I am now with the Department of Computer Science at Rochester Institute of Technology, Rochester, NY.
You can find me in Room 3-521, Golisano Hall (Building 70), or you can contact me by means given here Please, see my schedule this term.
Previously I worked at the Department of Computer Science, University of Texas at El Paso and School of Communications and Informatics at Victoria University, Melbourne, Australia.Want to know what I am doing? Thank you for your interest. Please, see my key presentations about my two current (and probably, future) areas of research.
Direction 1: Security and data quality evaluation, Big Data phenomenon: see my key address From Big Data to Quality Data: What is the emerging sensor and network technology going to deliver next? to NetWare 2014 , an umbrella event incorporating a few international conferences on November 20, 2014 in Lisbon, Portugal. Also, at the same conference I chaired the panel on November 19 on the topic Information Privacy: Does it really matter?
Direction 2: Intelligent systems and sensor networks design, machine learning and neural networks techniques and their implementation, Big Data analysis: see a joint presentation with my former student Dmitri Yudanov Heterogeneous Implementation of Neural Network Algorithms to the AMD Developer Summit, San Jose, November 11-13, 2013
Want to learn even more?? Please, look below for my latest publications and other information. If you are interested in collaboration, please, contact me (see above).
L. Reznik, S.E. Lyshevski Data Quality Indicators Composition and Calculus: Engineering and Information Systems Approaches, Sensors & Transducers, Vol. 185, Issue 2, February 2015, pp. 140-148
Lyshevski, S.E. ; Reznik, L. ; Smith, T.C. ; Beisenbi, M.A. ; Jarasovna, J.Y. ; Mukataev, N.S. ; Omarov, A.N. Estimates and measures of data communication and processing in nanoscaled classical and quantum physical systems, 2014 IEEE 14th International Conference on Nanotechnology (IEEE-NANO), Toronto, 2014 , pp.1044 – 1047
L. Reznik, S. Lyshevski Data Quality and Security Evaluation Tool for Nanoscale Sensors, SECURWARE 2014, The Eighth International Conference on Emerging Security Information, Systems and Technologies, Lisbon, November 16-21, 2014 in NetWare 2014, ISBN: 978-1-61208-047-5, pp. 118-122
Recently, in our research we moved from specifying the concept of data quality evaluation and assurance to investigating its various aspects. In ' L.Reznik and E.Bertino Data Quality Evaluation: Integrating Security and Accuracy, CCS '13: Proceedings of the 2013 ACM SIGSAC conference on Computer & Communications Security, Berlin, November 2013' we looked at the relationship between the accuracy and security indicators and their role in data quality, and how this knowledge can help improve the design of complex cyber-physical sytems and networks
while in ' S.E.Lyshevsky and L.Reznik Information-theoretic estimates of communication and processing in nanoscale and quantum optoelectronic systems, 2013 IEEE XXXIII International Scientific Conference on Electronics and Nanotechnology (ELNANO), 16-19 April 2013, pp. 33-37' we looked for data quality indicators, which might work in nano-scale systems.
At the same time, I continue my research with my former students on the topics of:
We continued our collaboration (see below) on data quality assessment in cyber-physical data acquisition and control systems with my colleagues Greg Timms, Paolo de Souza from Tasmanian Information and Communication Centre, CSIRO, Australia that resulted in a new paper G.P. Timms, P.A. de Souza, Jr., L. Reznik and D. V. Smith Automated Data Quality Assessment of Marine Sensors, Sensors 2011, 11(10), p.9589-9602
Also, I presented a more generic approach to the data quality assessment to the 2012 IEEE Instrumentation and Measurement Conference. See L.Reznik Integral Instrumentation Data Quality Evaluation: the Way to Enhance Safety, Security, and Environment Impact, 2012 IEEE International Instrumentation and Measurement Technology Conference, Graz, Austria, May 13-16, 2012, IEEE, 2012, pp. 2138 - 2143 in IEEExplore on-line library (you should have an access to IEEExplore).
Cognition is a fundamental feature of natural intelligence, which a modern technology has not yet been able to reproduce in full capacity. Sensor networks provide a new technological support for a substantial increase in an amount and quality of information that might be collected and communicated in complex adaptive systems. Their application may significantly raise the degree of intelligence in system design and implementation into the levels where effects of cognition will start kicking in. The paper, which we just published in IEEE SENSORS Journal, with my students Greg Von Pless (BS/MS class of 2007) and Tay Karim (BS/MS class of 2006) describes the results of an empirical study aiming to demonstrate that a cognition ability may be treated as a generic sensor network feature. See L. Reznik, G. Von Pless, and T.Karim Distributed Neural Networks for Signal Change Detection: On the Way to Cognition in Sensor Networks, IEEE Sensors Journal, vol.11, issue 3, March 2011 . It is already available in IEEExplore on-line library (you should have an access to IEEExplore).
With my students Mike J. Adams (BS/MS class of 2008) and Brian Woodard (BS/MS class of 2009) we have published a paper that improves neural network based intelligent design of intrusion detection systems by dynamically modifying them with genetic algorithms. This approach allows to optimize an intrusion detection based not on performance only but also on a resource consumption. See L. Reznik, M. J. Adams, and B. Woodard Intelligent Intrusion Detection Based on Genetically Tuned Artificial Neural Networks, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.14, No.6 pp. 708-713, 2010 . It is already available in this Japanese journal on-line library.
An application of intelligent techniques in measurement result processing is discussed in our recent paper G.N.Solopchenko, K.K. Semenov, V.Kreinovich and L.Reznik Measurement's Result and its Error as Fuzzy Variables: Background and Perspectives published in Key Engineering Materials, vol. 437, May 2010, pp 487-491 journal.
How to make sensor networks and systems communicate not only the data they collect but also automatically calculate and provide some characteristics of these data quality? My colleagues Greg Timms, Paolo de Souza from Tasmanian Information and Communication Centre, CSIRO, Australia and myself answer this question in the paper G.P. Timms, P.A. de Souza, L. Reznik Automated assessment of data quality in marine sensor networks, IEEE International Conference OCEANS 2010 IEEE – Sydney, Australia, 24-27 May 2010. It is available in IEEE Xplore library.
Another paper on intelligent sensor networks authored by my students Jody Podpora (class of 2006), Greg Von Pless (class of 2007) and myself was published in IEEE SENSORS Journal, see J.Podpora, L. Reznik, G. Von Pless Intelligent Real-Time Adaptation for Power Efficiency in Sensor Networks, IEEE Sensors Journal, vol.8, issue 12, December 2008, pp.2066-2073 . It is available in IEEExplore on-line library (you should have an access to IEEExplore).Our paper L.Reznik and V.Kreinovich "Fuzzy Prediction Models in Measurement" is published in IEEE Transactions on Fuzzy Systems, volume 16, No.4, August 2008, pp. 851-862 . It is available on-line in IEEExplore library (you should have an access right to IEEExplore)
My students Dima Novikov (class of 2006), Roman Yampolskiy (class of 2005) and myself published a paper on intrusion detection. D. Novikov, R. V. Yampolskiy, L. Reznik Traffic Analysis Based Identification of Attacks. International Journal of Computer Science & Applications (IJCSA), vol. 5, Issue 2, 2008, pp.69-88 It is already available on-line in IJCSA repository
Wiley and Sons just released Handbook of Granular Computing /Ed: W. Pedrycz, A.Skowron and V.Kreinovich , Wiley and Sons , Chichester, England, 2008, ISBN 978-0-470-03554-2 On pp.517-532 you can find my new paper L. Reznik Measurement Theory and Uncertainty in Measurements: Application of Interval Analysis and Fuzzy Sets Methods
My main research area is design and development of intelligent cyber-physical computer control, sensor, measurement and information networked systems built upon mobile communication and wireless sensor networks platforms. I am interested in both theoretical and practical aspects, and especially in computer security and quality assessment.
Everyone knows about mobile communication and computer security but what are sensor networks? - see a recent article in Washington Post.
Want to learn more about sensor networks software? - see the TinyOS community forum and University of California at Berkeley website and hardware: see the main manufacturer's sides: Crossbow Inc. and MoteIV
My teaching areas include undergraduate and graduate courses in computer security, artificial intelligence and machine learning, programming and computer science, software, computer, control and electrical engineering, project design, student's project supervision (PhD, graduate, and undergraduate).
Main directions for possible student projects are presented here (note, this presentation introduces directions only; I am happy to discuss with you how they could be adjusted to your interests if you might be interested in my supervision)
Courses taught recently:
Courses taught before at other schools:
Copyright © 1997, 2005, 2008, 2012, 2015 Leon Reznik