Jaspreet Singh, Ph.D.

Samsung Research America-Dallas, TX, USA Visa status: U.S. Permanent Resident

Email: acb4zp@r.postjobfree.com Ph: 469-***-****

Summary

Passionate, motivated and creative R&D engineer with 8+ years of solid and well-cited (>300 citations)

work in machine learning, statistical inference, signal processing, detection and estimation theory,

optimization theory

Education

University of California, Santa Barbara, CA, USA

Ph.D. in Electrical & Computer Engineering Dec 2009

M.A. in Statistics Aug 2009

M.S. in Electrical & Computer Engineering Dec 2005

(Graduate GPA: 3.94/4.00)

Indian Institute of Technology, Delhi, India May 2004

B.Tech. in Electrical Engineering GPA: 8.94/10.00 (top 10%)

Work Experience

Staff Research Engineer (Oct 2013-Present), Sr. Research Engineer (May 2010-Oct 2013), Samsung

Research America-Dallas, TX

Selected projects:

- Simulator development (C and statistical signal processing algorithms design (some patented) for

4G systems. Major techniques employed include statistical concepts such as MMSE/ ML detection

- Statistical inference and data analysis for studying feasibility of energy harvesting base stations

- 7 US patent applications (+2 under review), 2 IEEE papers, 2 Samsung Global Tech Conf papers

Assistant Specialist, University of California, Santa Barbara, CA (Jan 2010-Apr 2010)

- Research on algorithm design with low-precision sampling, and target tracking with binary sensors

Doctoral Researcher, ECE Dept., University of California, Santa Barbara, CA (June 2005-Dec 2009)

- Machine Learning:

-Bayesian target tracking with binary sensing. Developed a particle filtering algorithm (Monte Carlo

algorithm) that provided excellent tracking performance, even with binary sensing

-Event-based distributed data compression (K-means algorithm) for sensor networks

- Information Theory & Signal Processing:

-Developed theory and signal processing algos for communication with quantized sampling.

Extensive use of statistical signal processing, non-linear optimization and probability theory

Engineering Intern, Qualcomm Inc., Bridgewater, NJ (June-Sept 2008)

Algorithms for automatic gain control & timing synch in a peer-to-peer communication system

Visiting grad student, EECS Dept., Massachusetts Institute of Technology (MIT) (Jul-Aug 2007)

Distributed data compression for sensor network applications

Summer Intern, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland (May-July 2003)

Active damping of vibrations using a piezoelectric actuator and digital control

Computing Skills

Programming Languages: C/C++, Matlab/Octave, Python, SQL Platforms: Linux, MS-Windows

Other Software: Latex, MS Office

Awards and Honors

- 320+ research citations, as of Jan 2013 (source: Google scholar)

- Individual achievement award for "many outstanding contributions", Samsung Research, 2012

- Nominated for 2010 Lancaster Award, UCSB (for best PhD thesis in Engg and Sciences)

- Paper at IPSN 2007 cited more than 140 times; listed amongst “the best and most influential papers in

sensor networking over the last 8 years or so” by Prof. Matt Welsh, Harvard University, 2009

- National Talent Scholarship, Govt of India, 1998-2004 (most prestigious high school scholarship in India)

- IIT Dean’s Honor, Fall 2000 & Spring 2001 (top 7% in institute), Fall 2002 (top 2 students in elec engg)

- All India Rank 128 (top 0.1 %), IIT joint entrance examination, 2000

- Rank 3 in Senior Mathematics Olympiad, Delhi Region, 1998 (Consequently, one of the only 4 students

from Delhi region selected for the nurture program for Indian National Mathematics Olympiad)

- Qualified for Indian National Physics and Chemistry Olympiads, 1999 (top 200 students in the country)

Selected Coursework

Data Compression Matrix Analysis & Linear Algebra Digital Signal Processing

Stochastic Processes Pattern Recognition Computer Networks

Image Processing Error Correcting Codes Detection & Estimation Theory

Information Theory Data Structures Probability Theory - I, II, III

Statistical Theory - I, II, III Measure Theory Convex Optimization

Vector Space Optimization Non-Linear Optimization

[Recently completed Prof. Andrew Ng’s online Machine Learning course (with 100% score): Sound

knowledge of (large scale) supervised & unsupervised learning algorithms, anomaly detection systems,

and recommendation systems]

Publications & Patents

Journal: 3 IEEE/ACM Transactions papers (All as first author)

Magazine: 1 IEEE Magazine article (co-author)

Conferences: 11 IEEE/ACM Conf papers (8 as first author)

Patents: Filed 7 US patent applications (6 as first inventor), 2 disclosures under internal review

Professional Service

Invited Technical Reviewer: IEEE Trans on Information Theory, IEEE Trans on Signal Processing, IEEE Trans

on Mobile Computing, and several other journals and conferences

References

Available on request

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