Education

• Ph.D. in Computer Science, University of Texas at Austin, 2007
• M.S. in Computer Science, University Politehnica of Bucharest, 1999
• B.S. in Computer Science, University Politehnica of Bucharest, 1998

Research Interests

• Machine Learning
• Natural Language Processing
• Music Information Retrieval

Professional Activities

• Associate Editor for IEEE Transactions on Computers, 2024.
• Program co-chair of the International Summer School on Data Science organized by the Bucharest University of Economic Studies in Predeal, 2018-24.
• Standing reviewer for Computational Linguistics, 2021-23.
• Area chair for the NLP Applications track at ACL 2020.
• Co-chair, with Cindy Marling, of the Blood Glucose Level Prediction Challenge at the ECAI 2020 workshop on Knowledge Discovery in Healthcare Data.
• Guest editor of the special issue on Sensor Technologies: Artificial Intelligence for Diabetes Management in the journal Sensors, 2020.
• Area chair for the Applications track at ACL 2019.
• Co-chair, with Cindy Marling, of the Blood Glucose Level Prediction Challenge at the IJCAI 2018 workshop on Knowledge Discovery in Healthcare Data.
• Invited talk at University of Akron on Machine Learning Models for Blood Glucose Level Prediction, October 2017.
• Steven Bethard, Mausam, and I are co-chairs of the ACL-IJCNLP 2015 track on "Information Extraction and Text Mining".
• I was a member of the Senior Program Committee for IJCAI 2013.
• I was a member of the Senior Program Committee for AAAI 2012, in the area of "Natural Language Processing".
• Alex Yates and I co-chaired the ACL HLT 2011 track on "Text Mining and Information Extraction".
• Michael Raymer and I co-chaired the OCCBIO 2010 session on "Data Mining and Machine Learning".
• Vivi, Rada, Evgeniy and I organized the IJCAI 2009 workshop on "User Contributed Knowledge and AI: An evolving synergy".
• Rada, Evgeniy and I organized the AAAI 2008 workshop on "Wikipedia and AI: An evolving synergy".

A comprehensive list of publications is available in Google Scholar.

Selected publications

• Topic-Level Bayesian Surprise and Serendipity for Recommender Systems
  Tonmoy Hasan and Razvan Bunescu
  Proceedings of the 17th ACM Conference on Recommender Systems, September 2023.


• Socratic Questioning of Novice Debuggers: A Benchmark Dataset and Preliminary Evaluations
  Erfan Al-Hossami, Razvan Bunescu, Ryan Teehan, Laurel Powell, Khyati Mahajan, Mohsen Dorodchi
  Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA), July 2023.


• A semantic parsing pipeline for context-dependent question answering over temporally structured data
  Charles Chen, Razvan Bunescu and Cindy Marling
  Natural Language Engineering, October 2021.
  • Extended version of Context-Dependent Semantic Parsing over Temporally Structured Data
    Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), June 2019.


• Adversarial Learning of Expectation and Surprise: Experiments with Geometric Shapes
  Oseremen Uduehi and Razvan Bunescu
  Proceedings of the 12th International Conference on Computational Creativity (ICCC), September 2021.


• Changing the Narrative Perspective: From Deictic to Anaphoric Point of View
  Mika Chen and Razvan Bunescu
  Information Processing & Management, Special Issue on Creative Language Processing, 2021.


• LSTMs and Deep Residual Networks for Carbohydrate and Bolus Recommendations in Type 1 Diabetes Management
  Jeremy Beauchamp, Razvan Bunescu, Cindy Marling, Zhongen Li, Chang Liu
  Sensors, 2021, 21(9).
  Special Issue on Sensor Technologies: Artificial Intelligence for Diabetes Management.


• Hardware-Level Thread Migration to Reduce On-Chip Data Movement via Reinforcement Learning
  Quintin Fettes, Avinash Karanth, Razvan Bunescu, Ahmed Louri, and Kyle Shiflett
  IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, September 2020.


• Learning to Surprise: A Composer-Audience Architecture
  Razvan Bunescu and Oseremen Uduehi
  Proceedings of the 10th International Conference on Computational Creativity (ICCC), Charlotte, NC, June 2019.


• Chord Recognition in Symbolic Music: A Segmental CRF Model, Segment-Level Features, and Comparative Evaluations on Classical and Popular Music
  Kristen Masada and Razvan Bunescu
  Transactions of the International Society for Music Information Retrieval, 2(1), 2018.

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Code

• Python code and data for changing the narrative perspective.
• Python code and data for context dependent semantic parsing.
• Java code for chord recognition in symbolic music.
• Java & C++ packages for semi-supervised mining of functionally related genes.
• Java package for Adaptive Clustering.
• Java package for generalized subsequence kernels.
• Java package for Relational Markov Networks (discrete potentials).

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Datasets

• MIL dataset for relation extraction.
• Question Focus dataset.
• Question Ranking datasets. This work is licensed under a Creative Commons Attribution 3.0 Unported License.
• Wikipedia Sense and Reference datasets.

Courses taught at UNCC

• ITCS 4101: Introduction to Natural Language Processing, Fall 2024
• ITCS 5356: Introduction to Machine Learning, Fall 2024
• ITCS 6156/8156: Machine Learning, Spring 2023

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Courses taught at OU

• CS 6890: Deep Learning, Spring 2020
• CS 4040/5040: Design and Analysis of Algorithms, Spring 2020
• CS 6840: Natural Language Processing, Fall 2019
• CS 4900: Machine Learning, Fall 2019
• CS 6830: Machine Learning, Fall 2016
• CS 6860: Information Retrieval and Web Search, Fall 2013
• CS 3200: Organization of Programming Languages, Spring 2016

In my spare time, I like playing the guitar. I am also learning how to play the piano.

Current

• Erfan Al-Hossami, PhD
• Tonmoy Hasan, PhD
• Justin Smith, PhD
• Youssef Ait Alama, PhD
• Ramit Aditya, MSc
• Aman Waghchoure, BSc

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Alumni

• Oseremen Oscar Uduehi, PhD 2024
• Sampada Sakpal, MSc 2023
• Smita Ramkrishna Nannaware, MSc 2023
• Kristen Masada, MSc 2022
• Mika Chen, PhD 2022
• Quintin Fettes, PhD 2021
• Jeremy Beauchamp, MSc 2021
• Li (Charles) Chen, PhD 2019
• Yi Yu, MSc 2018
• Sadegh Mirshekarian, MSc 2017
• Lijie Xia, MSc 2017
• Hui Shen, MSc 2017
• Xin Ye, PhD 2016
• Chinmaya Naguri, MSc 2016
• Asish Gaddipati, MSc 2016
• Mika Chen, MSc 2011