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I am involved in two related projects at present, one being fundamental research leading towards a long-range research goal, and the other, for the most part, a software development project.
My long-term research goal is to advance the methodology of protein structure prediction from sequences. This led me, in the fall of 2009 to study quantum chemistry, as I pursued an understanding of the problem. I had decided to focus strictly on ab initio methods of protein structure prediction. Among the different protein structure prediction strategies, only ab initio (also known as de novo) methods use physical principles alone rather than relying on previously solved structures. These physical principles ultimately reduce to finding the global minimum of the potential energy function of the molecule, which, according to the Thermodynamic Hypothesis (Anfinsen's Dogma), yields the atomic coordinates of the native folded molecule for a large class of proteins, under suitable conditions. In the past, ab initio methods were considered to be infeasible. However, they are becoming more feasible as computers have grown in power and as research has led to improved global minimization algorithms.
Most approaches to the problem use classical molecular mechanics, even though quantum mechanics yields more accurate answers. The argument against using quantum mechanics is that it is still infeasible to use it, and that for practical purposes, it does not provide better information than classical mechanics. The jury is still out on this question though, and quantum mechanics is at the heart of the problem. Therefore, I decided, during the summer of 2009, to start with first principles and follow this approach.
My thesis work was a study of concurrent software testing; a brief summary of which is encapsulated in [12]. Although testing conventional software is in itself a difficult problem, concurrent software testing is immensely harder. While one cannot quantify the testing effort without making a lot of formal statements, roughly put, the cost of concurrent software testing is expontentially related to the cost of sequential software testing.
I also investigated the various methods of measuring software reliability, with my thesis advisor, Dr. Elaine J. Weyuker, [11,13]. For many years, I studied software testing strategies from both empirical and theoretical viewpoints. I compared different testing strategies through experimentation and analysis [1,2,6,7,8,9]. I also investigated measures by which one can actually compare testing strategies [10]. One of my Ph.D. students, Vladimir Fleyshgakker, and I proposed a hardware architecture for mutation testing and mutation analysis [3,5] as well as more efficient serial algorithms for mutation analysis [4]. Eventually, I found most of this research frustrating, because almost always, the results indicated that, for software to be judged nearly error-free, the amount of testing would have to be far in excess of that which industry would ever undertake. The research began to feel like nothing more than an academic exercise, and I felt that I did not measure up when I compared my accomplishments to those of my colleagues in the medical fields.
I turned my attention to medical software, specifically computer-based, ophthalmologic exams. I worked with a company that sought to develop computer based eye exams such as visual field tests, acuity tests, and contrast sensitivity tests. My work included developing algorithms and validating the software that ran the exams. The goal was to revolutionize the delivery of eye care to people who did not live near large medical centers by making these eye tests available on the internet and making it possible for doctors in remote regions to have access to high quality eye testing equipment.
Ph. D., (Computer
Science), Courant Institute of Mathematical Science, New York University,
1987
M. S., (Computer Science), Courant Institute of Mathematical Science, New York
University, 1984
B. A., summa cum laude, (Mathematics), Hunter College of CUNY, 1982
B. Architecture, The Cooper Union for the Advancement of Science and Art, 1973
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