Suleyman Serdar Kozat is a research staff member at IBM researching speech technologies. He has a PhD from the University of Illinois in electrical engineering, with a focus on digital signal processing. He has published numerous papers in signal processing and machine learning and holds several patents. He seeks full-time positions applying machine learning and signal processing to problems such as speech recognition.

1. Suleyman Serdar Kozat
E-mail: kozat@us.ibm.com
URL : http://www.research.ibm.com/people/k/kozat
174 Nob Hill Drive Tel: (914) 945 2713
Elmsford, NY 10523
Objective A full-time position with interests in machine learning, signal processing, speech
processing, development of signal processing and machine learning algorithms, data mining.
Qualifications
• Research work accomplished in the field of signal processing and machine learning with
emphasis on adaptive signal processing and machine learning algorithms for signal
processing; equalization, prediction, estimation and speech recognition, mathematical finance
and data mining: with several publications.
• Ranked 1st in OYS in 1994 based on nets.
• Recipient of several medals in mathematics competitions including competitions by ODTU,
AFL, Ozdebir.
• Recipient of several fellowships including Bilkent University Fellowship, Is Bankasi
Achievement Scholarship, Vakifbank Scholarship, Electric Telecommunications A.S
Scholarship (Nortel), Final Dersaneleri Fellowship, Sema Yazar Vakfi Fellowship.
• Several patent application for works done in Microsoft Research and IBM Research.
Education
2001-2004 PhD. in Electrical and Computer Engineering,
University of Illinois at Urbana-Champaign. Urbana, IL, USA
Advisor: Dr. Andrew C. Singer
o Concentration: Digital Signal Processing
o Thesis title: Competitive Signal Processing
1999-2001 M.S. in Electrical and Computer Engineering,
University of Illinois at Urbana-Champaign. Urbana, IL, USA
Advisor: Dr. Andrew C. Singer
o Concentration: Digital Signal Processing
o Thesis title: Multi-stage Adaptive Filters
o GPA: 3.94/4.00
1994-1998 B.S. in Electrical Engineering,
Bilkent University. Ankara, Turkey
Supervisor: Dr. Orhan Arikan
o High Honour: GPA: 3.89/4.00
o Awarded Full Scholarship for 4 years of undergraduate study.
o Ranked 4th in the EE department upon graduation
1991-1994 Ankara Fen Lisesi,. Ankara, Turkey

2. Experience
A brief description of research work is also available in Addendum.
• Full-time Research Staff Member: IBM, T.J. Watson Research Center, Yorktown, NY
(2004-Present)
Pervasive Speech Technologies
o Analysis and diagnoses of call center applications for performance improvement.
o Design and implementation of unsupervised and semi-supervised model training, and
active learning algorithms for telephony applications.
o Extension of linear feature transforms such as FMLLR with nonlinear transformations
based on fMPE for switchboard evaluations.
o Design and implementation of task and grammar independent confidence measures.
The proposed algorithms will be used in the latest IBM speech recognition engine.
o Design and implementation of model combination algorithms based on multi-stage
adaptive filtering for speech-to-speech translation systems.
• Software Developer: Microsoft Research, Redmond, Washington ( 2002-2004)
Cryptography and Anti-Privacy Group
o Design and implementation of novel robust signal hashing and watermarking
algorithms.
o Design and implementation of attacks on robust signal hashing and watermarking
algorithms based on universal estimation and prediction algorithms.
• Research Assistant: University of Illinois at Urbana-Champaign. Urbana, IL (1999-2004)
Advisor: Dr. Andrew C. Singer
o Member of Center for Signal Processing and Channel Coding (CSPCC)
Member of Wireless Communications Group (WCC)
o Introduced and developed new multistage algorithms as well as analyzed old
multistage algorithms for applications on universal data prediction, speech modeling
and coding, adaptive channel equalization.
o Provided convergence and optimality proofs for the proposed new algorithms.
o Derived worst case bounds on the performance of the best sequential prediction
algorithm for any bounded sequence
o Design and implementation of universal predictors that achieve optimality in the
worst case against several different competing algorithms including class of all linear,
nonlinear, switching predictors.
• Research Intern: Microsoft Research, Redmond, Washington (May 2003)
Signal Processing Group
o Introduced 3 new modes of operation for AMR-WB (adaptive multi band wideband)
speech codec which would be recommended to 3GPP for packet loss recovery.
o Introduced and implemented optimal media dependent FEC (forward error correction)
algorithms for loss recovery in packet switch networks. As a result of this work,
AMR-WB codec would be recommended to product groups, with the corresponding
loss-recovery algorithm, to be used in VoIP (voice over IP) applications.
o Implemented a novel stereophonic acoustic echo cancellation algorithm for VoIP
applications.
• Research Intern: Microsoft Research, Redmond, Washington (August 2003)
Cryptography and Anti-Privacy Group

3. o Introduced robust hashing and watermarking algorithms using pseudo random
geometric statistics to be used for audio, images and video.
o Implemented several novel watermarking algorithms based on matrix invariants, with
an emphasis on Singular Value Decomposition (SVD).
o Several patents are submitted.
• Research Intern: IBM, T.J. Watson Research Center, Yorktown, New York (May 2000)
Speech Processing Group
o Kalman Filtering for cepstrum bias removal.
o Speech signal enhancement by using discrete prolate spheroidal sequences.
o Speech modeling
• Graduation Project: Bilkent University (Spring 1998)
o Design and implementation of maximum likelihood and adaptive filtering algorithms
for online frequency estimation of sinusoidal data.
• Research Intern: Aselsan Electronic Industries Inc. Ankara, Turkey (June 1998)
Signal Process Group
o Design and implementation of an automatic modulation-recognition
system for analog and/or digitally-modulated signals with low SNR.
• Research Intern: Aselsan Electronic Industries Inc. Ankara, Turkey (June 1997)
Signal Process Group
o Implementation of an elliptic filter of order 15 for radar signal processing
applications.
Sample Publications
Available at http://www.research.ibm.com/people/k/kozat
• Suleyman S. Kozat, “Competitive Signal Processing,” Ph.D. Thesis, Department of Electrical
and Computer Engineering, University of Illinois at Urbana-Champaign, 2004
• Suleyman S. Kozat, “Multistage Adaptive Filters,” MS. Thesis, Department of Electrical and
Computer Engineering, University of Illinois at Urbana-Champaign, 2001
• Andrew C. Singer, Suleyman S. Kozat, Meir Feder, “A Sequential Probability Approach to
Universal Linear Least-Squares Prediction,” Information Theory, IEEE Transactions on ,
Volume: 48 Issue: 8 Aug. 2002 Page(s): 2354 –2362
• Suleyman S. Kozat, Andrew C. Singer, “Universal piecewise prediction via context trees,”
submitted to IEEE Transactions on Signal Processing T-SP-04291-2006
• Suleyman S. Kozat, Andrew C. Singer, “Universal piecewise constant and linear least squares
prediction,” submitted to IEEE Transactions on Signal Processing T-SP-04541-2006
• Suleyman S. Kozat, Andrew C. Singer, “Universal portfolios for switching and side-
information,” to be submitted to Journal of Mathematical Finance
• Suleyman S. Kozat, Andrew C. Singer, “Multiple order RLS prediction,” to be submitted to
IEEE Transactions on Signal Processing
• Suleyman S. Kozat, Andrew C. Singer, “Multiple order LMS prediction,” to be submitted to
IEEE Transactions on Signal Processing
• Suleyman S. Kozat, Andrew C. Singer, “Universal switching linear least squares prediction ,”
Proceedings of IEEE Conference on Information Theory and Its Applications, 6-10, UCSD,
La Jolla, CA, 2006

4. • Andrew C. Singer and Suleyman S. Kozat, “Universal context tree least squares prediction ,”
accepted for publication in the Proceedings of IEEE International Symposium on Information
Theory, 2006
• Suleyman S. Kozat, Karthik Visweswariah, Ramesh Gopinath, “Feature Adaptation Based on
Gaussian Posteriors,” Proceedings of IEEE International Conf. on Acous., Speech and Sig.
Processing, 2006
• Andrew C. Singer and Suleyman S. Kozat, “Universal context tree p-th order least squares
prediction,” submitted to the IEEE Workshop on Machine Learning for Signal Processing
2006
• Suleyman S. Kozat, Andrew C. Singer, “Universal portfolios for switching and side-
information,” submitted to the IEEE Workshop on Machine Learning for Signal Processing
2006
• Suleyman S. Kozat, Andrew C. Singer, “Minmax Optimal Prediction with Side Information”,
Proceedings of IEEE Conference on Acoustic, Speech and Sig. Proc., 469-72, 2004
• David Luengo, Suleyman S. Kozat, Andrew C. Singer, “Universal Piecewise Linear Least
squares Prediction,” Proceedings of IEEE International Symposium on Information Theory,
pp 198, 2004
• Suleyman S. Kozat, M. Kivanc Mihcak, Ramarathnam Venkatesan, “Robust Perceptual Image
Hashing via Matrix Invariants,” Proceedings of IEEE International Conference on Image
Processing, pp 3443-46, 2004
• Suleyman S. Kozat, Andrew C. Singer, “A lower bound on the performance of sequential
prediction,” Proceedings of IEEE International Symposium on Information Theory, 2002, 147
–147
• Suleyman S. Kozat, Andrew C. Singer, “Further Results on Multistage Adaptation
Algorithms,” Proceedings of IEEE International Conf. on Acous., Speech and Sig.
Processing, Orlando, US, 2002
• Suleyman S. Kozat, Andrew C. Singer, “On Universal Linear Prediction of Gaussian Data,”
Proceedings of IEEE International Conf. on Acous., Speech and Sig. Processing, Istanbul,
Turkey, 2000
• Suleyman S. Kozat, Andrew C. Singer, “Multi-Stage Adaptive Signal Processing
Algorithms,” First IEEE Sensor Array and Multichannel Sig. Proc. Workshop March, 2000
Massachusetts, USA
• Suleyman S. Kozat, Dinei Florencio, “Media Dependent Optimal FEC Transmission
Algorithms”, in preparation for submission to IEEE Conference on Acous., Speech and
Sig.Processing
• Suleyman S. Kozat, Karthik Visweswariah, Ramesh Gopinath, “Efficient, Low Latency
Adaptation for Speech Recognition,” in preparation for submission to International
Conference on Spoken Language Processing
Patents
• S. S. Kozat, R. Sarikaya, Y. Gao, “Optimal model selection and hypotheses combination for
spoken dialog systems and machine translation,” filed 2006
• S. S. Kozat, R. Sarikaya, A. Buyuktosunoglu, “A method and apparatus for optimal prediction
of microprocessor behaviour,” filed 2006
• S. S. Kozat, R. Venkatesan, M. K. Mihcak, “Digital goods representation based on matrix
invariants,” invention report filed 2004
Skills Languages: Turkish / English

5. Computer languages: C/C++ (Highly Experienced), Matlab, (Highly Experienced), 80x86
assembly, Pascal.
Utilities: Magic, Hspice, Pspice, Spice3, B2 Logic, Microsoft office programming packages,
various publishing and presentation packages.
Operating systems: Unix, Linux, Windows
Related Coursework
Micro and Macro Economics, Stochastic Processes, Real Analysis, Differential Equations,
Advanced Topics in Signal Processing, Digital Signal and Spectral Estimation, Digital
Imaging, Adaptive Signal Processing, Detection and Estimation Theory, Digital and Analog
Communication Systems, Information Theory, Digital Image and Video Processing,
Communication Networks, Modeling and Control of High-Speed Networks.
References
• Andrew C. Singer, University of Illinois At Urbana-Champaign, Urbana, IL
Email: acsinger@uiuc.edu
• M. Kivanc Mihcak, Bogazici University, Istanbul, Turkey
Email: kivanc.mihcak@boun.edu.tr , kivancm@microsoft.com
• Yoram Bresler, University of Illinois At Urbana-Champaign, Urbana, IL
Email: ybresler@ifp.uiuc.edu