Education

  • Doctor of Philosophy (Ph.D.) Computer Science   [ Fall 2018 - present ]
    The University of Texas at Dallas, TX, USA
    Advisor: Prof. Sriraam Natarajan
  • Master of Science (M.S.) Computer Science   [ Fall 2017 - Spring 2021 ]
    The University of Texas at Dallas, TX, USA
  • Bachelor of Technology (B.Tech.) Information and Communication Technology   [ May 2013 ]
    Dhirubhai Ambani Institute of ICT (DA-IICT), Gandhinagar, India
    Thesis Advisor: Prasenjit Majumder
    Thesis Topic: Language identification for short text in transliterated space

Publications

  1. [C5] Human-guided Collaborative Problem Solving: A Natural Language based Framework,
    Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth, In ICAPS (demo track) 2021.
    paper | video
  2. [W2] RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction (Extended Abstract),
    Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In Planning and RL (PRL) Workshop at ICAPS 2021.
    paper
  3. [C4] A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes,
    Athresh Karanam, Alexander L. Hayes, Harsha Kokel, David M. Haas, Predrag Radivojac, Sriraam Natarajan, In AIME 2021.
    paper | blog | DOI| video | cite
    @inproceedings{KaranamHKHRN21,
       author = {Athresh Karanam and Alexander L. Hayes and Harsha Kokel and David M. Haas and Predrag Radivojac and Sriraam Natarajan},
       title = {A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes},
       year = {2021},
       publisher = {Springer International Publishing},
       pages = {497--502},
       booktitle = {Artificial Intelligence in Medicine},
       isbn = {978-3-030-77211-6},
       DOI = {10.1007/978-3-030-77211-6_59},
       }

  4. [C3] RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction,
    Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli, In ICAPS 2021.
    paper | blog | code | supplemental | DOI | cite
    @article{KokelMNRT21,
       title={RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction},
       author={Kokel, Harsha and Manoharan, Arjun and Natarajan, Sriraam and Balaraman, Ravindran and Tadepalli, Prasad},
       journal={Proceedings of the International Conference on Automated Planning and Scheduling},
       number={1},
       volume={31},
       year={2021},
       month={May},
       pages={533--541},
       url={https://ojs.aaai.org/index.php/ICAPS/article/view/16001},
       }

  5. [W1] Graph Sparsification via Meta-Learning,* contributed talk (4/22 accepted paper)
    Guihong Wan, Harsha Kokel, In Deep Learning for Graphs (DLG) Workshop at AAAI 2021.
    paper | slide | video | cite
    @article{WanK21,
       title={Graph Sparsification via Meta-Learning},
       author={Wan, Guihong and Kokel, Harsha},
       journal={Deep Learning for Graphs (DLG) Workshop at AAAI},
       year={2021}
       }

  6. [C2] A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domain,
    Harsha Kokel, Phillip Odom, Shuo Yang, Sriraam Natarajan, In AAAI 2020.
    paper | blog | code | supplemental | poster | slide | DOI | cite
    @article{KokelOYN20,
       author = {Harsha Kokel and Phillip Odom and Shuo Yang and Sriraam Natarajan},
       title = {A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains},
       journal = {Proceedings of the AAAI Conference on Artificial Intelligence}
       volume = {34},
       number = {04},
       pages = {4460--4468},
       year = {2020},
       month = {Apr.},
       DOI = {10.1609/aaai.v34i04.5873},
       url = {https://aaai.org/ojs/index.php/AAAI/article/view/5873},
       }

  7. [C1] Morpheme Extraction Task,
    Rashmi Sankepally, Komal Agarwal, Harsha Kokel, Prasenjit Majumder, In Forum for Information Retrieval Evaluation (FIRE) 2013.
    paper | DOI | cite
    @inproceedings{SankepallyKAM13,
       author = {Rashmi Sankepally and Harsha Kokel and Komal Agarwal and Prasenjit Majumder},
       title = {Morpheme Extraction Task at {FIRE} 2012-2013},
       booktitle = {Proceedings of the Forum on Information Retrieval Evaluation, {FIRE}},
       pages = {5:1--5:4},
       publisher = {{ACM}},
       year = {2013},
       url = {https://doi.org/10.1145/2701336.2701637},
       doi = {10.1145/2701336.2701637},
       }

Experience

Industry

  • Research Intern, IBM T. J. Watson Research Center, Yorktown Heights, NY, USA   [ Summer 2021 ]
  • ML Intern, Turvo Inc., CA, USA   [ Summer 2018 ]
    Modeled cost estimator that leverages knowledge of the domain experts. Kokel et al. AAAI 2020 was motivated by the work at Turvo.
  • Senior Software Engineer, Amadeus Software Labs, Bangalore, India   [ 2016-17 ]
    Implemented efficient low fare search for Air Canada for elongated period.
  • Associate Technology, Publicis Sapient, Bangalore, India   [ 2013-16 ]
    Provided content management solutions for enhanced digital presence.

Academia

  • Research Assistant, UT Dallas, TX, USA   [ Fall 2018 ]
    Working on DARPA's Communicating with Computers grant
  • Teaching Assistant, UT Dallas, TX, USA   [ Fall 2018 ]
    CS6343 and CS4365, graduate and undergraduate level class of Artificial Intelligence.
  • Research Assistant, DA-IICT, Gandhinagar, India   [ 2012-13 ]
    Worked on Sandhan, a multilingual search engine for 8 Indian languages. Including cross lingual search. I developed the Query Builder for Indian languages with query expansion for relevance judgment.

Technical skills

    Python, Java, C, Shell Scripting, MATLAB, R, Linux/Unix, Git, SQL, Prolog, PDDL, Jupyter.

Projects

Effective Abstraction in Relational RL

Providing state abstraction for better task transfer in taskable reinforcement learning environments using D-FOCI statements. Kokel et al. ICAPS 2021.

Relational Q Learning

Implemented Q-learning for relational domains like blocksworld, where the states are represented using first-order logic predicates. [ code ]

Communicating with Computers

This is a DARPA funded project to build intelligent minecraft agent that can communicate and collaborate with humans through chat to build structures. [ video ]

Knowledge Intensive Gradient Boosting

Leveraging qualitative domain knowledge while learning tree based gradient boosting models to improve predictions in regions where data is noisy or absent. Kokel et al. AAAI 2020.

Learning Sparse Graph for GNN

Used meta-learning techniques to optimize the graph structure for obtaining sparse graph. Wan and Kokel, DLG 2021.

Causal inference from Protein Expression Data

Discovering causal molecular relationships from the evaluation of observational data using do-calculus. More details.

Ja-Walk-ER

Developed an interface that allows users with basic understanding of ER Diagrams to provide search bias for Inductive Logic Programming based. As described in Hayes et al. 2017. [ code ]

Expression Detection

A small project to detect wink and shush expression using OpenCV. [ code ]

RL for Healthcare

Learning polices for management of children on ECMO using batch reinforcement learning techniques. More details.

SRL model for credit default

Learnt and evaluated a statistical relational model for Kaggle Home credit default risk dataset and compared it with propositional models.

Optimization

Implementation of various first-order and second-order gradient methods for optimization. Including Barzilai-Borwein Gradient Descent, Conjugate Gradient Descent, Limited Memory BFGS and Armijo Line-search. [ code ]

ML/AI basket

My basket of Machine Learning and AI algorithms implemented over time. [ code ]

Academic Service

  • Volunteered at AAAI 2021.
  • Reviewed papers for AAAI 2021.
  • Student volunteer at ICDE 2020.
  • Assistant Electronic Publishing Editors for JAIR 2020 - present.
  • Reviewed papers for CODS-COMAD, 2020 and SDM, 2020.
  • Helped organize meeting of Forum for Information Retrieval Evaluation (FIRE), 2018, 2013.
  • Conducted a lab on Information Retrieval in Microsoft Research India & IRSI Pre-FIRE workshop, 2013.
  • Co-organized Morpheme Extraction Task at FIRE 2013.

My Github Contribution

My Github chart