1. ANOOP DOBHAL Email : anoop.dcrust@gmail.com
Contact : +91-9003194690
DOB : October 21, 1986
EDUCATIONAL QUALIFICATION
Examination Board/University Institute Year % / CPI
Post Graduation (M.Tech.)
(PG Specialization : CSE) IIT Bombay IIT Bombay 2014 6.81
Graduation (B.Tech.)
(UG Specialization : CSE) MDU, Rohtak DCRUST, Murthal 2008 67.50%
Intermediate (12th) CBSE GMSSS-19 Chandigarh 2004 65.40%
Matriculation (10th) CBSE HMSSS-10 Panchkula 2002 76.80%
Professional Experience
• July,2014-Present: Associate at Cognizant Technology Solution Private Limited
◦ Risk Analysis of Anonymized Data Sets using Hadoop and Machine Learning
∗ Finding associated risk in terms of sensitive information leak by defining various
risk matrices parameters such as k-anonymity, l-diversity, t-closeness, informa-
tion gain and information loss
∗ Checking the initial anonymized data sets correction level against these risk ma-
trices parameters using CART (Classification and Regression Tree)
∗ Developed MapReduce programs and Pig scripts to parse the data
∗ Used Mapreduce, Pig and Sqoop for calculating various risk values Anonymized
Data Sets
∗ Managed and reviewed Hadoop log files
◦ Network Intrusion Detection using Machine Learning
∗ Given extracted features from TCP data, classifying it into different classes of at-
tack or normal
∗ Performed feature reduction using Correlation Matrix and applied Principle Com-
ponent Analysis to reduce the dimension of features groups (high pair wise cor-
relation)
∗ Used Random Forest and Decision Tree with GMM(Gaussian Mixture Model) for
classification, results are same from both approach with minute differences
∗ Final result is evaluated based on Confusion Matrix of normal(positive) VS at-
tack(negative)
◦ Insurance Policy Renewal Model using Machine Learning
∗ Given various features data, finding whether customer will renew the insurance
policy

2. ∗ Performed sentiment analysis by collecting data from various sources like Face-
book, Twitter
∗ Built model for finding renewal tendency of policies by customer using Neural
Networks
• Feb,2009-May,2011: Worked as Visiting Lecturer at Shree Ram Institute of Technical
Education, Panchkula
◦ Conducted Labs and lectures for C/C++, Java, Data Structure, SQL
M.Tech. Projects
• Adaptive Testing for Classification of Learners and Quiz Questions using Clicker
(Guide: Prof. Deepak B. Phatak)
◦ Given a set of questions, recommending questions to users according to their past
responses
◦ Approach based on Rasch Model
◦ Implemented Collaborative filtering Recommendation System for the adaptive model
• Automatic Music Chords Generation
(Guide: Guide: Prof. G Sivakumar)
◦ Given a music piece as input with several measures, predicted the chords sequence
for melodies
◦ Approach based on Hidden Markov Model
◦ Computed the most likely chord progression using Viterbi Algorithm in Statistic and
Machine Learning Toolbox in MATLAB
• Legal Contract Document Classification
(Guide: Guide: Prof. G Sivakumar)
◦ Given both document structure as well as local document features, classifying the
documents
◦ Vector of TF-IDF weighted indicator features are prepared for both title and body text
separately
◦ Concatenated vector is used as a feature vector for classification using linear kernel
based SVM
• Designed block encryption function
(Guide: Prof. Virendra R Sule)
◦ Designed block encryption function for 32-bit block for enciphering instead of the
original 64-bit enciphering function
◦ Carried out the avalanche tests on the cipher
◦ Generated Stream rank using CTR mode and plot the result of stream rank test
Publications
• Privacy Risk Metrics for Internal and External Threat Analysis- An Enterprise Perspec-
tive
(The 2015 international conference on security and management (SAM’15))
◦ Identity and attribute disclosure of enterprise data is hazardous
◦ Developed a solution to handle multiple sensitive attributes and provide risk profiles
for them based on both insider and external threat sources.

3. Positions of Responsibility
• Teaching Assistantship, IIT Bombay
◦ Computer Programming and Utilization (Prof. Abhiram Ranade, Autumn 2012-13)
Worked as a Lab instructor assisting students to cope up with course pace and was
involved in grading them
◦ Aakash Project (Prof. Deepak B. Phatak, Autumn 2013-14)
∗ Mentor-ship for the project "Optimizing Moodle LMS for Improving User Re-
sponse Time"
∗ Responsible for mentoring interns, assisting students to cope up with course pace
in lab assignments
Courses Taken
• Machine Learning, Introduction to Data Science, Advanced Computer Architecture, In-
troduction to Cryptography and Number Theory, Applied Linear Algebra, Artificial In-
telligence, Implementation Techniques for relational database Systems, Software Archi-
tecture, Decision Analysis and Game Theory
Areas of Expertise
• Programming Languages: C, C++, Java, R
• Scripting Languages: Python, Shell
• Web Technologies: JavaScript, HTML, CSS, JSP, WML, xHTML, XML
• Big Data Ecosystems: Hadoop, Hive, Hbase, Pig, Sqoop, Mahout
• Operating Systems: Linux, Windows
• Database: MySQL, PostgreSQL, Oracle
• Frameworks: Spring, Hibernate, Web Frameworks (Struts, Spring MVC, JAX-WS)
• Development Tools: LATEX, Eclipse, IntelliJ Idea, Net-beans