About Me

Niraj Kumar, Ph.D.
NLP | Deep Learning | ML | AI | Researcher | Speaker

  • I obtained my Ph.D., (CSE) from IIIT-Hyderabad (July-2015), under the guidance of Dr. Kannan Srinathan and Dr. Vasudeva Varma.
  • Ph.D. Thesis Title: Towards Intelligent Text Mining: Under Limited Linguistic Resources.

Experience ( 8.0+ Years of Industry R&D Experience)

  1. Senior Research Staff and Manager- Samsung Research Institute, Bangalore (India), (May-2020 – to Now). Role: Research work on Conversational AI, NLP, Deep Learning, Machine Learning and Graph Algorithms.
    1. Solving the complex scenarios of conversational AI systems
    2. To be updated….
  2. Scientist III (Senior Scientist), Computer Science & Eng. at Conduent Labs (Bangalore, India), (Apr-2018 to May-2020)
    1. Role: (a) Leadership role, (b) bringing new research projects with strong business alignment, (c) mentoring team members, and (d) conducting high-level R&D works. Achievement (2019-2020)- Got Honor Roll Award from Conduent – For exceeding expectations by demonstrating outstanding attitude and excellent performance.
    2. (Research Projects Details):
  3. Senior Machine Learning Scientist, Phenom People (Dec 2016 to Feb-2018)
    1. Role: (a) Leadership role, (b) bringing new research projects with strong business alignment, (c) mentoring team members, and (d) conducting high-level R&D works.
    2. Research Project details:
      • Developed a novel weighted knowledge graph for (a) Smart B-2-B-2-C hiring, (b) Contextual and (c) Personalized Search.
      • Candidate Social Graph for automatic resource arrangements and supporting business planners and
      • Automatic Job-Highlight System.
  4. Post-Doctoral Researcher at University of California (Davis) (Sep-2015 to Sep-2016);
    • “Automatic identification of taxonomy of knowledge from software engineering documents”.
  5. Research Professional, TCS Innovation Lab, New Delhi (May 2013 to Aug-2015) (Research Project Details):
    • Automatic Plagiarism Detection system (highly effective in the case of paraphrasing and major word re-ordering). (winner of the best paper award 1st place @ CICLing-2014)
    • Automatic text-quality grading system (Effectively grades the quality of E-mails, without relevant background model).
    • Automatic event detection, alignment and prediction system (related to the economic events).
  6. Research Intern; IBM IRL; Bangalore, India (May 2012 – July 2012) (Research Project details):
    • Developed a new system to answer – “Why based questions” with the help of Wikipedia dump.

Achievements

  1. BEST PAPER AWARD (1st place) @ CICLING-2014 – Details: “Niraj Kumar; “A Graph-Based Automatic Plagiarism Detection Technique to Handle The Artificial Word Reordering and Paraphrasing”, A. Gelbukh (Ed.): CICLing 2014, LNCS 8404, pp. 481–494, 2014. (LINK)
  2. IN TOP SYSTEM @ TAC-2011: My system was in the top system for “Automatic Summarization Evaluation Task” at Text Analysis Conference (TAC 2011), organized by National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC-2011. (For details, see My Publications)
  3. IN TOP SYSTEM @ TAC-2010: My system was in the top system for “Automatic Summarization Evaluation Task” at Text Analysis Conference (TAC 2010), organized by National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC-2010. (For details, see My Publications).
  4. Other Recognition: Our Unsupervised Phrase Identification technique for Keyphrase Extraction, has been appreciated by the survey paper published in COLING-2010, Titled: “Conundrums in Unsupervised Keyphrase Extraction: Making Sense of the State-of-the-Art”

Research Interests

My research interests broadly span five areas and more specifically their intersection: Human Language Technology, Deep Learning, Machine Learning, Social Media Mining and Artificial Intelligence.

I am interested in almost every aspect of the above-discussed techniques and have experience in the following areas (including but not limited to):

  • Knowledge Representation: Knowledge Graph Construction, Dynamic Ontology, Dynamic Contextual Search System.
  • Conversational AI: Intent Classification, Slot-Tagging, Out-Of-Domain Detection, Switching the control from Bot to Human, Dialogue Selection and so on.
  • NLP Psycho-linguistic/Analytic Features: Weighted Sentiment Analysis, Sarcasm Detection, Emotion (Anger, Fear, Joy/happiness, & Sadness, etc.) Extraction, Valence, Arousal Dominance Extraction.
  • NLP (related to Social Media): Hate Speech and Hate Target Classifier, Aggression Identification from Text, Automatic extraction of Threat, Insult, Complain and C
  • NLP General: Keyphrase Extraction, Named Entity Extraction, Entity Normalization, Single & Multi-document Summarization (Extract, Abstract and Guided Summarization), Summarization Evaluation, Text Clustering, Classification, Automatic Question Answering, Automatic Plagiarism Detection.
  • Recommendation System.
  • Code Mixed NLP Applications

Other Professional Activities

  1. Program Committee Member: (1) CODS-COMAD2018, 2019, 2020, 2021 (2) ICON 2013, 2016, 2020, 2021.
  2. Reviewed Journal paper: Oxford Journals -> Science & Mathematics -> “Computer Journal”, IEEE ACCESS.
  3. Prepared E-Books: video E-Book on Deep Learning, video E-Book on Machine Learning (to be completed)
  4. Latest Presentation and seminars: (1) Tech Talk @ SRM University

Publications

Patents Granted

  1. Niraj Kumar, Neural network systems and methods for event parameter determination (https://patents.google.com/patent/US20200410321A1/en ).
  2. Niraj Kumar, Neural network systems and methods for target identification from text. Obtained US Patent. (https://patents.google.com/patent/US11017177B2/en )

Refereed journal articles

  1. Niraj Kumar, Bhiman Kumar Baghel, “Smart Stacking of Deep Learning Models for Granular Joint Intent-Slot Extraction for Multi-Intent SLU” has been accepted for publication in IEEE Access. [June-2021]
  2. Niraj Kumar, Kannan Srinathan and Vasudeva Varma; “Unsupervised Deep Semantic and Logical Analysis for Identification of Solution Posts from Community Answers”; “Int. J. of Information and Decision Sciences”,  IJIDS 8(2): 153-178 (2016).
  3. Niraj Kumar, Kannan Srinathan and Vasudeva Varma; “A Graph based Unsupervised N-gram Filtration Technique for Automatic Keyphrase Extraction”; “Int. J. of Data Mining, Modelling and Management”, Vol. 8, No. 2: 124-143, (2016)

Peer-reviewed proceedings

  1. Anant Khandelwal, Niraj Kumar; A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts. COMAD/CODS 2020: 55-64.
  2. Niraj Kumar; “A Graph Based Automatic Plagiarism Detection Technique to Handle the Artificial Word Reordering and Paraphrasing” CICLing 2014, LNCS 8404, pp. 481–494, 2014. (My work @ TCS Innovation Lab; best paper award, 1st place @ CICLing 2014).
  3. Niraj Kumar and Lipika Dey; “Automatic Quality Assessment of documents with Application to Essay grading”; accepted for publication in MICAI-2013. (My work @ TCS Innovation Lab).
  4. Niraj Kumar, Kannan Srinathan, Vasudeva Varma: A Knowledge Induced Graph-Theoretical Model for Extract and Abstract Single Document Summarization. CICLing (2) 2013: LNCS 7817, pp. 408-423.
  5. Niraj Kumar, Rashmi Gangadharaiah., Kannan Srinathan and Vasudeva Varma; “Exploring the Role of Logically Related Non-Question Phrases for Answering Why-Questions”; Accepted for publication in NLDB-2013.
  6. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma;  Using Graph Based Mapping of Co-Occurring Words and Closeness Centrality Score for Summarization Evaluation; A. Gelbukh (Ed.): CICLing 2012, LNCS 7182, pp. 353–365, 2012.
  7. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma;  Using Wikipedia Anchor Text and Weighted Clustering Coefficient to Enhance the Traditional Multi-Document Summarization; A. Gelbukh (Ed.): CICLing 2012, LNCS 7182, pp. 390–401, 2012.
  8. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma; Using Unsupervised System with least linguistic features for TAC-AESOP Task; In: Proceedings of Text Analysis Conference (TAC 2011), National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC-2011.
  9. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma;  An Effective Approach for AESOP and Guided Summarization Task; In: Proceedings of Text Analysis Conference (TAC 2010), National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC 2010.
  10. Niraj Kumar,  Kannan Srinathan and Vasudeva Varma;  Evaluating Information Coverage in Machine Generated Summary and Variable Length Documents; COMAD 2010.
  11. Niraj Kumar, Venkata Vinay Babu Vemula, Kannan Srinathan, Vasudeva Varma:  Exploiting N-gram Importance and Wikipedia based Additional Knowledge for Improvements in GAAC based Document Clustering. KDIR 2010: 182-187.
  12. Niraj Kumar,  Kannan Srinathan and Vasudeva Varma;  Key Fact Extraction from Newswire Articles by Exploiting Local features based weighting and Interaction of sentences,(Published in ICON-2010, length 6-pages)
  13. Niraj Kumar and Kannan Srinathan; A New Approach for Clustering Variable Length Documents,(Published in IEEE IACC-09).
  14. Niraj Kumar, Kannan Srinathan: Automatic keyphrase extraction from scientific documents using N-gram filtration technique. ACM Symposium on Document Engineering 2008: 199-208.

Contact: nirajrkumar@{gmail.com; yahoo.com; rediffmail.com} Ph: +91 8142710442