Resume: ANINDYA SANKAR PAUL 2192 NW Thorncroft Drive, # 722 Hillsboro, OR 97124 Office: 503-7481925 Home: 503-6908293 E-mail:anindya@csee.ogi.edu website: http://www.csee.ogi.edu/~anindya Education: Degree: Pursuing PhD in OGI School of Science and Engineering at Oregon Health and Science University (OHSU), Beaverton, OR, USA: 09/03-10/08 (expected) M.S.E.E. from Wright State University (WSU),Dayton, OH, USA: 09/01-08/03 Degree: B.Eng. from Sikkim Manipal Institute of technology, India:09/97-07/01 Research Interests: Machine learning, statistical pattern recognition and optimization algorithms, neural networks, probabilistic inference and Bayesian learning including their applications on localization and tracking, signal/image processing, simultaneous localization and mapping (SLAM), automatic target detection/recognition and speech enhancement/recognition. Experience: Graduate Research Assistant, Adaptive Systems Lab, CSEE Dept.,OGI:09/03-till now The research work deals with: 1. Unobtrusive indoor localization and tracking using Wi-Fi received signal strength identification (RSSI) and ultrasonic sonar range sensors. 2. Developing new formulation for sigma-point Kalman smoothers for nonlinear systems. 3. Analyzing stability and convergence criteries for sigma-point kalman filter. 4. Developing new adaptive/statistical signal processing techniques to assist machine automated diagnosis of cardiac causes (e.g. Congestive Heart Failure) of dyspnea (shortness of breath) in the emergency department setting. 5. Developing a dual estimation framwork (SLAM) for autonomous navigation of a vehicle in unknown environment. 6. Developing Sigma Point Kalman filter as a superior alternative to the Extended kalman filter in state estimation, parameter estimation and dual estimation framework. Graduate Research Assistant, EE dept.,WSU: 09/01-08/03. The research work in collaboration with Wright Patterson AirForce Base deals with: 1. SAR Target Detection using subspace filtering. 2. Synthetic Target and Clutter statistical modeling. 3. HRR-ATR using Eigen template based matched Filtering (ETMF) and Discrete Hidden Markov Model (DHMM). 4. New HRR-ATR technique using hybridization of ETMF and DHMM. 5. Speaker recognition using F0 manipulation. Summer Intern at Webel Micro-controller research center, Calcutta, India: 04/99-07/99. Developed an Autodialler Circuitry using microcontroller. Grader: Grader for grad courses "Linear systems","Non-linear filters". Awards: "Special Award for Collaborative Acheivements" obtained in OGI School of Science and Engineering for research in multiple collborative projects and research groups in 2007. "Special Award for Academic Excellence" obtained in Sikkim Manipal University for overall second rank during my undergraduate study. Received Prestigious Merit Scholarship for excellent performance at final high school examination. Professional Membership: Member, IEEE Signal Processing Society, Jan 2006-present Member, IEEE Computational Intelligence Society, Jan 2005-present Member, IEEE Communication Society, Jan 2001-Dec 2003 Member, IEEE Computer Society, Jan 2004-Dec 2004 Student Member, IEEE, Jan 2001-present Review Activities: Reviewer, IEEE Signal Processing Society Reviewer, IEEE Aerospace and Electronic Systems Society Reviewer, IEEE Potential Publication: Peer reviewed published papers: Sunghan Kim, Anindya S. Paul, Eric A. Wan and James Mcnames, "Multiharmonic Tracking Using Sigma-Point Kalman Filter," Accepted in 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008 (IEEE EMBC 08), Vancouver, Canada, August, 2008. Anindya S. Paul and Eric A. Wan, "Wi-Fi Based Indoor Localization and Tracking Using Sigma-Point Kalman Filtering Methods," In proceedings of IEEE/ION Position Location and Navigation Symposium 2008 (PLANS 2008), Monterey, CA, USA, May, 2008. Anindya S. Paul and Eric A. Wan, "A new formulation for nonlinear forward-backward smoothing," In proceedings of IEEE International Conference on Acoustics, Speech and Siganl Processing 2008 (ICASSP 2008), pp. 3621- 3624, Las Vegas, NV, USA, March-April, 2008. Misha Pavel, Tamara Hayes, Ishan Tsay, Deniz Erdogmus, Anindya S. Paul, Nicole Larimer, Holly Jimision and John Nutt, "Continous Assessment of Gait Velocity in Parkinson's Disease from Unobtrusive Measurements," In proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering, pp. 700-703, Kohala Coast, Hawaii, USA, May, 2007. Anindya S. Paul, Eric A. Wan and Alex T. Nelson, "Noise Reduction For Heart Sounds Using a Modified Minimum-Mean Squared Error Estimator with ECG Gating," In proceedings of 28th IEEE EMBS Annual International Conference, pp. 3385- 3390, New York City, USA, August-September, 2006. Anindya S. Paul and Arnab K. Shaw, "Subspace-based Clutter Filtering for Improved SAR Target Detection," In Proceedings of Signal and Image Processing (SIP 2006), Honolulu, Hawaii, USA, August 2006. Anindya S. Paul, "Dual Kalman Filter for Autonomous Terrain Aided Navigation in Unknown Environment," Technical Report, OGI School of Science and Engineering, Oregon Health and Science University, Beaverton, OR, May 2005. Anindya S. Paul and Eric A. Wan, "Dual Kalman Filters for Autonomous Terrain Aided Navigation in Unknown Environment," In proceedings of International Joint Conference on Neural Networks (IJCNN), vol. 5, pp. 2784- 2789, Montreal, Canada, July-August, 2005. Anindya S. Paul, Arnab K. Shaw, Koel Das and Atindra K. Mitra, "Improved HRR-ATR Using Hybridization of HMM and Eigen Template Based Matched Filtering," In Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Hong Kong, vol. 2, pp. 397-400, April 6-10, 2003. Atindra K. Mitra, Thomas L. Lewis, Anindya S. Paul and Arnab K. Shaw, "Self Training Algorithms for Ultra-Wideband Radar Target Detection," In Proceedings of Synthetic Aperture Radar Imagery X, SPIE, vol. 5095, pp. 254-264, Orlando, FL, 2003. Anindya S. Paul and Arnab K. Shaw, "Robust HRR Radar Target Identification by Hybridization of HMM and Eigen-Template Based Matched Filtering," In Proceedings of Automatic Target Recognition XIII, SPIE, vol. 5094, pp. 278-289, Orlando, FL, 2003. Atindra K. Mitra, Thomas L. Lewis, Anindya S. Paul and Arnab K. Shaw, "Ultra-Wideband Radar Data Models and Target Detection with Adaptive Rank Order Filters," In Proceedings of Synthetic Aperture Radar Imagery IX, SPIE, vol. 4727, pp. 112-121, Orlando, FL, April, 2002. Papers currently under review: Sunghan Kim, Anindya S. Paul, Eric A. Wan and James Mcnames, "A New Multiharmonic Frequency Tracking Using the Sigma-Point Kalman Smoother," Under review in IEEE Transactions of Signal Processing. Arnab K. Shaw, Anindya S. Paul and Rob Williams, "Eigen-Template based Matched Filtering (ETMF) for Robust HRR-ATR," Under review in IEEE Transactions of Aerospace and Electronic Systems (AES). Anindya S. Paul and Arnab K. Shaw, "Robust HRR Radar Target Identification by Hybridization of HMM and Eigen-Template based Matched Filtering," Under review in IEEE Transactions of Aerospace and Electronic Systems (AES). Atindra K. Mitra, Anindya S. Paul, Arnab K. Shaw and Thomas L. Lewis, "Improved SAR Target Detection Using Subspace Filtering," Under review in IEEE Transactions of Aerospace and Electronic Systems (AES). Research Experience: Thesis: Masters thesis "Improved target recognition and target detection algorithms using HRR profiles and SAR Images" successfully defended in September, 2003. Research Projects: True Unobtrusive indoor localization and tracking using received signal strength identification (RSSI) and sonar range sensors: My research project currently involves in developing an unobtrusive indoor location tracking system using a number of low cost noisy sensor observations. The primary sensors considered in this research are Wi-Fi based received signal strength identification (RSSI) and sonar range sensors. Augmenting the RSSI measurements are infra-red (IR) motion sensors mounted on the walls and foot-switches which are placed on the floor. As GPS performance is limited in indoor environments, estimating the location of people and tracking them poses a fundamental challenge in ubiquitious computing environment. This work is supported in part by Intel Digital Health group as part of the Behavioral and Interventions Common (BAIC). This unique academic-industrial collaboration aims to focuss on developing a remote monitoring and assistive technologies for the elederly to keep them safe at their own home environment. We proposed a new software based location tracking system which optimally fuses a model of walking motion, room-wall potential fields and all sensor observations in order to track a person. At the core of our system is a novel location and tracking algorithm using sigma-point Kalman smoother (SPKS) based Bayesian inference approach. We specifically used our recently proposed forward-backward statistically linearized sigma-point Kalman smoother (FBSL-SPKS) algorithm as a location tracker. Heart Function Characterization Using Acoustics and ECG: I worked on a project which proposes developing new adaptive/statistical signal processing techniques to assist machine automated diagnosis of cardiac causes (e.g. Congestive Heart Failure) of dyspnea (shortness of breath) in the emergency department setting. This project was jointly funded by Inovise Medical Inc. and School of Medicine, OHSU. In this pilot study, both accoustic sensors data and electrocardiogram (ECG) signals were used for heart function characterization. Currently cardiologists listen the heart sound through stethoscope in order to form a diagnosis of the heart failure. As this form of diagnosis is highly subjective and depends on Cardiologist's past experience, the recent trend is to automate the heart sound diagnosis operation and make heart sound auscultation more quantitative. Inovise Medical Inc. developed a product named "Audicor" which performs an automated collection and analysis of heard sounds in the context of a standard 12 lead diagnostic ECG test. Microphones are placed at 2 ECG locations and acoustical and electrical signals are then analyzed to determine the presence of abnormal heart sounds. This analysis is highly complicated due to the presence of extraneous noise in the audio signal. The fatal heart sounds are generally low-amplitude and low-energy signals that can be easily buried under the noise floor and hence can be missed by the diagnosis. Our job on this project was to investigate advanced signal processing techniques in order to develop a robust noise reduction front end which would enhance the heart sounds with minimal signal distortion. Our approach was based on spectral domain Minimum Mean Square Error (MMSE) estimation, where an adaptive Wiener gain is applied to the spectral amplitudes. Simultaneous Localization and Mapping (SLAM): I investigated a new method for terrain aided navigation of unmanned vehicles in unknown environments. The task is to simultaneously estimate the state of the vehicle (position and attitude) and a map of the surrounding environment given limited sensing capabilities. We recently demonstrated that dual sigma-point kalman filter (SPKF) based implementation without having any priori knowledge of state and environment not only converges faster to the true state and map but also at a lower mean square error than that of the Extended Kalman filter (EKF) based algorithm which was the current industry standard. SAR Target Detection Using Subspace Filtering: We proposed a new class of Subspace filter based algorithms for detecting targets in forest clutter environment. The training phase of the proposed Synthetic Aperture Radar (SAR) target detection algorithms “learns” the clutter characteristics using local or global clutter subspaces. Both off-line and on-the-fly self-training versions of the algorithm are investigated. These adaptive approaches utilize the Singular Value Decomposition (SVD) algorithm where small blocks of data in the neighborhood of a sliding test window are processed in real-time to estimate clutter characteristics. The real-time clutter models are then used to nullify clutter in the test window. The proposed approach is shown to be highly effective for removing blob-like impulsive clutter for improved detection performance. Automatic target recognition: I have worked on a new hybrid Automatic Target Recognition (ATR) algorithm on high range resolution (HRR) profiles. The proposed hybrid algorithm combines Eigen-Template based Matched Filtering (ETMF) and Hidden Markov modeling (HMM) techniques to achieve superior HRR-ATR performance. In the proposed hybrid approach, each HRR test profile is first scored by ETMF that is followed by independent HMM scoring. The first ETMF scoring step produces a limited number of “most likely” models that are subsequently used for improved HMM scoring in the second step. The individual scores of ETMF and HMM are combined using Maximal Ratio Combining to render the final classification decision. Speaker Recognition: I participated in building an Improved Speaker Recognition system by F0 Manipulation. There we built a Text Dependent Speaker Recognition System to examine the effects due to change in vocal effort level on speech recognition. Target/clutter mathematical modeling in stochastic scenario: I have worked on Target and Clutter modeling for Foliage Penetrating Radar (FOPEN). A new bimodal technique is developed for modeling ultra wideband radar clutter and target chips by applying a radar scattering center model. A new adaptive rank-order filter algorithm is developed to estimate the high-end of the clutter distribution. This filtering approach is denoted as the "Discontinuity Filter". We also developed a new singular value decomposition (SVD) technique to improve the baseline False Alam rate by nullifying the foliage clutter. Tracking of Unmanned Aerial vehicle: I was the project leader of signal processing/pattern recognition/Target tracking group of the Wright State University Avionics team. Graduate Coursework: Machine Learning Satistical Pattern Recognition Stochastic Signal Processing Optimization algorithms Digital Image Processing Structure of Spoken Language Adaptive Signal Processing Wireless communication Advanced Wireless Communication Multitarget Tracking and Data Association Kalman Filter and Estimation Optimal Data Fusion VLSI circuit design Software skills: Packages: MATLAB, Real time Data acquision toolbox, PSPICE, and B2 Spice. Languages: C, assembly language programming in 8085, 8086 and 8031. EDA tools: Spice, IRSIM Web Development tools: HTML and Front Page Express. References: Available upon request