Lydia Manikonda

From Msplacements

Url: http://web.iiit.ac.in/~lydia
E-mail: lydia@research.iiit.ac.in
Contact No: +91 9989035417

Career Objective

  • Seeking a challenging position at a leading development center to learn and deliver something of value mutually

Education

  • MS by research(CSE), IIIT-Hyderabad, August 2010(Expected)
  • BTech(CSE), International Institute of Information Technology, Hyderabad CGPA - 8.23
  • Senior Secondary, Narayana Junior College, Nellore (I.P.E April, 2004) Percentage - 94.8%
  • Secondary, Adarsh Public School, Tenali, Guntur Dist, AP (S.S.C March, 2002) Percentage - 89.9%

Academic & Research Experience

  • Working as a Teaching Assistant for Data Mining and Data Warehousing course under Prof.Kamalakar Karlapalem, IIIT Hyderabad (Monsoon '09)
  • Worked as a Teaching Assistant for Intro to Medical Informatics course under Mrs.Ratna Saripalli, Microsoft Hyderabad(Spring '09)
  • Worked as a Teaching Assistant for Compilers course under Prof.Govinda Rajulu, IIIT Hyderabad (Monsoon '08)
  • Worked as a Research Assistant during the Summer (May-Jul'08) under Prof.Sanjay Chawla in the School of Information Technologies, University of Sydney, Sydney, Australia.

Academic Achievements

  • Dean’s award for academic excellence for the 5th and 6th semesters
  • AIR of 1352 in AIEEE-2005, state rank of 906 in EAMCET-2005

Workshops and Conferences attended

  • 14th International Conference on Management of Data (COMAD 2008) held at IIT Bombay, India
  • The 3rd International Conference on Natural Language Processing, (IJCNLP 2008) held at Hyderabad
  • Twentieth International Joint Conference on Artificial Intelligence (IJCAI 2007) held at Hyderabad

Course work

    Computer Organization, Operating Systems, DBMS, Algorithms, Theory of Computation, Compilers, Computer Networks, Software Engineering, Data Mining and Data Warehousing, Web Data and Knowledge Management, Data Compression, Special Topics in Data Mining, Information Extraction and Retrieval, Computer Graphics, Artificial Neural Networks, A course on Medical Informatics

Areas of Interest

  • Data Mining
  • Information Extraction and Retrieval
  • Algorithms

Skill Set

  • Operating Systems: Windows, Linux
  • Programming Skills: C, C++, Java
  • Database Technologies: Microsoft SQL Server, mysql, Oracle9i
  • Scripting Languages: Shell, Python, Perl
  • Web Technologies: HTML, PHP, CGI, Java Script
  • Software packages: Weka, Matlab
  • Miscellaneous: R, Lex, Yacc, Protege

Projects

  • Survey Mining(on-going)
    National Institute of Nutrition being a premier research institute of India has a vision to achieve optimal nutrition of vulnerable segments of population such as women of reproductive age, children, adolescent girls and elderly. They collect a lot of survey data on which we are trying to use the techniques of Data Mining to get interesting results which are helpful.
    Guide: Dr. Vikram Pudi, Assistant Professor, Center for Data Engineering, IIIT Hyderabad.
  • Fast and Efficient Document Indexer and Retrieval Engine for a large corpus
    A document indexer which, given a query displays the documents efficiently. This system works with Boolean queries too. We are currently using the Wikipedia dump organized in subfolders with 2+million documents and also the TFIDF and probabilistic Model scoring function. System supports up to 20 fielded keywords as part of the query.
    Guide: Dr. Vasudeva Varma, Associate Professor, Search and Information Extraction Laboratory, IIIT Hyderabad.
  • Profit Mining
    Given a particular transaction made by a customer along with the past transactions made by the customers, profit mining model not only recommends the customers particular products but also satisfy both the Buyer and Seller by keeping Profit as the main consideration.
    Guide: Dr. Vikram Pudi, Assistant Professor, Center for Data Engineering, IIIT Hyderabad.
  • Creating a BOT for ARIMAA game
    Arimaa is a game almost similar to chess with a branching factor very high than that of chess. We built an efficient BOT to play Arimaa using the strategy “Continuous learning from previous games and Automatic Improvement” while exploiting the human strategies in playing any game as a part of an online multi player World Championship. Reference: http://arimaa.com
    Guide: Dr. Vikram Pudi, Assistant Professor, Center for Data Engineering, IIIT Hyderabad.
  • Outlier Detection Using WEKA
    Weka is a tool kit which is the collection of machine learning algorithms for data mining tasks. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Tools for Outlier Detection have been developed which will be soon released in its new version.
    Guide: Dr.Sanjay Chawla, Assistant Professor, School of IT, University of Sydney, Sydney
  • Efficient Mining of Frequent Item sets
    To mine the Maximal Frequent Item sets from a given database of huge number of transactions in a very efficient manner by using the Graph-Based algorithms.
    Guide: Dr. Kamalakar Karlapalem, Professor, Center for Data Engineering, IIIT Hyderabad.
  • other
    • Mining interesting patterns from e-sagu Dataset
    • Information Extraction for Disaster Technology
    • Interactive GUI for Nagarjuna University’s results using Java servlets


Extra Curricular

  • Coordinated/Volunteered for Excitement of Research (EXOR)-08, 07, 06, 05 held at IIIT Hyderabad
  • Teaching poor kids in the near by slum areas of my college
  • A member of my Church Choir
  • Received many prizes in Sports and drawing competitions
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