Signal Processing Engineering

BHAVANA CHAKRABORTY, Ph.D.

***** ***** ******* **, ******** Heights, MI 48314

602-***-**** • *******.***********@*****.*** • http://www.public.asu.edu/~bmanjuna/

Summary of Qualifications

Highly skilled professional seeking research position that utilizes strengths in advanced signal processing, algorithm development, and MATLAB programming. Well-versed in data analysis and stochastic filtering methods for state estimation, prediction, detection and tracking. Possess in-depth knowledge of Monte Carlo methods, Bayesian and statistical modeling techniques. Experience in working on modern sensors for advanced vehicle tracking. Authored numerous international publications. Valued and respected associate recognized for keen attention to detail, solid presentation skills, and creative approach to problem solving. Areas of interest include:

Stochastic methods• Adaptive Filters • Statistics and Numerical Methods

Feature Extraction • Data analysis for diagnostics and prognosis • Urban Sensors

MIMO Signal Processing • Multi-core processing for complex algorithms/large data sets

Education

ARIZONA STATE UNIVERSITY, Tempe, AZ 2010

Ph.D. in Electrical Engineering (Signal Processing and Communications)

• Dissertation: “Advancements in Waveform Design for MIMO Radar and Urban Multipath Exploitation Radar”

• GPA: 3.77/4.0

• Graduate Research Assistantship

• Relevant coursework: Real-time Digital Signal Processing, Random Signal Theory, Time-Frequency Signal Processing, Digital Spectral Analysis, Monte Carlo methods and simulation, Advanced Linear Algebra and Optimization, Artificial Neural Networks, and Detection and Estimation Theory

Master of Science in Electrical Engineering (Signal Processing and Communications)

• GPA: 3.77/4.0

VISVESWARAIAH TECHNOLOGICAL UNIVERSITY, R. V. College of Engineering, Belgaum, India 2005

Bachelor of Engineering in Instrumentation Technology

Research Experience

ARIZONA STATE UNIVERSITY (ASU), Tempe, AZ 2005–Present

Postdoctoral Scholar, Signal Processing and Adaptive Sensing (SPAS) Lab • 2010–Present

• Perform environment modeling and analysis (for radars) in support of project funded by Air Force Office of Scientific Research (AFOSR) Multidisciplinary University Research Initiative (MURI).

• Create algorithms for novel state estimation criteria; oversee all aspects of algorithm prototyping and implementation.

• Develop novel feature design and active learning algorithms for diagnosis.

• Prepare grant proposals and presentations for multi-university meetings.

• Mentor graduate and Ph.D. candidates.

Research Assistant, SPAS Lab • 2007–2010

• Implemented Monte Carlo methods for vehicle tracking purposes.

• Multi-core parallel implementation of advanced signal processing algorithms.

• Target tracking using urban environment maps.

• Sensor scheduling for MIMO radar system.

• Directed efforts to implement and test novel algorithms for detection, estimation, and tracking.

• Documented results and produced detailed technical reports.

ASU, Tempe, AZ (Continued) 2005–Present

Research Assistant, SPAS Lab • 2007–2010 (Continued)

• Research results were accepted, published, and presented at international conferences (Complete list of publications available at http://www.public.asu.edu/~bmanjuna/).

Research Assistant, Integrated Sensing and Processing (ISP) Group • 2005–2006

• Collected/analyzed data for wireless sensor networking for remote sensing. Acoustic signals from human footsteps were used to estimate and localize target position in wireless sensor grid. Project was funded by Defense Advanced Research Projects Agency (DARPA) ISP program and Raytheon Missile Systems.

• Captured acoustic data using Mote sensors.

• Developed target detection and tracking algorithms from received data signatures; prepared technical reports and posters.

• Research results were accepted and published in Research in Interdisciplinary Science and Engineering Symposium at ASU.

• Used MATLAB and C programs to implement digital signal processing algorithms.

TEXAS INSTRUMENTS, Bangalore, India 2005

Engineering Intern

• Worked closely with characterization engineers to design LabVIEW instrument drivers for testing

and calibration. Instrument drivers were developed for data generator systems, oscilloscopes, and jitter measurement instruments.

• Generated in-depth technical reports and prepared/delivered presentations.

• Engineering project was honored as ‘2nd Best’ at RV College of Engineering in India.

• Gained hands-on experience using LabVIEW and related National Instruments (NI) products.

Key Projects

Monte Carlo Methods & Simulation

• Performed randomness testing, including uniformity, correlation, periodicity, chi-square, and discrepancy, of data sets.

• Made approximations to Gaussian random variable using Law of Large Numbers (LLN) and Central Limit theorems.

• Utilized simulated annealing (SA) and Monte Carlo simulations to solve difficult integrals and traveling salesman problem (TSP).

Linear Algebra

• Experimented with gradient descent algorithm to solve quadratic minimization problems.

• Applied Newton’s Method for unconstrained and equality constrained optimization problems.

• Sensor scheduling formulated mixed Boolean-convex optimization problem and solved using Branch and Bound (B&B) algorithm.

• Results published in Asilomar Conference on Signals, Systems & Computers.

Detection & Estimation Theory

• Analyzed stream of noisy data from an array of 9 sensors using time-series and time-frequency analysis.

• Used maximum likelihood estimator (MLE) and Cramer-Rao lower bound (CRLB) optimization to calculate range and direction-of-arrival (DOA) estimation. Results were published and presented at Waveform Diversity and Design Conference.

Filtering of Stochastic Processes

• Investigated stochastic processes in relation to auto-regressive moving average (ARMA) filters.

• Performed variety of simulations, including (extended) Kalman filter, second-order extended Kalman filter, and iterated extended Kalman filter.

• Conducted survey on particle filter and variants. Results were used in Sensor, Signal and Information

Processing workshop.

Neural Network & Learning Machines

• Utilized artificial neural networks (ANNs) to solve data classification and feature extraction problems; used perceptrons, least mean squares, Weiner filters, backpropagation algorithms, and self-organizing maps (SOMs).

Projects involving large datasets

• Developed algorithms to handle large dataset in particle filters using multiprocessor approach. Processing time was reduced 50% through use of 4-processor architecture; results were published and used at IEEE workshop.

• Efficiently applied feature extraction techniques to manage large data collected by acoustic sensor motes.

Publications (other name used: Bhavana Manjunath)

Book Chapter

• A., Papandreou-Suppappola, J. Zhang, B. Chakraborty, L. Ying, S. Sira, and D. Morrell. "Adaptive waveform design for tracking." Chapter 16 in Waveform Diversity for Advanced Radar Systems, (F. Givin, A. De Maio, and L. Patton, Eds.), IET Peter Peregrinus, 2010.

Journals

• B. Chakraborty, J. Zhang, A. Papandreou-Suppappola, and D. Morrell. "MIMO radar scheduling and adaptive waveform design for dynamic target tracking." (In preparation for) IEEE Transactions on Signal Processing, 2010.

• M. K. Banavar, B. Chakraborty, H. Kwon, Y. Li, J. Zhang, C. Chakrabarti, A. Papandreou-Suppappola, A. Spanias, and C. Tepedelenlioglu. “A Review on Sensor, Signal, and Information Processing Algorithms.” Digital Signal Processing Journal, 2010 (accepted for publication).

Conferences

• B. Chakraborty, J. Zhang, A. Papandreou-Suppappola, and D. Morrell. “Urban terrain tracking in high clutter using waveform agility.” (accepted for publication) IEEE International Conference on Acoustic, Speech and Signal Processing, Prague, Czech Republic, 2011

• B. Chakraborty, J. Zhang, A. Papandreou-Suppappola, and D. Morrell. “Urban terrain tracking using MIMO radar.” IEEE DSP Workshop, Sedona, AZ, 2011.

• B. Chakraborty, Y. Li, J. J. Zhang, T. Trueblood, A. Papandreou-Suppappola, and D. Morrel. "Multipath exploitation with adaptive waveform design for tracking in urban terrain.” IEEE International Conference on Acoustic, Speech and Signal Processing, Dallas, TX, 2010.

• B. Manjunath, J. Zhang, A. Papandreou-Suppappola, and D. Morrell. "Sensor scheduling with waveform design for dynamic target tracking using MIMO radar." Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2009.

• B. Manjunath, J. Zhang, and A. Papandreou-Suppappola. "Waveform-Agile Sensing for Range and DoA Estimation in MIMO Radars." In IEEE Waveform Design and Diversity conference, Orlando, FL, 2009.

• B. Manjunath, A. Williams, C. Chakrabarti, and A. Papandreou-Suppappola. "Efficient Mapping of Advanced Signal Processing Algorithms on Multiprocessor Architectures.” IEEE Workshop on Design and Implementation of Signal Processing Systems, Washington DC, 2008.

• J. Zhang, B. Manjunath, G. Maalouli, A. Papandreou-Suppappola, and D. Morrell. "Dynamic Waveform Design for Target Tracking Using MIMO Radar." Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, 2008.

• B. Manjunath, A. Papandreou-Suppappola, C. Chakrabarti, and D. Morrell. "Computationally Efficient Particle Filtering Using Adaptive Techniques." Sensor, Signal and Information Processing Workshop, Sedona, AZ, 2008.

• B. Manjunath and D. Chakraborty. "Perimeter security using an acoustic sensor network." Research in Interdisciplinary Science and Engineering Symposium – FGSA Annual Student Symposium, ASU, Tempe,

AZ, 2007.

Professional Affiliations & Activities

• Society of Women Engineers (SWE), member

• Institute of Electrical and Electronics Engineers (IEEE), student member

• Sensor Signal and Information Processing (SENSIP) Center, member

• Reviewer of the following papers: IEEE ICASSP (2008 and 2009); DSP Journal (2009); and IEEE DSP/SPE (2008).

• Organizing committee member for IEEE SENSIP workshop (2008).

• Coordinated lab tour and project demonstration for Women in Applied Science and Engineering (WISE-UP) program.

Technical Skills

Proficient in using various programming tools, operating systems, and software programs, such as Mathematica, MATLAB, C, C++, LabVIEW, Verilog, MacOS, Linux, Windows, LATEX, AutoCAD, and Microsoft Office products.

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