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About me:
About me:
I am a Postdoctoral Researcher at Pacific Northwest National Laboratory (PNNL). I received my Ph.D. from the Department of Computer Science at Purdue University, and my Master's and Bachelor's degrees from the Department of Computer Science (CSE) at the Bangladesh University of Engineering and Technology (BUET).
I started my career as a Lecturer (2014-2017) at BUET's CSE department and was promoted to Assistant Professor (2017-2024). I currently work as a postdoc in the language intelligence department at PNNL (2025-present).
Email address: siddhartha.das@pnnl.gov, siddhartha047@gmail.com
Google Scholar: https://scholar.google.com/citations?user=kTAFl2yYe6QC&hl=en
Research Interests
Research Interests
I am a Postdoctoral researcher at Pacific Northwest National Laboratory (PNNL) in the Language Intelligence group of the Data Science and Machine Intelligence department.
My interests lie broadly in the domain of Machine Learning and Graph Algorithms. My works include theories and applications related to graph representation learning. I have designed scalable Graph Neural Network (GNN) algorithms for homophilic and heterophilic graphs. My research also includes graph sparsification and graph construction for machine learning tasks.
Furthermore, my work extends to practical applications, such as classifying and analyzing Software Vulnerabilities (CVEs) into Weaknesses (CWEs) and Attack Patterns (CAPECs) using large language models (LLMs). My work has been recognized in top-tier conferences and journals and has received the best paper awards.
Awards and News Media
Awards and News Media
Selected Publications
Selected Publications
Das, Siddhartha Shankar, Naheed Anjum Arafat, Muftiqur Rahman, S. M. Ferdous, Alex Pothen, and Mahantesh M. Halappanavar. "SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks." arXiv preprint arXiv:2502.10208 (2025). https://doi.org/10.48550/arXiv.2502.10208
Siddhartha Shankar Das, S M Ferdous, M. Halappanavar, E. Serra, and A. Pothen. 2024. AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’24), August 25–29, 2024, Barcelona, Spain. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3637528.3671940
Siddhartha Shankar Das, E. Serra, M. Halappanavar, A. Pothen and E. Al-Shaer,“V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities,” 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA), pp. 1-12, https://doi.org/10.1109/DSAA53316.2021.9564227 [Best Paper]
Siddhartha Shankar Das, A. Dutta, S. Purohit, E. Serra, M. Halappanavar, and A. Pothen, “Towards automatic mapping of vulnerabilities to attack patterns using large language models.” 2022 IEEE International Symposium on Technologies for Homeland Security (HST). IEEE, 2022. https://doi.org/10.1109/HST56032.2022.10025459 [Best paper]
Siddhartha Shankar Das, M. Halappanavar, A. Tumeo, E. Serra, A. Pothen, and E. Al-Shaer. “VWC-BERT: Scaling vulnerability–weakness–exploit mapping on modern AI accelerators.” In 2022 IEEE International Conference on Big Data (Big Data), pp. 1224-1229. IEEE, 2022. https://doi.org/10.1109/BigData55660.2022.10020622
K. Panchal, Siddhartha Shankar Das, L. Torre, J. Miller, R. Rallo, and M. Halappanavar. “Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM).” In 2022 IEEE International Symposium on Technologies for Homeland Security (HST), pp. 1-7. IEEE, 2022. https://doi.org/10.1109/HST56032.2022.10025443
Das, Siddhartha Shankar, Md Monirul Islam, and Naheed Anjum Arafat. "Evolutionary algorithm using adaptive fuzzy dominance and reference point for many-objective optimization." Swarm and evolutionary computation 44 (2019): 1092-1107. https://doi.org/10.1016/j.swevo.2018.11.003
Rizvi, Asm, Tarik Reza Toha, Siddhartha Shankar Das, Sriram Chellappan, and ABM Alim Al Islam. "Many-objective performance enhancement in computing clusters." In 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC), pp. 1-2. IEEE, 2017. https://doi.org/10.1109/PCCC.2017.8280491
sm Rizvi, A., Tarik Reza Toha, Siddhartha Shankar Das, Sriram Chellappan, and ABM Alim Al Islam. "Exploiting a Synergy between Greedy Approach and NSGA for Scheduling in Computing Clusters." In 2018 5th International Conference on Networking, Systems and Security (NSysS), pp. 1-8. IEEE, 2018. https://doi.org/10.1109/NSysS.2018.8631376
Other Research Projects
Other Research Projects
Scaling GNN:
Supervised and Unsupervised sparsifiers for Graph Neural Networks (GNN).
Edge Disjoint Graph Sampling for Graph Neural Networks (GNN).
Feature-based Spectral Sampling for Graph Neural Network (GNN).
Scalable Graph Sparsification based on feature diversity.
Supervised Graph Construction, Regular/Balanced Graph Construction, Graph Neural Network.
A Many-objective Evolutionary Approach Using Fuzzy Dominance With Bidirectional Bias
Siddhartha Shankar Das, Monirul Islam, Naheed Anjum Arafat
[pdf][code]
Submitted as Undergraduate Thesis
A Grid Based Many-Objective Evolutionary Algorithm using Fuzzy Fitness
Siddhartha Shankar Das, Naheed Anjum Arafat, Monirul Islam
[pdf][code]
Best poster award: 3rd in 2nd undergraduate thesis poster presentation, 2014 (out of 53 submissions)
Implementation of document image Segmentation algorithm for handwritten OCR
Siddhartha Shankar Das
[presentation][code]
Advanced Image Processing Course, 2016
A short survey on Near-Duplicate Video detection and retrievalSiddhartha Shankar Das
[presentation][pdf]
High Dimensional Data management Course, 2016
Analysis of Advertisement fraudulent activities (click fraud, impression fraud etc)
based on our implementation of a large-scale Advertisement service system, that loads millions of ads daily into different news portal of Bangladesh (prothom alo, bdnews, bangla tribune, bikroy )
[code] Siddhartha Shankar Das, Azad Salam
[report]
Details of other projects can be found here
Current and recent collaborators: Mahantesh Halapanavar, Proteek Chandan Roy (Michigan State University), Sriram Cheppallan (University of South Florida)
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