shreya rajpal resume

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7/25/2019 Shreya Rajpal Resume http://slidepdf.com/reader/full/shreya-rajpal-resume 1/2 Shreya Rajpal +91-9999805820 [email protected] Education Bachelor of Technology  - Production and Industrial Engineering (8.225/10.0) Expected: May 2016 Minor  - Computer Science (Coursework GPA - 9.235/10.0) Indian Institute of Technology, Delhi Publications [1] Shreya Rajpal, Karan Goel, Mausam. POMDP-Based Worker Pool Selection for Crowdsourcing. CrowdML Workshop, International Conference on Machine Learning (ICML).  Lille, France. July 2015. Relevant Coursework Computer Science : Introduction to Computer Science [topped among 350+ students], Data Structures, Analysis and Design of Algorithms, Artificial Intelligence, Probabilistic Graphical Models Electrical Engineering : Digital Electronics (+ Lab) Industrial Engineering : Probability and Stochastic Processes, Operations Research Research Experience Cost-Quality-Time Optimization in Crowdsourcing [ report  |  slides] with  Prof. Mausam (IIT-Delhi)  July 2015 - Present  Modeled the optimization of a 3-variable reward function, in a multi-agent setting using Markov Deci- sion Processes (MDPs). Agents make online decisions for task pricing, prioritization and termination.  Utilized a Thinned Non-Homogenous Poisson Process to model worker arrivals to the marketplace, with a Discrete Choice Model to estimate task selection.  Exploring the application of Decentralized Partially Observable MDPs (DEC-POMDPs) to this paradigm. Modeling Human Perception for Discovering Consensus Rankings [ report] with  Prof. Aditya Parameswaran (UIUC), Collaborator: Prof. David Forsyth (UIUC)  July 2015 - Present  Proved NP-Hardness for the problem of discovering multiple latent consensus rankings when humans sort a set of items, by reducing from the Minimum Clique Cover problem in graphs.  Conducted experiments on Amazon MTurk to study perception of depth with ambiguous visual cues, by adapting Cornell’s OpenSurfaces interface to our application, and deploying it on Amazon EC2.  Developing a Conditional Random Field model to classify workers based on similarity of perception. Worker Pool Selection in Crowdsourcing [1] [ paper |  poster  |  slides] with  Prof. Mausam (IIT-Delhi)  January 2015 - May 2015  Developed an online task routing algorithm using Partially Observable MDPs (POMDPs), with a novel approach that leverages an organization of workers based on their qualifications. The model systematically trades off push and pull crowdsourced approaches in a single, theoretical framework.  Experiments in simulation and on real Amazon MTurk data demonstrated improvement over baselines.  Accepted at the International Conference on Machine Learning’s CrowdML workshop. Teaching Experience Artificial Intelligence, Undergraduate and Graduate-Bridge Course [website] with  Prof. Mausam (IIT-Delhi)  July 2015 - Present  Developed, implemented and graded 2 assignments on developing AI game bots.  Taught 125+ students concepts in MDPs and POMDPs after creating problem sets for them.  Undertook several one-on-one teaching sessions for a student with a hearing disability.

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7/25/2019 Shreya Rajpal Resume

http://slidepdf.com/reader/full/shreya-rajpal-resume 1/2

Shreya Rajpal

+91-9999805820 [email protected]

Education

Bachelor of Technology  - Production and Industrial Engineering (8.225/10.0) Expected: May 2016Minor  - Computer Science (Coursework GPA - 9.235/10.0)Indian Institute of Technology, Delhi

Publications

[1] Shreya Rajpal, Karan Goel, Mausam. POMDP-Based Worker Pool Selection for Crowdsourcing.CrowdML Workshop, International Conference on Machine Learning (ICML).   Lille, France. July 2015.

Relevant Coursework

Computer Science : Introduction to Computer Science [topped among 350+ students], Data Structures,

Analysis and Design of Algorithms, Artificial Intelligence, Probabilistic Graphical ModelsElectrical Engineering : Digital Electronics (+ Lab)Industrial Engineering : Probability and Stochastic Processes, Operations Research

Research Experience

Cost-Quality-Time Optimization in Crowdsourcing [report   |  slides]with  Prof. Mausam (IIT-Delhi)   July 2015 - Present

•  Modeled the optimization of a 3-variable reward function, in a multi-agent setting using Markov Deci-sion Processes (MDPs). Agents make online decisions for task pricing, prioritization and termination.

•   Utilized a Thinned Non-Homogenous Poisson Process to model worker arrivals to the marketplace,with a Discrete Choice Model to estimate task selection.

•   Exploring the application of Decentralized Partially Observable MDPs (DEC-POMDPs) to this paradigm.

Modeling Human Perception for Discovering Consensus Rankings [report]with   Prof. Aditya Parameswaran (UIUC), Collaborator: Prof. David Forsyth (UIUC)   July 2015 - Present

•   Proved NP-Hardness for the problem of discovering multiple latent consensus rankings when humanssort a set of items, by reducing from the Minimum Clique Cover problem in graphs.

•  Conducted experiments on Amazon MTurk to study perception of depth with ambiguous visual cues,by adapting Cornell’s OpenSurfaces interface to our application, and deploying it on Amazon EC2.

•   Developing a Conditional Random Field model to classify workers based on similarity of perception.

Worker Pool Selection in Crowdsourcing [1] [paper  |  poster   |  slides]with  Prof. Mausam (IIT-Delhi)   January 2015 - May 2015

•   Developed an online task routing algorithm using Partially Observable MDPs (POMDPs), with a

novel approach that leverages an organization of workers based on their qualifications. The modelsystematically trades off push and pull crowdsourced approaches in a single, theoretical framework.

•  Experiments in simulation and on real Amazon MTurk data demonstrated improvement over baselines.•   Accepted at the International Conference on Machine Learning’s CrowdML workshop.

Teaching Experience

Artificial Intelligence, Undergraduate and Graduate-Bridge Course [website]with  Prof. Mausam (IIT-Delhi)   July 2015 - Present

•  Developed, implemented and graded 2 assignments on developing AI game bots.•  Taught 125+ students concepts in MDPs and POMDPs after creating problem sets for them.•   Undertook several one-on-one teaching sessions for a student with a hearing disability.

7/25/2019 Shreya Rajpal Resume

http://slidepdf.com/reader/full/shreya-rajpal-resume 2/2

Internships

Algorithm Performance Metrics for Foreign Exchange Currenciesat Deutsche Bank Center, Mumbai, India    May 2015 - July 2015

•   Developed a performance metric for High Frequency Trading algorithms and utilized this metric toanalyze the performance of frequently used algorithms and find issues with inefficient algorithms.

•  Developed a heuristic for selecting optimal HFT algorithm given trade volume, using the metric.•   Developed an efficient querying scheme using graph pruning algorithms for a massive dataset.

Outlier Detection in Large Datasetsat LIRIS Lab, University of Lyon-1, France    December 2013

•  Implemented a Principal Component Analysis based algorithm for anomaly detection, and analyzedits performance with respect to the state-of-the-art.

Projects

OCR Word Prediction using Conditional Random Fields (CRFs) [report   |  code 1   |  code 2]

•  Performed Variable Elimination on a CRF and used the Min-Fill heuristic to generate a Clique Tree.•   Implemented Sum-Product Message Passing, Gibbs Sampling and Loopy Belief Propagation to find

the Max-Marginal Assignment and also implemented their Most Probable Explanation counterparts.•   Increased model complexity by increasing CRF connectivity to compare algorithm performance.

POS and NER Tagging for Tweets using MALLET [code]

•   Engineered features to improve POS and NER tagging in a CRF model. Grouped similar soundingwords via metaphone similarity to tweets and added Twitter specific features.

•  Studied CRF performance by performing an ablation study by adding features.

Viterbi Algorithm for Genomic Sequences [code]

•  Implemented a Hidden Markov Model to identify CpG islands in Genomic Sequences. Learned modelparameters using Maximum-Likelihood estimation and used the Viterbi Algorithm for prediction.

A Review of Convolutional Codes and the Viterbi Algorithm [paper]

•  Performed a literature survey on the Viterbi Algorithm and its faster, less optimal extensions.•   Compared two popular hardware implementation of the Viterbi algorithm.

AI for Connect M-N-K

•   Created two game bots using Minimax with Alpha-Beta pruning, and Monte Carlo Tree Search.•  Enabled flexible board configuration handling for a general Connect-4 game board.

Skills

Languages:  C/C++, Python, SQL, JavascriptSoftware:  MATLAB, AutoCAD, LATEX

Development:  HTML, CSS, JQuery, Ajax

Activities

•  Institute journalist for the Board of Student Publications.•   Performed stage and street theater for inter-college events.•   Regularly act as master of ceremony for institute-wide events.