Nidhi Goyal
Assistant Professor
nidhi.goyal@mahindrauniversity.edu.in
Dr. Nidhi Goyal is Assistant professor in the Department of CSE at Ecole Centrale School of Engineering. She has completed her Ph.D (CSE) from IIIT-Delhi. She is advised by Prof. Ponnurangam Kumaraguru (PreCog, IIIT-H), Dr. Raghava Mutharaju (KRaCR, IIIT-Delhi) and Dr. Niharika Sachdeva from InfoEdge India Limited (Naukri.com). She has received the prestigious Prime Minister Fellowship for Doctoral Research (PMRF-DR) while working in collaboration with Naukri.com. She is a recipient of ACM India Anveshan Setu Fellowship during her PhD. She has been selected among 50 young Indian and International researchers for ACM Pingala interactions in computing, February, 2024. This event is hosted by Infosys Mysore Campus. She is also IRM certified Global Level 1 Professional on Enterprise Risk Management.
She has served as PC Member for many top-tier conferences such as CIKM, TheWebConf2023-Companion, and SEMREC; reviewer for DASFAA, ICANN, and PeerJ ; sub reviewer for AAAI, WWW, CODS-COMAD, ESWC, ICWSM, ICKG, ISI.
She has received many travel grants (Microsoft Research Travel Grant for EACL, ACML, CODS-COMAD, ACM SIGWEB, ISWC, IndoML) during her PhD for conference travels. She served as a Social Media Chair at Fourth International Conference on Emerging Techniques in Computational Intelligence, ICETCI 2024. She has participated in research weeks and symposiums such as Google Research Week, Indo-ML, ACM-ARCS and SIR.
Ph.D.
- Ph.D. in Computer Science, IIIT-Delhi (2018-2024)
M.Tech
- Masters in Computer Science (M.Tech), GJUST (2014-2016)
B.Tech
- Bachelors in Information Technology (B.Tech), GJUST (2010 –2014)
Present
- Dr. Nidhi Goyal is an Assistant Professor in the Department of CSE at École Centrale School of Engineering
2018-2022
- She has prior industry experience working as a Data Science Intern at Naukri.com (2018-2022) and R&D associate with Ensologic Ecommerce Limited (2022-2023) during her PhD. She has also served as an Industry Expert for Third-year Data Science and AIML specialization students at NorthCap University, Gurgaon.
- She has overall teaching experience working as an Assistant professor at USICT, Gobind Singh Indraprastha university (GGSIPU), New Delhi and Dronacharya College of Engineering (DCE), Gurgaon and Coaching (GATE EASY and Brainstorm Achiever, New Delhi) to teach GATE/UGC-NET students (2016-2018).
- She has been teaching assistant for the following courses:
- Online Privacy Course
- Natural Language Processing for PGDDS&AI
- Foundations to Computer Security
- Privacy and Security in Online Social Media
- Designing Human-Centred Systems, NPTEL,
- Designing Human-Centred Systems, IIIT-Delhi
- Computer Organisation
- Operating Systems
2016-2018
- She has prior teaching experience as an Assistant professor at Guru Gobind Singh Indraprastha university (GGSIPU), New Delhi and Dronacharya College of Engineering (DCE), Gurgaon (2016-2018). She has been teaching assistant for Online Privacy Course, Natural Language Processing for PGDDS&AI, Foundations to Computer Security, Privacy and Security in Online Social Media, Designing Human-Centred Systems, NPTEL, Designing Human-Centred Systems, and Computer Organisation and Operating Systems. She has also served as an Industry Expert for Third-year Data Science and AIML specialization students at NorthCap University, Gurgaon.
Publications
2024
- Jaglan, K., M. C. Pindiprolu, T. Sharma, A. R. Singam, Goyal, P. Kumaraguru, and U. Brandes. “Tight Sampling in Unbounded Networks”. Proceedings of the International AAAI Conference on Web and Social Media, vol. 18, no. 1, May 2024, pp. 704-16, doi:10.1609/icwsm.v18i1.31345.
- Potta, R., Asthana, M., Yadav, S., Goyal, N., Patnaik, S. and Jain, P., 2024, March. AttriSAGE: Product Attribute Value Extraction Using Graph Neural Networks. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (pp. 89-94).
- Goyal, N., Goel, A., Garg, T., Sachdeva, N., Kumaraguru, P. (2024). Efficient Knowledge Graph Embeddings via Kernelized Random Projections. In: Sachdeva, S., Watanobe, Y. (eds) Big Data Analytics in Astronomy, Science, and Engineering. BDA 2023. Lecture Notes in Computer Science, vol 14516. Springer, Cham. https://doi.org/10.1007/978-3-031-58502-9_14
2023
- Kansal K., Kansal, N., Bavana, S., Vamshi, B., Goyal, N. A Systematic Study on Video Summarization: Approaches, Challenges, and Future Directions. Accepted at NarSUM '23, Proceedings of the 2nd Workshop on User-centric Narrative Summarization of Long Videos In conjunction with ACM MM 2023, Ottawa, Canada.
- Goyal, N., Kalra, J., Sharma, C., Mutharaju, R., Sachdeva, N., and Kumaraguru, P. JobXMLC: EXtreme Multi-Label Classification of Job Skills with Graph Neural Networks. Accepted at Findings of the Association for Computational Linguistics: EACL 2023.
- Goyal, N., Mamidi, R., Sachdeva,N., and Kumaraguru, P. Warning: It’s a scam!! Towards understanding the Employment Scams using Knowledge Graphs. Accepted at ACM India Joint International Conference on Data Science and Management of Data (CoDS-COMAD 2023) YRS track. Bombay, Jan 4 - 7, 2023
2022
- Goyal, N.*, Arora, U.*, Goel, A., Sachdeva,N., Kumaraguru, P. Ask It Right! Identifying Low-Quality questions on Community Question Answering Services . In Proceedings of International Joint Conference on Neural Networks (IJCNN-2022), July 19 - July 23, Padua,Italy
2021
- Goyal, N., Sachdeva, N., Goel, A., Kalra, J., and Kumaraguru, P. KCNet: Kernel-based Canonicalization Network for entities in Recruitment Domain. In 30th International Conference on Artificial Neural Networks (ICANN). 2021.
- Goyal, N., Sachdeva, N., and Kumaraguru, P. Spy The Lie: Fraudulent Jobs Detection in Recruitment Domain using Knowledge Graphs. In 14th International Conference on Knowledge Science, Engineering and Management (KSEM 2021). 2021.
2019
- Goyal, N., Sachdeva N., Choudhary V., Kar R., Kumaraguru P., and Rajput N. Con2KG-A Large-scale Domain-Specific Knowledge Graph. In Proceedings of the 30th ACM Conference on Hypertext and Social Media, pp. 287-288. 2019.
Her Ph.D. research focused on devising novel frameworks for content quality detection (low, ambiguous, fraud, off-topic, inconsistent, incomplete content) on online professional networks and using AI for enterprise, specifically towards real-world applications in recruitment and knowledge sharing domain.
She is also Principal Investigator, Building Brain-Computer Interfaces (BCIs) using deep generative models (2024-2026) funded by Mahindra University, Hyderabad (2024-2026).
Her primary research areas/technologies are:
- Natural Language Processing (NLP)
- Knowledge Graphs (KGs) construction
- Ontology, and Knowledge Graph representations (KR)
- Graph neural Networks (GNNs)
- Machine learning (ML)
- Deep learning (DL)
- Information Extraction (IE), Entity Normalization
- AI and Neuroscience
