Pradap Konda

You can contact me at: pradap@cs.wisc.edu

LinkedIn

Bio

I am a Ph.D. candidate in the Department of Computer Sciences, at the University of Wisconsin-Madison. During my Ph.D., I have interned at WalmartLabs in summer of 2014, and at Johnson Controls in the summer of 2015. Prior to joining UW-Madison, I worked as a senior research engineer for seven years.

Research

I am interested in the broad area of Data Management, and more specifically in Data Integration, Data Science, Machine Learning, Big Data, and Crowdsourcing. My advisor is Prof. AnHai Doan.

During my PhD, I worked on Magellan project which aims to build end-to-end entity matching management systems. Specifically, I worked on developing a solution framework that help data scientists/analysts to come with an EM workflow (involving machine learning, crowd sourcing, etc) and execute the workflow using tools that are built on top of data science stacks.

Publications

  1. MatchCatcher: A Debugger for Blocking in Entity Matching
    H. Li, Pradap Konda, Paul Suganthan G.C, A. Doan
    EDBT 2018 (To Appear)

  2. Human-in-the-Loop Challenges for Entity Matching: A Midterm Report  [Paper]
    A. Doan, A. Ardalan, J. R. Ballard, S. Das, Y. Govind, Pradap Konda , H. Li, S. Mudgal, E. Paulson, Paul Suganthan G.C., H. Zhang
    HILDA 2017

  3. Magellan: Toward Building Entity Matching Management Systems  [Paper]
    Pradap Konda, S. Das, Paul Suganthan G.C., A. Doan, A. Ardalan, J. R. Ballard, H. Li, F. Panahi, H. Zhang, J. Naughton, S. Prasad, G. Krishnan, R. Deep, V. Raghavendra
    VLDB 2016 (selected for research highlight award in SIGMOD)

  4. Magellan: Toward Building Entity Matching Management Systems over Data Science Stacks  [Paper]
    Pradap Konda , S. Das, Paul Suganthan G.C., A. Doan, A. Ardalan, J. R. Ballard, H. Li, F. Panahi, H. Zhang, J. Naughton, S. Prasad, G. Krishnan, R. Deep, V. Raghavendra
    VLDB (Demo) 2016

  5. Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System [Paper],
    Pradap Konda , Arun Kumar, Christopher Re, Vaishanavi Sashikanth
    VLDB (Demo) 2013.

Patents

  1. US 20130238534 : Method and system for prediction and root cause recommendations of service access quality of experience issues in communication networks.

  2. WO Patent WO/2012/047,683 : Method and apparatus for reliable control channel performance.

Open Source Contributions

I have been the main developer of (py_entitymatching) Python package. This package is the prototype of Magellan work that I did as a part of my research. I have been managing the end-to-end development and release process of this package.

This package is currently being used at multiple organizations (such as RIT, Johnson Controls, Marshfield Clinic etc.) and in data science classes at UW-Madison. The package is currently available in PyPI and Conda. Feel free to ping me in case you face any issues with the packages.

Older Publications

  1. Uplink buffer status reporting for delay constrained flows in 3GPP long term evolution
    [Paper]
    Pradap Konda , Vinod Ramachandran, Suresh Kalyanasundaram
    WCNC 2009

  2. Robust channel estimation and detection for uplink control channel in 3GPP-LTE
    [Paper]
    M.R. Raghavendra, Shirish Nagaraj, Pradap Konda, Phil Fleming
    GlobeComm 2009

  3. Lab performance analysis of a 4G LTE prototype
    [Paper] Pradap Konda with many other authors
    WCNC 2009


Last updated: Jan, 27 2018