Present PhD students -
1. Madhusudan Ghosh (areas of research: Natural Language Processing, Deep Learning) (from 2020 - funded by IACS)
2. Shrimon Mukherjee (area of research: Applications of deep learning in drug repurposing) (from 2021- funded by IACS)
3. Payel Santra (area of research: Applications of ODE and graph algorithms in spread models such as epidemiological models) (from 2021- funded by IACS)
4. Samiran Dey (areas of research: Medical image processing, Deep learning) (from 2022 - funded by DBT-Vinnova project)
Research interests -
1. Graph algorithms - application of graph algorithms in massive graphs in the background of social networks (e.g. Facebook, Twitter) and recommender systems (as in Amazon, Flipkart, Zomato).
2. Recommender systems
3. Graph based NLP
4. Bioinformatics/ Computational Biology
Post-doc experience: Queen's University, Belfast
PhD in Computer Science and Engineering (Jadavpur University)
Dissertation title: Dynamics of Communities in Social Networks
MS in Computer Science (Louisiana State University)
MS in Computer and Electrical Engineering (Louisiana State University)
BE in Electronics and Telecommunication Engineering (BE College, Shibpur)
Sreetama Gayen, Adarsh Singh, Debasis Mitra, Partha Basuchowdhuri, Bappaditya Mandal and Robin Augustine. Exploring the New Horizon of Microwave-based Bio-Medical Imaging for Lung monitoring. Proceeding of the 2nd International Conference on Computational Electronics for Wireless Communications (ICCWC), LNNS. 2022.
Shrimon Mukherjee, Madhusudan Ghosh, Partha Basuchowdhuri. Deep Graph Convolutional Network and LSTM based approach for predicting drug-target binding affinity. SIAM Data Mining (SDM) conference, 2022. Acceptance rate: 27%
Suchetana Gupta, Ditipriya Mallick, Kumarjeet Banerjee, Shrimon Mukherjee, Soumyadev Sarkar, Sonny TM Lee, Partha Basuchowdhuri, Siddhartha S Jana. D155Y substitution of SARS-CoV-2 ORF3a weakens binding with Caveolin-1. Computational and Structural Biotechnology (IF: 7.3). 2022
Partha Basuchowdhuri, Satyaki Sikdar, Varsha Nagarajan, Khushbu Mishra, Surabhi Gupta, and Subhashis Majumder. Fast Detection of Community Structures using Graph Traversal in Social Networks. Knowledge and Information Systems (KAIS), Springer (2019).
Subhajit Datta, Partha Basuchowdhuri, Surajit Acharya, and Subhashis Majumder. The Habits of Highly Effective Researchers: An Empirical Study. IEEE Transactions on Big Data (I.F: 3.34), Volume: 3, Issue: 1, PP 3-17, 2016.
Partha Basuchowdhuri, Satyaki Sikdar, Sonu Shreshtha, and Subhashis Majumder. Detecting Community Structures in Social Networks by Graph Sparsification. Proceedings of the 3rd IKDD Conference on Data Science(ACM IKDD CoDS), 2016. Article No. 5. (Acceptance rate (full papers): less than 5%)
Partha Basuchowdhuri, Lakshan V. K. Prabhu, Mithun Roy, Subhashis Majumder, and Sanjoy K. Saha. Unified Scheme for Finding Disjoint and Overlapping Communities in Social Networks Using Strength of Ties. International Journal of Social Network Mining (IJSNM), Vol. 2, No. 2, 2015.
Sohom Ghosh, Angan Mitra, Partha Basuchowdhuri, and Sanjoy Kumar Saha. Analysis of Online Product Purchase and Predicting Items for Co-purchase. Proceedings of 3rd International Conference on Advanced Computing, Networking, and Informatics, ICACNI 2015.
Partha Basuchowdhuri, Riya Roy, Siddhartha Anand, Diksha Roy Srivastava, Subhashis Majumder and Sanjoy Kumar Saha. Spanning Tree-Based Fast Community Detection Methods in Social Networks. Accepted for publication in Innovations in Systems and Software Engineering: A NASA Journal, Springer (March, 2015).
Partha Basuchowdhuri, Varsha Nagarajan, Khusbu Mishra, Surabhi Gupta and Subhashis Majumder. Graph Traversal-based Fast Community Detection in Social Networks. (Accepted for research track poster presentation in ASONAM 2015, withdrawn due to lack of funding).
Partha Basuchowdhuri, Manoj Kumar Shekhawat and Sanjoy Kumar Saha. Analysis of Product Purchase Patterns in a Co-purchase Network. Proceedings of 4th International Conference of Emerging Applications of Information Technology. (EAIT 2014) (accepted for oral presentation).
Partha Basuchowdhuri, Siddhartha Anand, Diksha Roy Srivastava, Khusbu Mishra and Sanjoy Kumar Saha. Detection of Communities in Social Networks Using Spanning Tree. Advanced Computing, Networking and Informatics- Volume 2 (ICACNI). Smart Innovation, Systems and Technologies Volume 28, 2014, pp 589-597.
Partha Basuchowdhuri and Subhashis Majumder. Finding Influential Nodes in Social Networks Using Minimum k-Hop Dominating Set. In Proceedings of the 1st Internationl Conference on Applied Algorithms (ICAA), Lecture Notes in Computer Science (LNCS), Springer, 2014, Volume 8321/2014, pp.136-150.
Arpan Chaudhury, Partha Basuchowdhuri and Subhashis Majumder. Spread of Information in a Social Network Using Influential Nodes. In Proceedings of the 16th Pacific-Asia Conference of Knowledge Discovery and Data Mining (PAKDD), PAKDD 2012, Lecture Notes in Artificial Intelligence (LNAI), Springer, 2012, Volume 7302/2012, pp.121-132. http://www.springerlink.com/content/g77313t177t32108/
Marcel Karnstedt, Tara Hennessy, Jeffrey Chan, Partha Basuchowdhuri, Conor Hayes, and Thorsten Strufe. Churn in Social Networks. In Borko Furht (ed.), Handbook of Social Network Technologies and Applications, pp.185-220, Springer Verlag, 2010. ISBN: 9781441971418. http://www.springerlink.com/content/umr3386464w3v525/
Partha Basuchowdhuri and Jianhua Chen. Detecting Communities Using Social Ties. In Proceedings of the 2010 IEEE Conference on Granular Computing (IEEE GrC), pp.55-60, IEEE Press, 2010. http://www.computer.org/portal/web/csdl/doi/10.1109/GrC.2010.141
Partha Basuchowdhuri, Jianhua Chen and Peter P. Chen. Degree-based Approximate Sub-graph Matching for Social Network Analysis in Terrorist Detection. 13th International Conference on Artificial Intelligence (IC-AI), pp.286-293, CSREA Press, 2009.
Emrah Ceyhan, Partha Basuchowdhuri, Thair Judeh, Shangli Ou, Brett Estrade, and Tevfik Kosar. Towards a Faster and Improved ADCIRC (ADvanced Multi-Dimensional CIRCulation) Model. Journal of Coastal Research (JCR), Special Issue No.50 (2007), pp.949-954.
Teaching @ IACS
Undergraduate Courses -
MCS1101B: Introduction to Computing with Python (Autumn 2019)
MCS2101B: Data Structures and Algorithms (Autumn 2019, Autumn 2020)
MCS2111 (Lab): Data Structures and Algorithms Lab (Spring 2020, Spring 2021, Spring 2022)
Previous teaching experience prior to joining IACS
@ Heritage Institute of Technology
Courses and labs taken:
Introduction to Computing (Core - B.Tech level)
Data Structures and Algorithms (Core - B.Tech level)
Design and Analysis of Algorithms (Core - B.Tech level)
Software Tools (Lab - B.Tech level)
Data Mining and Knowledge Discovery (Elective - B.Tech level, M.Tech level)
Social and Complex Networks (Elective - B.Tech level, M.Tech level)
Cryptography and Network Security (Elective - B.Tech level)
1. DBT-VInnova project titled "AI based Detection of Acute Respiratory Distress Syndrome (AI-DARDS): An artificial intelligence aided non-contact framework for detecting acute respiratory distress syndrome using microwave sensors". Total grant for IACS: ~25 Lakhs
Best Teaching Award @ Heritage Institute of Technology (2015)