My research interests have mostly been in the domain of network science and data mining. In specific, I have been looking into the evolutionary dynamics of temporal networks like citation, human communication and author collaboration. More recently, I have been interested in applying deep neural architectures as well as social science theories to understand human behavior on the Web. I am also working towards developing methods for interpretable, fair and robust Machine Learning.

Google scholar, Dblp, GitHub

Publications:

• Seham Nasr and Sandipan Sikdar. IndMask: Inductive Explanation for Multivariate Time Series Black-box Models. ECAI 2024, Santiago de Compostela, Spain

• Maryam Badar, Sandipan Sikdar, Wolfgang Nejdl and Marco Fisichella. TrustFed: Navigating Trade-offs between Performance, Fairness, and Privacy in Federated Learning. ECAI 2024, Santiago de Compostela, Spain 

• Tobias Schumacher, Marlene Lutz, Sandipan Sikdar and Markus Strohmaier. Properties of Group Fairness Measures for Rankings. ACM Transactions on Social Computing. 2024

• Jingge Xiao, Leonie Basso, Wolfgang Nejdl, Niloy Ganguly and Sandipan Sikdar. IVP-VAE: Modeling EHR Time Series with Initial Value Problem Solvers. AAAI 2024, Vancouver, Canada. Also presented at ICLR 2023 Workshop on Time Series Representation Learning for Health

• Maryam Badar, Sandipan Sikdar, Wolfgang Nejdl and Marco Fisichella. FairTrade: Achieving Pareto-Optimal Trade-offs Between Balanced Accuracy and Fairness in Federated Learning. AAAI 2024, Vancouver, Canada 

• Sandipan Sikdar and Parantapa Bhattacharya. Interpretability of Deep Neural Networks. Ethics in Artificial Intelligence: Bias, Fairness and Beyond. Studies in Computational Intelligence, vol 1123. Springer, Singapore. 2023.

• Manjish Pal, Subham Pokhriyal, Sandipan Sikdar and Niloy Ganguly. Ensuring Generalized Fairness in Batch Classification. Scientific Reports. 2023

• Jan Engler*,  Sandipan Sikdar*, Marlene Lutz and Markus Strohmaier (*equal contribution). SensePOLAR: Word sense aware interpretability for pre-trained contextual word embeddings. EMNLP (findings) 2022, Abu Dhabi, UAE. Also presented at BlackboxNLP 2022, IC2S2 2023 (Awarded one of the two best parallel talks)

• Hussain Hussain*, Meng Cao*, Sandipan Sikdar, Denis Helic, Elisabeth Lex, Markus Strohmaier, and Roman Kern (*equal contribution). Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks. IEEE ICDM 2022, Orlando, Florida, USA 

• Jens Helge Reelfs, Timon Mohaupt, Sandipan Sikdar, Markus Strohmaier and Oliver Hohlfeld. Interpreting Emoji with Emoji: 🏖️ => ☀️😎🌊 . EMOJI@NAACL 2022, Seattle, Washington

• Sandipan Sikdar, Florian Lemmerich and Markus Strohmaier. GetFair: Generalized Fairness Tuning of Classification Models. ACM FAccT 2022, Seoul, South Korea. 

• Sandipan Sikdar, Rachneet Singh Sachdeeva, Johannes Wachs, Florian Lemmerich and Markus Strohmaier.  The Effects of Gender Signals and Performance in Online Product Reviews. Frontiers Big Data - Data Mining and Management - User Modeling and Recommendation (special issue) (fdata.2021.771404 ). 2021

• Sandipan Sikdar*, Parantapa Bhattacharya* and Kieran Hesse (*equal contribution). Integrated Directional Gradients: Importance Attribution to Feature Interactions in Neural NLP Models. ACL 2021 (full paper), virtually (online). 

• Sandipan Sikdar, Animesh Mukherjee and Matteo Marsili. Unsupervised Ranking of Clustering Algorithms by INFOMAX. PLoS ONE (15 (10) e0239331). 2020  

• Binny Mathew*, Sandipan Sikdar*, Florian Lemmerich and Markus Strohmaier (*equal contribution). POLAR: Polar opposites enable interpretability of pre-trained word embeddings. Web Conference 2020 (previously WWW), Taipei, Taiwan

• Abhirut Gupta, Sandipan Sikdar, Prateeti Mohapatra and Niloy Ganguly. Topic Influence Graph Based Analysis of Seminal Papers. CODS-COMAD 2020, Hyderabad, India

• Soumya Sarkar, Bhanu Prakash Reddy, Sandipan Sikdar and Animesh Mukherjee. StRE: Self Attentive Edit Quality Prediction in Wikipedia. ACL 2019, Florence, Italy 

• Soumya Sarkar, Sandipan Sikdar, Sanjukta Bhowmick and Animesh Mukherjee. Using Core-Periphery Structure to Predict High Centrality Nodes in Time-Varying Networks. Data Mining and Knowledge Discovery Journal 32.5 (2018): 1368-1396 (ECML-PKDD 2018 journal track). 

• Sandipan Sikdar, Tanmoy Chakraborty, Soumya Sarkar, Niloy Ganguly and Animesh Mukherjee. ComPAS: Community Preserving Sampling for Streaming Graphs. AAMAS 2018, Stockholm, Sweden. 

• Sandipan Sikdar, Paras Tehria, Matteo Marsili, Niloy Ganguly and Animesh Mukherjee.  On the effectiveness of the scientific peer-review system: a case study of the Journal of High Energy Physics. International Journal on Digital Libraries (IJDL) 2018. 

• Sandipan Sikdar. Significance of scientific peer-review system: A case study of the Journal of High Energy Physics. IEEE TCDL Bulletin 2017 and also in JCDL PhD Forum 2017, Toronto, Ontario, Canada.

• Sandipan Sikdar, Matteo Marsili, Niloy Ganguly and Animesh Mukherjee. Influence of Reviewer Interaction Network on Long-term Citations: A Case Study of the Scientific Peer-Review System of the Journal of High Energy Physics. JCDL 2017, Toronto, Ontario, Canada. (nominated for best student paper)

• Marcin Bodych, Niloy Ganguly, Tyll Krueger, Animesh Mukherjee, Rainer Seigmund-Schultze and Sandipan Sikdar (alphabetical order). Threshold-based epidemic dynamics in systems with memory. EuroPhysics Letters (EPL) 2017, 116(4), 48004

• Sandipan Sikdar, Matteo Marsili, Niloy Ganguly and Animesh Mukherjee. Anomalies in the peer-review system: A case study of the journal of High Energy Physics. CIKM 2016, Indianapolis, USA.

• Sandipan Sikdar, Abhijnan Chakraborty, Anshit Choudhury, Gourav Kumar, S.Kumar, Abhijeet Patil, Niloy Ganguly and Animesh Mukherjee. Identifying and Characterizing Sleeping Beauties on YouTube, CSCW 2016 (poster), San Francisco, USA.

• Sandipan Sikdar, Niloy Ganguly and Animesh Mukherjee. Time series analysis of temporal networks. European Physics Journal B (EPJB) topical issue on Temporal Network Theory and Applications 2016, 89(1).

• Sandipan Sikdar, Marcin Bodych, Rajib Ranjan Maity, Biswajit Paria, Niloy Ganguly, Tyll Krueger and Animesh Mukherjee. On the broadcast of segmented messages in dynamic networks. NetSciCom 2015, HongKong.

• Tanmoy Chakraborty, Sandipan Sikdar, Niloy Ganguly and Animesh Mukherjee. Citation Interactions among Computer Science Fields: A Quantitative Route to the Rise and Fall of Scientific Research. Social Network Analysis and Mining (SNAM) 2014.

• Tanmoy Chakraborty, Sandipan Sikdar, Vihar Tammana, Niloy Ganguly and Animesh Mukherjee. Computer Science Fields as Ground-truth Communities: Their Impact, Rise and Fall. ASONAM 2013, Ontario, Canada. (nominated for best paper)