A Personal Note from Dr. A.J.

I’ve always been fascinated by the intersection of mind and brain, and particularly in how we can improve our own capabilities. Over the next two decades, I believe that we’ll make major breakthroughs in human capabilities; largely tied to Brain-Computer Interfaces (BCIs).
Well before this, we’ll have major advances in artificial intelligence (AI) and machine learning (ML), and we’ll go well beyond “deep learning.” I’m also firmly convinced that statistical thermodynamics is an integral tool.

Dr. Maren is an innovator in the emerging realm of Brain-Computer Information Interfaces (BCII). Her most recent work introduces a new role for the Cluster Variation Method (from statistical thermodynamics) to modeling neural activation patterns in the brain. See The Cluster Variation Method: A Primer for Neuroscientists, in Brain Sciences, 6(4), 44 (2016), doi:10.3390/brainsci6040044 pdf.

Dr. Maren has devoted her life to figuring out predictive intelligence solutions when the answers are not simple. This quest underlay her first patent on biologically-based sensor fusion (receiving a New York Times Patent of the Week award). Her most recent patent focused on a predictive intelligence architecture, which is a means of capturing intelligence into a computational form.

Dr. Maren has received four patents for breakthroughs in predictive intelligence, knowledge discovery, evidence association for entity matching, and biologically-based sensor fusion – a militarily critical technology. She was the lead scientist on a 2004-2005 DIA-sponsored effort to survey predictive analysis methods, leading her to later form an advanced method to meet the challenges that could not be answered with the then-current technology.

Dr. Maren’s 30+ years working with entrepreneurs and start-ups, receiving over $3.4M in federally-funded contracts for innovative research along with two rounds of investment funding, and winning four patent awards gives her a solid foundation to help you work across disciplines and achieve insights. Her first book, the “Handbook of Neural Computing Applications” (Academic, 1990), became a landmark in the emerging neural network arena. Now, her latest book, “Predictive Intelligence for a Nonlinear World” (expected late 2016) will help scientists, technologists, and strategic thinkers harness the full power of predictive intelligence.

More recently, returning to her roots in statistical mechanics, Dr. Maren shows how using a more complete means of expressing the overall system free energy overcomes the limitations of needing extensive a priori information. Instead, local patterns communicate rich information, which can be characterized with just a few parameters. This new method is captured in the CORTECON II architecture.