About Me

I am passionate about Research and Teaching. My goal as a Trainer is to help people become knowledgeable, independent thinkers and researchers. I want to make easy-reach of high-end technologies to common people.

  • I obtained my Ph.D., (CSE) from IIIT-Hyderabad (June-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

(After PhD Thesis work 7.5+ years and 11+ years with PhD Research)
  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.
  2. Scientist III (Senior Scientist), Computer Science & Eng. at Conduent Labs (Bangalore, India), (Apr-2018 to May-2020) 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. (Research Projects Details):
    • Niraj Kumar and Team; Developed Automated BOT-Humanization System for Conduent BOT-DARA – A Conversational AI Research Project (Investigation Disclosure Submitted).
    • Niraj Kumar and team; A Deep Learning based Fully Automatic Crime Volume Prediction System (Filed US Patent, Patent ID – 87979419)
    • Niraj Kumar and team; An Automatic Hate Target Identification System (Filed US Patent- Patent ID – 87979416).
    • Niraj Kumar and team; A Deep Learning based Fully Automated Cyber Hate Profiling System (“Awarded by the Company”, Submitted for Patenting process).
    • Niraj Kumar and team: Quantification of emotion and sentiment in calls and chats. (Investigation Disclosure Submitted).
  3. Senior Machine Learning Scientist, Phenom People (Dec 2016 to Feb-2018) 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. (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
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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”

Publications

Refereed journal articles

  1. 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).
  2. 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. (Download Tool)
  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. (Download Tool)
  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. (Download Tool)
  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.