analysis of it no matter where it resides, who owns it, what format it is in, or how much of it there is.

Mission:

Our mission is to provide a new kind of information service that allows users to realize the benefit from combining many distributed data sources together to make better decisions, but without the high costs and delays of actually integrating the data.

Strategy:

Our strategy is to employ an approach we call Collaborative Analytics, which enables real-time predictive decision making from distributed silos of data, without integrating the data.  The approach is based on a machine learning method in which the learning of the global data model as well as the derived predictions are fully distributed processes. The platform is built out and can be evaluated on your datasets.

 

Our Team

Alan Chao and John Wissinger were once graduate school officemates at MIT’s Laboratory for Information and Decision Systems (LIDS), and have since sustained a twenty-five year history of professional collaboration. They are engineers with a shared passion for distributed algorithms and architecting challenging mathematically-intensive distributed systems. They share technical expertise in estimation and control, large-scale and stochastic optimization, statistical signal processing, probabilistic modeling, and data analytics. 

 

Alan Chao, co-founder

Dr. Chao is an experienced system architect and software developer, with specialized expertise in large-scale machine learning, high-performance computing, and distributed systems. 

He previously served as Chief Engineer in the Signal Understanding and Networking Division at BAE Systems, Advanced Information Technologies (formerly Alphatech, Inc.). In this capacity, he led research and engineering efforts in technical areas of statistical signal processing, computer vision, sensor fusion, distributed systems, and sensor resource management, resulting in the development of operational systems. At Alphatech/BAE, he led the development of an architecture for integrating advanced, distributed sensor exploitation algorithms within a high-performance computing platform. This architecture enabled the orchestration of algorithms as services along the target kill chain for multi-target detection, geo-location, and identification while balancing the resource load across these services. He also led the development of Alphatech/BAE's coherent and non-coherent radar change detection system using large-scale computing to process high-rate streaming synthetic aperture radar imagery in real time. After BAE Systems, he co-founded lifeblast.com, a location-based, mobile social networking company developing a social discovery and collaboration application.  At lifeblast, he developed a novel algorithm for estimating the presence of individuals at social venues based on geoposition measurements and a model of the social preferences of the individual based on prior collected history.

Dr. Chao received his Bachelors from Georgia Tech and his Masters and PhD from MIT, all in Mechanical Engineering; thesis area: stability robustness of non-linear feedback systems.

John WISSiNgER, co-founder

Dr. Wissinger is a seasoned engineer and manager, with broad and diverse experience in technologies, product development approaches, application domains, and business models.

He previously served at Veeco Instruments (as VP/GM, VP Engineering Metrology), a global public company manufacturing process equipment, analytic instrumentation, and metrology tools for nanotechnology applications.  In this capacity he managed all business functions including sales, marketing, engineering, manufacturing and customer support for product lines in interferometric microscopy and stylus profilometry. Prior to that time, he worked at NP Photonics (VP Engineering), a venture-backed startup engineering micro-fiber optical amplifiers and fiber lasers, and for Alphatech Inc. (Division Manager), a private company which was acquired as BAE Systems Advanced Information Technology Division, where he led development of specialized image and signal processing algorithms and software products for US Government customers, and also managed a commercial venture in video-based License Plate Recognition for airport parking revenue control. During the founding phase of Prism, he held a part-time appointment as Research Professor at the University of Arizona’s College of Optical Sciences in the advanced fiber-optic networking and photonic communications group, where he established testbed infrastructure, served as liaison to numerous corporate partners, and contributed to research in the areas of optical computing and software-defined networks.

Dr. Wissinger received his Bachelors and Masters in Electrical Engineering and Computer Science from Rice University, and his PhD in EECS from MIT; thesis area: learning algorithms for distributed hypothesis testing networks. 

https://www.linkedin.com/in/johnwissinger1

Careers

Prism Informatix is actively seeking summer interns.  We are looking for driven candidates who want to help create the next generation of analytic solutions. We provide a fast-paced, demanding, and constantly evolving entrepreneurial environment with the ability to learn from some of the best mentors.  While the internship would be unpaid, there is the possibility of full-time employment post graduation. Prism Informatix is a participating startup in MIT’s Venture Mentoring Service (VMS).

·      Marketing: MBA candidates preferred; tasks - market analysis, business development

·      R&D: MS or PhD candidates in computer science, data science, or engineering preferred; tasks - data analytics, machine learning, test and evaluation, software development