About Me

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 (Around 9.0 Years of Industry R&D Experience)

Research Manager, Fujitsu India (FRIPL) (APR-2022 to Now). Role. – Working on R&D in the area of – Industry Oriented, AI, Core Deep Learning and Graph Neural Networks
Senior Research Staff and Manager- Samsung Research Institute, Bangalore (India), (May-2020 – to APR-2022). Role: Research work on Conversational AI, NLP, Deep Learning, Machine Learning and Graph Algorithms. Solving the complex scenarios of conversational AI systems
1. Achievements: Accepted Journals/Papers (Others are still in review) –
  - 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]
  - Niraj Kumar, Bhiman Kumar Baghel, “Intent Focused Semantic Parsing and zero-shot Learning for Out-of-Domain detection in Spoken Language Understanding” has been accepted for publication in IEEE Access. [Dec-2021]
2. Filed Three Patents [Two of them got accepted by the company as A-grade Patents, others are still in review]
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):
  - 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 (Got US Patent, https://patents.google.com/patent/US20200410321A1/en)
  - Niraj Kumar and team; An Automatic Hate Target Identification System (Got the US Patent- https://patents.google.com/patent/US11017177B2/en).
  - Niraj Kumar and team; A Deep Learning based Fully Automated Cyber Hate Profiling System (“Awarded by the Company”, Submitted for Patenting process).
  - A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts (Published in CODS-COMAD 2020 )
  - Niraj Kumar and team: Quantification of emotion and sentiment in calls and chats. (Investigation Disclosure Submitted).
  - Technical Contribution: Developed the adverse drug event detection system (an R&D project), won 1st prize in the Conduent’s 3i HUB (Innovate, Implement ant Impact), Initiative. (US Patent Filed – Patent Application Number- 17/718,839)
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.
Post-Doctoral Researcher at University of California (Davis) (Sep-2015 to Sep-2016);
- “Automatic identification of taxonomy of knowledge from software engineering documents”.
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 1^st 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).
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

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)
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)
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).
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

Program Committee Member: (1) CODS-COMAD – 2018, 2019, 2020, 2021 (2) ICON 2013, 2016, 2020, 2021.
Reviewed Journal paper: Oxford Journals -> Science & Mathematics -> “Computer Journal”, IEEE ACCESS.
Prepared E-Books: video E-Book on Deep Learning, video E-Book on Machine Learning (to be completed)
Latest Presentation and seminars: (1) Tech Talk @ SRM University

Publications

Patents Granted

Niraj Kumar, Neural network systems and methods for event parameter determination (https://patents.google.com/patent/US20200410321A1/en ).
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

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]
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).
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

Anant Khandelwal, Niraj Kumar; A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts. COMAD/CODS 2020: 55-64.
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).
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).
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.
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.
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.
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.
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.
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.
Niraj Kumar, Kannan Srinathan and Vasudeva Varma; Evaluating Information Coverage in Machine Generated Summary and Variable Length Documents; COMAD 2010.
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.
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)
Niraj Kumar and Kannan Srinathan; A New Approach for Clustering Variable Length Documents,(Published in IEEE IACC-09).
Niraj Kumar, Kannan Srinathan: Automatic keyphrase extraction from scientific documents using N-gram filtration technique. ACM Symposium on Document Engineering 2008: 199-208.