Curriculum Vitae – Inventions and Innovations
Research, Inventions, and Innovations for Alianna J. Maren
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There is nothing so practical as a good theory. Kurt Lewin, Father of Social Psychology |
As a scientist and innovator, Dr. Maren applies methods from statistical mechanics to modeling behavior in collections of neural domains and to large-scale data corpora. In the past, she has used neurophysiological insights to inspire algorithms and architectures in knowledge discovery, sensor fusion, and predictive analytics.
Current Work
The cutting edge of both nonlinear predictive analysis for large data corpora and modeling ensemble behavior in collections of neural domains each requires novel methods from statistical mechanics – surprisingly, the same theoretical foundation serves both applications.
Inventions with Awarded Patents
Dr. Maren’s four awarded patents apply insights from statistical thermodynamics, neural networks, and neurophysiology to problems in big data analytics, knowledge discovery, sensor fusion, and predictive intelligence.
As a scientist and innovator, Dr. Maren creates unique multi-disciplinary solutions to challenging problems. Her four awarded patents apply insights from statistical thermodynamics, neural networks, and neurophysiology to problems in big data analytics, knowledge discovery, sensor fusion, and predictive intelligence.
Dr. Maren’s current work uses nonlinear models, derived from both neural architectures and statistical thermodynamics, to predict nonlinear changes in unstructured data and other complex systems.
Inventions and Entrepreneurship
Dr. Maren’s life goal has been to build systems that will help humans discover and advance their greatest potential.
To this end, she decided that theoretical was more germane than a lab-based approach, and so immersed herself in early studies of chemistry, physics, and mathematics (yielding a B.S. in math, and then a Ph.D. in theoretical physical chemistry, under the renowned theoretician Sheng H. Lin).
With her Ph.D. in hand, Dr. Maren focused on artificial intelligence, rapidly assessing and discarding the circa 1980’s-style expert systems, and moving (during the late 1980’s) into neural networks. Later, during a one-year sojourn at Radford University, she had an opportunity to connect closely with Dr. Karl Pribram at his Brain Research Laboratory, active in the early 1990’s. This gave her further insights into brain-based processes.
Combining neural network methodologies, advanced forms of statistical thermodynamics for system modeling, and brain-based models for system control, she developed several unique and innovative methods.
Most recently, Dr. Maren has been re-invigorating predictive intelligence modeling using nonlinear systems, particularly drawing on statistical thermodynamics.
As a means of getting product-to-market, she founded Mourning Dove Press (MDP) in 2010. This venture was initially begun to support publication of her newest book. Within just two years, she found that MDP’s true value was in providing an outreach platform for teaching emerging authors and entrepreneurs. This was the first time that – using newer technologies and a different business model – Dr. Maren was able to directly create and sustain a teaching and mentoring program independent of classroom and geographic boundaries.
Prior to founding Mourning Dove Press, and up through 2008, Dr. Maren was the Initiating Founder and Chief Scientist of EagleForce Associates (later Viziant Corporation), a high-technology company devoted to building advanced knowledge discovery capabilities, applicable to very large, heterogeneous data corpora.
The immediate motivation for EagleForce was 9/11, and the need to create knowledge discovery solutions – methods for finding relevant and inter-connected pieces of data hidden within very large data corpora. Assessing the various algorithms and solutions offered by different knowledge discovery companies at that time, she determined that the challenge was not so much in application of a single algorithm, but rather in establishing a control structure that would make the best possible use of a series of well-known algorithms. This approach built on the classic artificial intelligence principle of different representation levels for data processing, together with brain-based concepts for feedback loops and direction of attention. This work led to her second major patent, (Knowledge discovery method with utility functions and feedback loops).
Dr. Maren obtained her first patent while addressing the sensor fusion problem for the U.S. Navy. This patent, Sensor Fusion Apparatus and Method; Patent US 5850625 A, was selected by the New York Times as a Patent of the Week. It addressed a militarily-critical problem, and took an innovative brain-based approach, formulating a methodology based on how the superior colliculus responds to and directs processing attention to novel stimuli by integrating data from multiple biological sensor systems. In a manner presaging her second patent, this approach used a control loop to direct processing resources. She devised a unique cooperative-competitive neural network to match distinct sensor inputs; this helped solve the many-to-many matching problem.
This first patent, obtained while Dr. Maren was Senior Scientist at Accurate Automation Corporation (1990 – 2000), set the tone for future work; using brain-based processes to inspire novel solutions to complex problems. During this time, Dr. Maren was Principal Investigator for eleven Phase I & Phase II SBIR/STTR contracts, for a total of over $3.4M in contract revenue, with contracts from the Office of Naval Research, the Dept. of the U.S. Navy, the U.S. Marine Corps, the National Science Foundation, and NASA.