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Abhijeet Mohapatra
Ph.D Candidate, Computer Science Dept.,
Stanford University
abhijeet@stanford.edu
Curriculumn Vitae
Research:  Aggregates in Logic Programming
Advisor:  Michael Genesereth
   
Development

Worksheetshttp://worksheets.stanford.edu

A platform that enables users to build worksheets i.e. create dynamic, interactive webpages in a DIY fashion (akin to creating spreadsheets).
 

In our model for creating worksheets, the interactivity and the dynamics of the worksheet are embodied within the worksheet as logical formulas, similar to formulas in a spreadsheet. Our platform also enables the creation and management of workbooks of worksheet submissions of the same type, and workspaces that integrate heterogenous worksheets.
 

Dexterhttp://dexter.stanford.edu

A browser-based, domain-independent, (structured) data explorer.

 

Dexter's purpose is enabling end-users to explore accessible data (e.g. local files, public apis, accessible databases, webpages) in an ad-hoc, DIY fashion (e.g. Show me all senators who have a DUI record), to query the data with higher expressivity than that is directly supported by the data sources. Data processing in Dexter is carried out on the client side - because you love your data and we don't want it!

 

Merlinhttp://stanford.edu/~abhijeet/merlin

A system to automatically design game visualizations.

Merlin's goal is to bring humans into the General Game Playing loop by providing different visualizations to play the games and strategize, and to help game artists to implove their game visualizations. Trifecta is a visualization of standard Tic-Tac-Toe that was generated by Merlin.
 

TPrimehttp://logic.stanford.edu/tprime
A novel UI for browsing, and aggregating relational tables on smaller displays.
 

TPrime enables users to aggregate columns in a table by zooming out ( - ), or explore the aggregated values by zooming in ( + ). TPrime also enables organization of a table's content along different axes. 

 

Research Publications
Update Policies
Australasian Joint Conference on AI, 2016
Abhijeet Mohapatra, Sudhir Agarwal, and Michael Genesereth
 
Invariant Projections in Games 
Global Conference on AI (GCAI), 2016
Abhijeet Mohapatra, Bertrand Decoster, Sudhir Agarwal, and Michael Genesereth
paper
 
Smart Forms 
AAAI Fall Symposium, 2016
Sudhir Agarwal, Abhijeet Mohapatra, and Michael Genesereth
 
Automating the Design of Game Visualizations 
Technical Report, 2015
Abhijeet Mohapatra
 
Rule-Based Exploration of Structured Data in the Browser 
RuleML, 2015
Sudhir Agarwal, Abhijeet Mohapatra, and Michael Genesereth
 
Raising Authorization Awareness in a DBMS 
Conference on Innovative Database Systems Research (CIDR), 2015
Abhijeet Mohapatra, Ravishankar Ramamurthy, and Raghav Kaushik
 
Dexter: Plugging-n-Playing with Data Sources in Your Browser
AAAI Workshop on Semantic Cities, 2014
Abhijeet Mohapatra, Sudhir Agarwal, and Michael Genesereth
 
Incremental Maintenance of Aggregate Views
Foundations of Information and Knowledge Systems (FoIKS), 2014 
Abhijeet Mohapatra, and Michael Genesereth
 
An Incremental Algorithm to Optimally Maintain Aggregate Views
Logic for Programming, AI and Reasoning (LPAR), 2013 
Abhijeet Mohapatra, and Michael Genesereth
 
Reformulating Aggregate Queries using Views
Symposium on Abstraction, Reformulation, and Approximation (SARA), 2013 
Abhijeet Mohapatra, and Michael Genesereth
 
Aggregates in Datalog under Set Semantics
Technical Report, 2012
Abhijeet Mohapatra, and Michael Genesereth
 
Incrementally Maintaining Run-length Encoded Attributes in Column Stores 
International Database Engineering and Applications Symposium (IDEAS), 2012 
Abhijeet Mohapatra, and Michael Genesereth
 
Optimal Sort Ordering in Column Stores is NP-Complete
Technical Report, 2009
Abhijeet Mohapatra
 
Database techinques in crowd simulations and the scheduling problem in SDF graphs
Undergraduate Thesis, 2008
Abhijeet Mohapatra
Advisor: P. P. Chakrabarti
 

Capturing safety properties of stream queries in a temporal logic framework 
Indian Academy of Sciences Fellowship, 2006
Abhijeet Mohapatra, R. K. Shyamasundar
 

Inventor Profile
Method and System for Database Storage Management 20130097127
A technique to incrementally update compressed relations in column stores. A compressed attribute is updated in time that is logarithmic in the number of the distinct values of that attribute. Batch updates can be performed in time that is constant per updated tuple. No technique can perform faster updates in an asymptotic sense.
 
Optimizing Fine Grained Access Control using Authorization Indexes 20120330925
Architecture that is an index mechanism which optimizes complex queries that result from enforcing fine grained access control. The architecture addresses the problem of efficient query evaluation in the presence of fine grained access control.
 
Efficient Database Compression 20120150877
A method for compressing a database relation by leveraging an optimal ordering of tuples and composition of compression operators.
 
Internships

Auto-Admin Project

Microsoft Research, Redmond, Summer 2010
Supervisor: Ravishankar Ramamurthy
- Proposed and implemented a mechanism to optimize fine-grained access control in database queries. For a variety of authorization policies, an order of magnitude speed-up was observed on TPC-H benchmark. (USPTO#: 20120330925)
 

Auto-Admin Project
Microsoft Research, Redmond, Summer 2009
Supervisor: Ravishankar Ramamurthy
- Proposed and implemented an extensible framework to compress database relations by composing compression techniques. The compression achieved on syntenthic as well as real datasets using our framework was an order of magnitude larger than state-of-art compressors such as WinZip and xMill. (USPTO#: 20120150877)
 
Scalable Games Project
DB Group, Cornell University, Summer 2007
Supervisors: Johannes GehrkeAl Demers and Walker White
- Proposed a novel architecture which decouples the sequencial modules in a traditional game loop.
- Proposed a new algorithm for collision-free navigation in crowd simulations.
 
IBM Research Lab, New Delhi, Summer 2006
Supervisor: R. K. Shyamasundar
- Developed a formal model to answer continuous queries on complex event streams in the temporal logic framerwork of Lustre. 
 
Teaching
CS 157: Computational Logic (Fall 2014) at Stanford and the corresponding MOOC: Introduction to Logic
 
CS 157: Computational Logic (Fall 2010)
 
Presentations
Worksheets
Logic and Collaboration for Intelligent Applications
2017 
 
Jabberwocky
Stanford Computation + Journalism Symposium
2016
 
Automating the Design of Game Visualizations
General Game Playing Competition, AAAI 
2015
Trifecta Game 
 
Plug & Play with Data Sources in your Browser with Dexter
Stanford CS Annual Affiliates Meeting
2014
 
Digital Department
Stanford CS Annual Affiliates Meeting
2013
 
Efficiently Updating Column Stores
Stanford CS Annual Affiliates Meeting
2012
 
Course Projects
Item-basket Revenue Maximization, 2009
CS 322, Supervisor: Jure Leskovec
 
Towards a hybrid approach to Netflix Challenge, 2009
CS 345A, Supervisor: Jeffrey D. Ullman

Analysis of Netflix Data
 

Affiliations
Stanford Logic Group, Infolab
 

Artwork