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Data Computer Science

Overland Park, Kansas, United States
October 27, 2016

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Kesav Kancherla

***** * ***** *** *** *

Overland park, KS 66210



Qualified data scientist seeking a data analyst position with 8 years experience in modeling, analyzing & testing large structured and unstructured data sets.


Data Mining Specialist with over 8 years of experience in data mining, data extraction, text mining, business intelligence and machine learning algorithm development and implementation.

Predictive Analytics and Data Mining expert - using MATLAB, R, Python, Weka, CLUTO, LibSVM and SAS to improve understanding of the analytical result.

Validating analysis and model predictions using SEMMA methodology (Sample, Explore, Modify, Model and Assess) to make sure the conclusion or analysis are the right ones and not spuriously or haphazardly conducted.

Knowledge in modeling and analyzing large data, building, deploying and maintaining data support tools.

Expertise in building data models using machine learning techniques for Classification, Regression, Clustering and Associative mining.

Experience in statistical data analysis like Chi-square, T-test; Dimensionality reduction methods like PCA, LDA and feature selection methods.

Expertise in handling in complex SQL queries and validating the output.

Proficiency in coding programming languages C, C++ and knowledge of Java, JSP and PHP.

Knowledge of big data analysis using Hadoop and MapReducer, Hive, Spark, NoSQL, HBASE, Pig and Cassandra.

Published & presented 16 research papers and journals about data mining tools and techniques.

Expertise in research and development of software tools.

Demonstrated excellent problem solving, leadership and communication skills.


Data Mining Tools: Matlab, R, Octave, Weka, CLUTO, CART, LibSVM, RapidMiner, SAS, FASTA, Tableau

Languages and Technologies: C, C++, Python, Java, JSP, MySQL, XML, XSL, XSLT, XPath

Other Tools:

Malware: UPX, PEiD, BinText,

Network analysis: Nmap, Look@LAN, Nessus, Metasploit


Data Scientist, May 2015 – Present

DST Systems

Record Linkage and de-duplication of multiple large databases.

Apply pattern matching and machine learning techniques for identification of anomalies.

Perform segmentation and build recommender systems for users.

Research Scientist, August 2010 – May 2015

Institute for Complex Additive Systems Analysis (ICASA)

Developed Visualization techniques like Byte plot and Markov plot for Malware detection.

Used Byte plot and Markov plot for Packer Identification problem.

PCA and Chi square algorithms are used for the feature analysis.

Performed data extraction and cleaning of large datasets.

Researched and published papers on Malware and Phishing detection using Visual analytics.

Bioinformatics developer, August 2008 – August 2010

Biomoda, Inc

Designed and implemented algorithms for nucleus segmentation and features extraction.

Performed Multi spectrum analysis for Lung cancer detection.

Associative Mining - Identified important rules for Lung cancer detection.

Provided training in Tableau visualization tool.

Multimedia Forensics, January 2007 – August 2010

New Mexico Institute of Mining and Technology

Performed Video Steganalysis using Motion estimation and Discrete Cosine Transform (DCT) based features.

Crafted a Video Forgery detection tool using noise residue.

Designed and developed Image steganalysis tool using Calibration and High order features.

Developed a Digital Watermarking Tool for MPEG videos using motion vectors.

Information Security Analyst - StrikeTeam, Summer 2007-2010

Computational Analysis and Network Enterprise Solutions (CAaNES)

Assessed and documented the security posture of Networks.

Performed digital forensics analysis including collection, recovery and preservation.

Teaching Assistant - January 2007 – May 2009

New Mexico Institute of Mining and Technology

Worked as teaching assistant for Algorithms and Data structures in C, Computer System Organization and Digital Image Processing.

Mentored classes, grading, answering students’ questions, test preparation, project evaluation and solving problems.


PhD in Computer Science (2009 – 2015)

New Mexico Institute of Mining and Technology, New Mexico

CGPA: 3.76

Masters (M.S.) in Computer Science with IT (2007 – 2009)

New Mexico Institute of Mining and Technology, New Mexico

CGPA: 3.79

Bachelor of Technology in Electronics and Communication Engineering (2002 – 2006)

Andhra University, India

CGPA: 3.5


Big Data Specialization, University of California, San Diego (2015 – 2016)


1.Kesav Kancherla and Srinivas Mukkamala, “Packer Identification Using Byte plot and Markov plot ”, Journal of Computer Virology and Hacking Techniques, Modified Version under review 2014.

2.Kesav Kancherla and Srinivas Mukkamala, “Image Visualization based Malware Detection,” IEEE Symposium Series on Computational Intelligence SSCI, 2013.

3.Kesav Kancherla and Srinivas Mukkamala, “Early Lung Cancer Detection using Nucleus Segmentation based Features,” International Conference on Machine Learning and Applications ICMLA, 2012.

4.Kesav Kancherla and Srinivas Mukkamala, “Block Level Video Steganalysis Scheme,” International Conference on Machine Learning and Applications ICMLA, 2012. 651-654

5.Kesav Kancherla and Srinivas Mukkamala: “Feature Selection for Lung Cancer Detection Using SVM Based Recursive Feature Elimination Method,” European Conference on Evolutionary Computation, Machine Learning and Data Mining in Computational Biology EvoBIO, 2012. 168-176

6.Kesav Kancherla and Srinivas Mukkamala, “Novel Blind Video Forgery Detection Using Markov Models on Motion Residue” Asian Conference on Intelligent Information and Database Systems ACIIDS (3) 2012. 308-315

7.Kesav Kancherla and Srinivas Mukkamala: "Phishing Webpage Detection Using Block Similarities AND LOGO Detection," International Association for Development of the Information Society (IADIS) International Conference on Applied Computing (AC) 2011.

8.Kesav Kancherla and Srinivas Mukkamala "Lung cancer detection using labeled sputum sample: multi spectrum approach," International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems IEA/AIE 2011.

9.Madhu K. Shankarapani, Kesav Kancherla, Subbu Ramamoorthy, Ram S. Movva and Srinivas Mukkamala, “Kernel machines for malware classification and similarity analysis,” Computational Intelligence for Privacy and Security, Springer, 2012.

10.Kesav Kancherla and Srinivas Mukkamala "Detection of YASS Using Calibration by Motion Estimation," 6th International Conference on Information Warfare & Security ICIW 2011.

11.Madhu K. Shankarapani, Kesav Kancherla, Subbu Ramamoorthy, Ram S. Movva, Srinivas Mukkamala: “Kernel machines for malware classification and similarity analysis,” International Joint Conference on Neural Networks IJCNN 2010: 1-6

12.Kesav Kancherla, Raveesh Chilakapati, Divya Suryakumar, John Cousins, Constance Dorian, and Srinivas Mukkamala, “Lung Cancer Detection and Classification Using Microarray Data,” International Conference on Bioinformatics & Computational Biology BIOCOMP 2009. 477-488

13.Kesav Kancherla and Srinivas Mukkamala: “Video Steganalysis using Spatial and Temporal Redundancies,” International Conference on High Performance Computing & Simulation, HPCS 2009

14.Kesav Kancherla, Srinivas Mukkamala, aveesh aveeshti and John Cousins; “Labeling of Cancer Cells in Sputum for the Early Detection of Lung Cancer Using Tetrakis Carboxy Phenyl Porphine (TCPP),” Indian International Conference on Artificial Intelligence IICAI 2009: 1503-1518

15.Kesav Kancherla and Srinivas Mukkamala: “Non Intrusive and Extremely Early Detection of Lung Cancer Using TCPP (Biomoda Lab Cultured Lung Cancer Data),” 13th World Conference on Lung Cancer WCLC 2009.

16.Kesav Kancherla and Srinivas Mukkamala, “Video steganalysis using motion estimation,” International Joint Conference on Neural Networks, IJCNN 2009: 1510-1515

17.Kesav Kancherla, Raveesh Chilkapatti, Srinivas Mukkamala, John Cousins and Connie Dorian “Non Intrusive and Extremely Early Detection of Lung Cancer Using TCPP,” International Multi-Conference on Computing in the Global Information Technology - ICCGI, 2009

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