Coursework

Graduate Coursework

Fall 2011 -

1) Analysis of Algorithm

Book Referred: Cormen, Leiserson, Rivest & Stein, Introduction to Algorithms (3rd edition), The MIT Press, 2009

2) Data Mining

Book Referred: Pang-Ning Tan, Michael Steinbach & Vipin Kumar, Introduction to Data Mining, Addison Wesley, 2006

Tool used: Weka, Matlab

Reference Link: http://chem-eng.utoronto.ca/~datamining/dmc/data_mining.htm

Reference Link for SOM: http://www.ai-junkie.com/ann/som/som1.html

3) Intro to Artificial Intelligence

Book Referred: Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach (3rd edition), Prentice Hall, 2010

Tool used: Lispworks , GNU Prolog

Reference Link for LISP tutorials: http://paulgraham.com/acl.html

Reference Link: http://www.ai-junkie.com/index.html

Spring 2012 -

4) Foundation of Parallel Computation

Book Referred: Ananth Grama, Anshul Gupta, George Karypis & Vipin Kumar, Introduction to Parallel Computing (2nd edition), Pearson

Tool used: MPICH, CUDA

Reference Link for MPI Programming: https://computing.llnl.gov/tutorials/mpi/#What

Reference Link for OpenMP Programming: https://computing.llnl.gov/tutorials/openMP/

5) Component based Software Development

Book Referred: Richard, & Bill Burke, Enterprise Javabeans 3.1 (6th edition), Ingram Publication, 2010

Tool used: Eclipse, Java

Fall 2012 -

6) Concurrent Software System

Book Referred: Richard H. Carver & Kuo-Chung Tai, Modern Multithreading: implementing, testing & debugging multithreaded Java & C++/PThreads, Win32 programs

POSIX Threads programming: https://computing.llnl.gov/tutorials/pthreads/

Reference Link for Java thread Programming: http://elvis.rowan.edu/~hartley/JavaConcProg/index.html#SEMAPHORES

7) Pattern Recognition

Book Referred: Hastie, Tibshirani & Friedman, The Elements of Statistical Learning

Rogers & Girolami, A first course in Machine Learning

Christopher M. Bishop, Pattern Recognition and Machine Learning, 1st edition, 2006

Tool used: Matlab

Spring 2013 -

8) Theory of Computation

Book Referred: Michael Sipser, Introduction to the Theory of Computation, 3rd edition

Michael Huth & Mark Ryan, Logic in Computer Science, 2nd edition

9) Master Thesis - Using Multi-Task Learning for Large-Scale Document Classification under Prof. Huzefa Rangwala [Link] [pdf]

Fall 2013 -

10) Stochastic Processes

Book Referred: S. Ross, Introduction to Probability Models, 10th edition

11) Data Mining for Multimedia Databases

Book Referred: J. Han, M. Kamber & J. Pel, Data Mining: Concepts and Techniques, 3rd edition, Morgan Kauffmann

Spring 2014 -

12) Mining Massive Datasets

Book Referred: Chuck Lam, Hadoop In Action, Manning Publications

Jimmy Lin & Chris Dyer, Data-Intensive Text Processing with MapReduce, Morgan & Claypool Publishers

13) Quantitative Methods & Experimental Design in CS

Book Referred: Raj Jain, The Art of Computer Systems Performance Analysis, John Wiley, 1991

David Lilja, Measuring Computer Performance: A Practitioner's Guide, Cambridge University Press, 2005

14) Social Networks

Book Referred: D. Easley & J. Kleinberg, Networks, Crowds, & Markets: Reasoning about a Highly Connected World, Cambridge University Press

Fall 2014 -

15) Computer Science Colloquium

16) Nonlinear Optimization/Application

Book Referred: R. Fourer, D. M. Gay, & B.W. Kernighan, AMPL: A Modeling Language for Mathematical Programming. Duxbury Press / Brooks/Cole Publishing Company, 2002

Online course

1) Machine Learning by Prof. Andrew Ng (Stanford) [certificate]

2) Computing for Data Analysis by Prof. Roger D. Peng (John Hopkins University) [certificate]

3) Heterogeneous Parallel Programming by Prof. Wen-mei W. Hwu (University of Illinois) [certificate]

4) Introduction to Theoretical Computer Science by Dr. Sebastian Wernicke [certificate]

5) Introduction to Programming by Prof. Cay Horstmann [certificate]

6) Introduction to Big Data with Apache Spark by Prof. Anthony D. Joseph [certificate]

7) Scalable Machine Learning by Prof. Ameet Talwalkar [certificate]

GTA course (Outstanding Graduate Teaching Assistant - 2013, 2014)

1) Computer Systems Architecture (Spring 2012, Fall 2012, Spring 2013, Fall 2013, Spring 2014)

Book Referred: D. Patterson & J. Hennessy, Computer Organization & Design:The H/w S/w Interface, Revised 4th ed., Morgan Kaufmann, 2010

Tool used: MARS: http://courses.missouristate.edu/kenvollmar/mars/

Reference Link for Programming: http://chortle.ccsu.edu/assemblytutorial/index.html#part1

Reference Link for Cache Mapping: http://www.eecg.toronto.edu/~moshovos/ECE243-07/l26-caches.html

Reference Link for Pseudo instructions & Branches: http://www.cs.umd.edu/class/sum2003/cmsc311/Notes/Mips/pseudojump.html

2) Analysis of Algorithms (Spring 2014)

Book Referred: Jon Kleinberg & Eva Tardos, Algorithm Design, Addison Wesley, 2005

Undergraduate Coursework

Pl. mail me for detailed undergraduate coursework.