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Robert J. Marks II

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Robert J. Marks II

Robert J. Marks II
Born (1950-08-25) August 25, 1950 (age 63)
West Virginia, United States
Main interests Intelligent Design · Electrical Engineering · Evolutionary Computation · Computational Intelligence

Robert Jackson Marks II is a Distinguished Professor of Electrical and Computer Engineering at Baylor University and proponent of intelligent design. From 1977 to 2003, he was on the faculty of the University of Washington in Seattle. He was the first president of the Institute of Electrical and Electronics Engineers (IEEE) Neural Networks Council (now the IEEE Computational Intelligence Society) and the editor-in-chief of the IEEE Transactions on Neural Networks.[1] Marks has over 300 peer-reviewed technical publications, and is a fellow of the IEEE and the Optical Society of America.[2] An old earth creationist,[3] he is a subject of the 2008 pro-intelligent design motion picture, Expelled: No Intelligence Allowed.[4][5]

The Evolutionary Informatics Lab website controversy

In 2007, Marks created on a Baylor University server a website for the Evolutionary Informatics Lab, a site promoting intelligent design.[6] The website, initially hosted on Baylor servers, was deleted when Baylor's administration determined that it violated university policy forbidding professors from creating the impression that their personal views represent Baylor as an institution. Baylor said they would permit Marks to repost his website on their server, provided a 108 word disclaimer accompany any intelligent design-advancing research to make clear that the work does not represent the university's position.[7][8][9] The site now resides on a third-party server [10] and still contains the material advancing intelligent design.

Additional controversy arose when it was discovered that William Dembski, a notable intelligent design proponent and former Baylor staff member at the heart of a previous intelligent design controversy at Baylor over the Michael Polanyi Center's promotion of intelligent design who was removed as the center's director, had returned to Baylor as a member of the Evolutionary Informatics Lab.[11] Dembski's participation was funded by a $30,000 grant from the Lifeworks Foundation, which was funded and administrated by researcher Brendan Dixon of the Biologic Institute, another lab promoting intelligent design affiliated with the Discovery Institute.[12][13]

Marks agrees that "associating with [intelligent design] proponents can be harmful to your career" and expressed sympathy for Guillermo Gonzalez and William Dembski, who feature with Marks in the pro-intelligent design film Expelled: No Intelligence Allowed.[14] Interview footage with Marks was shot for Expelled following the deletion of the website.[4] The motion picture alleges persecution of intelligent design advocates by academic institutions and the scientific establishment.[5]

Technical contributions

Marks is a researcher in the area of electrical engineering.[15]

  • Treatment of prostate cancer. Marks and his colleagues developed algorithms for real time identification of placement of radioactive seeds in cancerous prostates.[16][17] For this work, he was a co-recipient of the Judith Stitt Best Abstract Award from the American Brachytherapy Society.[18] The algorithm is used clinically .[19]
  • Optimal detection. In the field of detection theory, Marks and his colleagues developed the first closed form solution for the Neyman–Pearson optimal detection of signals in non-Gaussian noise[20][21]
Marks, Wise, Haldeman and Whited have derived exact expressions for the test statistic distribution functions, and thus were able to analyze the performance of the optimal detector for given values of signal strength and sample size.[22]
  • Power load forecasting using neural networks. With his colleagues at the University of Washington, Marks was the first[23] to apply an artificial neural network to forecast power demands for utilities in 1991.[24] Six years later neural networks were being used by 32 major North American utilities [23] and remains in common use today. IEEE sponsors a MATLAB based webinar on use of neural networks in load forecasting.[25] A technique "similar to one already used to successfully forecast electrical load needs" has been used to forecast Dow Jones closing values using data from millions of Twitter messages.[26] Concerning the success of the technology introduced in his paper, Marks said "My wife’s grandfather was fond of saying if he had known how long he would have lived, he would have taken better care of himself. If I had known how successful the load forecasting paper would become, I would have spent more time polishing it."[27]
  • Signal display in time and frequency. The Zhao-Atlas-Marks time-frequency distribution,[28] (a.k.a. the ZAM distribution or ZAMD), was originally called the cone shaped time-frequency distribution.[29]
The Zhao–Atlas–Marks distribution produces a good resolution in time and frequency domains. The ZAMD method reduces the interference resulting from the cross-terms present in multi-component signals. It is useful in resolving close spectral peaks and capturing non-stationary and multi-component signals.[32]
[T]he Zhao-Atlas-Marks time-frequency distribution ... significantly enhances the time and frequency resolution and eliminates all undesirable cross terms. // The ZAM distribution has been applied to speech with remarkable results.[33]
  • Remote sensing. Marks and his colleagues [34][35] were the first to use neural network inversion in remote sensing. They measured snow parameters from microwave measurements made by satellites. Their general approach is widely used today.[36][37]
  • Wireless arrays. Marks is a co-recipient of a NASA Tech Brief for pioneering power efficient communication in wireless arrays.[38][39]
  • Power generation. Working with Southern California Edison, Marks and his colleagues pioneered computational intelligence based methods for early detection of intermittent shorted windings in multi ton electric generators while the rotors were still turning.[40][41]
[Their diagnostic test performs] detection and localization of shorted turns in the DC field winding of turbine-generator rotors using novelty detection and fuzzified neural networks. Use of neural networks with fuzzy logic outputs and traveling wave techniques ... is an accurate locator of shorted turns in turbo-generator rotors.[42]
  • Marks has made a number of contributions to the sampling theorem including authoring the first book exclusively dedicated to the subject.[43]
    • Restoration of lost samples. Using "sophisticated estimation of the missing samples using previous and future samples,"[44] Marks[45] first showed that, when a signal sampled above its Nyquist rate, lost samples are "are redundant, in the sense that any finite number of them can be obtained from the remaining ones by solving a system of linear equations."[46]
    • Ill-posed sampling. The sampling theorem's Cheung–Marks theorem[47] shows that samples taken from a signal at or above the Nyquist rate may prove incapable of restoring the signal in the presence of small amounts of noise.[48]
    • Optimal image sampling. Cheung and Marks [49] also first showed that images could be sampled below their Nyquist rate and still be recovered without aliasing.
Their "very interesting multidimensional construction ... exploit[s] the [required] spectral gaps that occur when sampling multidimensional signals. Their approach is to slice the spectrum into narrow bands, and handle separately those bands which contain signal energy and those which do not." [50]
    • System representation using samples. Marks and his colleagues showed continuous dynamic systems can be characterized using the sampling theorem.[51][52]
Techniques have been developed by Walkup, Marks, and their co-workers whereby a shift-variant transformation can be separated into a number of discrete operations. // Marks et al. have derived a generalized sampling theorem that gives the ... rates necessary for dealing with shift-variant operations. // Marks has [also] proposed a number of processors based on temporally multiplexing the impulse response.

[53]

  • Optical computers. Marks invented [54] and implemented [55] an all optical computer that – using lenses, mirrors, and light from a laser – performs iterative calculations literally at the speed of light.
While many problems in optics can be solved by projections, it is difficult to solve such problems using all-optical methods. A notable exception is Marks' all-optical implementations of the convex projection algorithm for implementing super-resolution.[56]

Christianity

Marks served as the faculty adviser to the University of Washington's chapter of Campus Crusade for Christ for seventeen years. He has presented his talk "What Does Calculus Have to Do with Christianity?" [57] in Poland, Japan, Canada, Russia, and the United States.[2]

Marks has made science-oriented Christian apologetics presentations.[58] Venues include Poland, Japan, Moscow, Canada, and Siberia.[18] His creationist view is highlighted in "Genesis and Science: Compatibility Extraordinaire."[3] There he says the God of Genesis is the creator of the universe, and indicates that, from an observers perspective on the surface of the earth (granting an opaque to translucent to transparent atmosphere), the "sequence of events in Genesis is consistent with the sequence of events in science."

Marks refers to himself as "A servant of Jesus Christ."[2]

Other activities

Books by Robert J. Marks II

  • R.J. Marks II, "Handbook of Fourier Analysis and Its Applications," Oxford University Press, (2009).[23]
  • R. D. Reed and R.J. Marks II, Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks, MIT Press, Cambridge, MA, (1999).
  • M. Palaniswami, Y. Attikiouzel, R.J. Marks II, David Fogel and Toshio Fukuda; Editors, Computational Intelligence: A Dynamic System Perspective, IEEE Press, (1995).
  • R.J. Marks II, Editor, Fuzzy Logic Technology and Applications, IEEE Technical Activities Board, Piscataway, (1994).
  • J.Zurada, R.J. Marks II and C.J. Robinson; Editors, Computational Intelligence: Imitating Life, (IEEE Press, 1994).
  • R.J. Marks II, Introduction to Shannon Sampling and Interpolation Theory, Springer-Verlag, (1991).[24]
  • M.A. El-Sharkawi and R. J. Marks II, Editors, Applications of Neural Networks to Power Systems, IEEE Press, Piscataway, (1991).

References

External links

  • Robert J. Marks II, PhD home page
  • Dr. Robert J. Marks II Engineering Faculty, Baylor University
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