Lebenslauf und Publikationen Russa Biswas

Education

• 2017 - present: PhD student / Junior Researcher, FIZ Karlsruhe – Leibniz Institute for Information Infrastructure and Karlsruhe Institute of Technology (KIT), Institute of Applied Informatics and Formal Description Methods (AIFB)
• 2013 - 2016: Master of Science in Computer Science, Saarland University, Germany GPA - 1,7
• 2007 - 2011: Bachelor in Technology , Computer Science and Engineering, West Bengal University of Technology, India, GPA - 8.4/10

Masters Thesis

• Russa Biswas: Graph Based Enhancement of Clusters for Effective Semantic Classification of Twitter Text, 2016 [local copy (PDF)]
  Supervisors: Prof. Dr. Dietrich Klakow and Prof. Dr. Vera Demberg

Experience

• Industrial Work Experience
   
  • August 2011 - August 2013: Software Developer - Salesforce.com, Wipro Technologies, India
     
• Research Experience
   
  • December 2016 - April 2017 : Junior Researcher, DFKI and Saarland University, Saarbrücken, Germany
  • July 2016 - October 2016 : Research Assistant , Machine Learning Group, Saarland University, Saarbrücken, Germany
  • April 2015 - June 2016 : Research Assistant, Computational Linguistics Group, Saarland University, Saarbrücken, Germany
  • March 2014 - December 2014 : Student Assistant, Fraunhofer IZFP, Saarbrücken, Germany
     
• Teaching Experience
   
  • June 2017 - October 2017: Teaching Assistant, Information Service Engineering, KIT, Karlsruhe, Germany
  • April 2018 - August 2018: Teaching Assistant, Information Service Engineering, KIT, Karlsruhe Germany
  • October 2018 - March 2019: Teaching Assistant, Project Seminar course Information Service Engineering, AIKIT, Karlsruhe, Germany
  • April 2019 - August 2019: Teaching Assistant, Information Service Engineering, KIT, Karlsruhe, Germany
  • July 2019: Assistant Tutor, International Semantic Web Research Summer School 2019 (ISWS), Bertinoro, Italy
  • October 2015 - April 2016 : Teaching Assistant, Machine Learning Course, Saarland University, Saarbrücken, Germany
     
• Supervision Experience – Bachelor Theses 
   
  • Radina Sofronova: Fine-grained Type Prediction of Entities using Knowledge Graph Embeddings, 2019, DOI: 10.5445/IR/100010000, [local copy (PDF)]

Summer School Organization

• ISWS 2019, International Semantic Web Research Summer School 2019, Poster Track

Program Committees

2021

• CoNLL, The SIGNLL Conference on Computational Natural Language Learning, 2021
• SEM21EU, SEMANTiCS 2021, Research & Innovation Track, 2021
• KGSWC 2021, The third edition of the Iberoamerican conference, The second edition of the Indo-American conference, Research Track, 2021
• CSSA 2021, workshop co-located with ECML-PKDD, 2021
• ESWC 2021, 18th Extended Semantic Web Conference, Research Track, 2021

2020

• CoNLL, The SIGNLL Conference on Computational Natural Language Learning, 2020
• Workshop Chair of DL4KG, Deep Learning for Knowledge Graphs, collocated with the Extended Semantic Web Conference (ESWC 2020), 2020
• Sem20-EU, SEMANTICS 2020 - 16th International Conference on Semantic Systems, Poster & Demo Track, 2020
• IJCAI-PRICAI 2020, 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence 2020
• ECAI 2020, 24th European Conference on Artificial Intelligence 2020, Research Track

2019

• KCap 2019, the 10th International Conference on Knowledge Capture, Research Track
• Semantics 2019, the 15th International Conference on Semantic Systems 2019, Poster and Demo Track

• Machine Learning
• Natural Language Processing
• Information Extraction
• Semantic Web

Zitate

Russa Biswas @ Google Scholar
Russa Biswas @ DBLP
Russa Biswas @Scopus

2022

• R. Biswas; Y. Chen; H. Paulheim; H. Sack, M. Alam: It's All in the Name: Entity Typing Using Multilingual Language Models Preprint available on EasyChair Preprints, No. 7809, 2022; 5 p. https://easychair.org/publications/preprint/BHWG
• R. Biswas,H. Sack, M. Alam: MADLINK: Attentive Multihop and Entity Descriptions for Link Prediction in Knowledge Graphs (Accepted), Semantic Web Journal. [local copy (PDF)].

2021

• R. Biswas, R. Sofronova, H. Sack, M. Alam: Cat2Type: Wikipedia Category Embeddings for Entity Typing in Knowledge Graphs. In The 11th International Conference on Knowledge Capture (K-CAP 2021), Association for Computing Machinery, New York, NY, USA, pp.81-88.  https://doi.org/10.1145/3460210.3493575 [local copy (PDF)]
• R. Biswas, R. Sofronova, M. Alam, H. Sack: Contextual Language Models for Knowledge Graph Completion. In Machine Learning with Symbolic Methods and Knowledge Graphs workshop co-located with ECML PKDD 2021 (ECML PKDD 2021), CEUR workshop proceedings, vol. 2997, CEUR-WS.org, online at http://ceur-ws.org/Vol-2997/paper3.pdf [local copy (PDF)]
• R. Biswas, R. Sofronova, M. Alam, N. Heist, H. Paulheim, H. Sack: Do judge an entity by its name! Entity Typing using Language Models. In: The Semantic Web: ESWC 2021 Satellite Events(ESWC 2021), Poster & Demo Track, pp. 65-70 DOI: 10.1007/978-3-030-80418-3_12 [local copy (PDF), Video, Website].
• M. Alam, R. Biswas, Y. Chen, D. Dessì, G. A. Gesese, F. Hoppe, H. Sack:
  HierClasSArt: Knowledge-Aware Hierarchical Classification of Scholarly Articles. In Proc. of 1st International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K 2021), co-located with The Web Conf 2021, Companion Proceedings of the Web Conference 2021 (pp. 436-440), online at https://dl.acm.org/doi/10.1145/3442442.3451365. [local copy (PDF)]

2020

• G. A. Gesese, R. Biswas, M. Alam, H. Sack:
  A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?, Semantic Web Journal, 12(4), 2020, pp. 617-647. DOI: 10.3233/SW-200404 [local copy (PDF)].
• R. Biswas:
  Embedding based Link Prediction for Knowledge Graph Completion, In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), Doctoral Consortium (CIKM 2020), pp. 3221–3224. DOI: 10.1145/3340531.341812 [local copy (PDF)]
• R. Biswas:
  Embedding based Link Prediction for Knowledge Graph Completion. In Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (ECAI 2020), pp. 69–70. http://hdl.handle.net/10347/23263 [local copy (PDF)].
• R. Sofronova, R. Biswas, M. Alam, H. Sack:
  Entity Typing based on RDF2Vec using Supervised and Unsupervised Methods, In: ESWC 2020: The Semantic Web: ESWC 2020 Satellite Events, Lecture Notes in Computer Science LNCS Vol. 12124, pp. 203 - 207. DOI: 10.1007/978-3-030-62327-2_35 [local copy (PDF)].
• R. Biswas, R. Sofronova, M. Alam, H. Sack:
  Entity Type Prediction in Knowledge Graphs using Embeddings, In Proc. of DL4KG workshop co-located with ESWC 2020, CEUR workshop proceedings, vol. 2635, CEUR-WS.org, online at http://ceur-ws.org/Vol-2635/, [local copy (PDF)].

2019

• G. A. Gesese, R. Biswas, H. Sack:
  A Comprehensive Survey of Knowledge Graph Embeddings with Literals: Techniques and Applications, Workshop on Deep Learning for Knowledge Graphs (DL4KG), co-located with of the 16th Extended Semantic Web Conference (ESWC 2019), CEUR workshop proceedings, vol. 2377, pp. 31-40, CEUR-WS.org, online at http://ceur-ws.org/Vol-2377/), [local copy (PDF)].
• S. Müller, M. Brunzel, D. Kaun, R. Biswas, M. Koutraki, T. Tietz and H. Sack:
  HistorEx: Exploring Historical Text Corpora Using Word and Document Embeddings, in: ESWC 2019: The Semantic Web: ESWC 2019 Satellite Events, Lecture Notes in Computer Science LNCS Vol. 11762, pp. 136 - 140. DOI: 10.1007/978-3-030-32327-1_27  [local copy (PDF)].
• T. Abderrahmani Ghor, E. Agrawal, M. Alam, O. Alqawasmeh, C. D'amato, A. Annane, A. Azzam, A. Berezovskyi, R. Biswas, M. Bonduel, Q. Brabant, C. Bucur, E. Camossi, V. Carriero, S. Chari, D. Fraga, F. Ciroku, M. Cochez, H. Curien, V. Cutrona, R. Dandan, D. Dess, V. Carlo, A. Djebri, M. Van Erp, F. Falakh, A. Izquierdo, G. Futia, A. Gangemi, S. Gasperoni, A. Grall, L. Heling, P. Henri, N. Herradi, S. Issa, S. Jozashoori, N. Juniarta, L. Kaffee, I. Keles, P. Khare, V. Kovtun, V. Leone, S. Li, S. Lieber, P. Lisena, T. Makhalova, L. Marinucci, T. Minier, B. Moreau, A. Moya Loustaunau, D. Nandini, S. Ozdowska, A. De Moura, S. Padhee, G. Palma, P. Del Pozo Jimnez, V. Presutti, R. Reda, E. Rizza, H. Rosales-mndez, S. Rudolph, H. Sack, L. Sciullo, H. Simanjuntak, C. Stomeo, T. Thanapalasingam, T. Tietz, D. Varanka, M. Vidal, M. Wolowyk, M. Zocholl,
  Linked Open Data Validity -- A Technical Report from ISWS 2018, arXiv e-prints, arXiv:1903.12554, 2019 [local copy (PDF)].

2018

• R. Biswas, M. Koutraki, H. Sack:
  Predicting Wikipedia Infobox Type Information using Word Embeddings on Categories, in Proc. 21st International Conference on Knowledge Engineering and Knowledge Management 2018 (EKAW 2018), Poster & Demo Track, p. 29-31, http://ceur-ws.org/Vol-2262/ekaw-poster-27.pdf [local copy (PDF)]
• R. Biswas, M. Koutraki, H. Sack:
  Exploiting Equivalence to Infer Type Subsumption in Linked Graphs, in The Semantic Web: ESWC 2018 Satellite Events Posters & Demo Tracks, Lecture Notes in Computer Science, Vol. 11155, Springer, Cham, pp. 72-76. DOI: 10.1007/978-3-319-98192-5_14 [local copy (PDF)]
• R. Biswas, R. Türker, F. Bakhshandegan-Moghaddam, M. Koutraki, H. Sack:
  Wikipedia Infobox Type Prediction Using Embeddings, in Proceedings of the 1st Workshop on Deep Learning for Knowledge Graphs and Semantic Technologies DL4KGS 2018, co-located with ESWC 2018, CEUR workshop proceedings, vol. 2106, http://ceur-ws.org/Vol-2106/paper6.pdf [local copy (PDF)]

2017

• Öksüz, N.; Biswas, R.; Shcherbatyi, I.; Maass, W.
  Measuring Biosignals of Overweight and Obese Children for Real Time Feedback and Predicting Performance, NeuroIS 2017

• N. Abbas, K. Alghamdi, M. Alinam, F. Alloatti, G. Amaral, et al.: Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019. arXiv pre-prints, arXiv:2012.11936, 2020. [local copy (PDF)]
• R. Biswas, M. Alam, H. Sack: Is Aligning Embedding Spaces a Challenging Task? A Study on Heterogeneous Embedding Alignment Methods, arXiv e-prints,  https://arxiv.org/abs/2002.09247, 2020 [local copy (PDF)].

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