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.