Welcome to my homepage.
My research interest lies at the intersection of Machine Learning and Semantic Web. Specifically, my focus is on explainable machine learning. Currently, machine learning/deep learning algorithms work as a black box and we only get the output from the model. The algorithm itself doesn't give any explanation why this output is chosen or why not. By using semantic background knowledge, I am trying to make an explanation for machine learning algorithms. Previously I have worked to make ontology editing easier and for that, I have developed 2 plugins (OWLAx and ROWL) for linked data analysis.
Worked at Accenture Technology Lab as a research intern for summer-2017.
Previously I have worked at Samsung Electronics for 2 years as software engineer.
Research Interests: Deep Learning, Semantic Web, Linked Data, Information Retrieval
Current Research Projects:
Deep learning algorithms are performing very good and sometimes they outperform humans. But still, their decision-making process is opaque. This is important for safety-critical operations like medical diagnostics, emergency response etc. We are trying to explain the decision of the algorithm. Our results Explaining Trained Neural Networks with Semantic Web Technologies: First Steps, Relating Input Concepts to Convolutional Neural Network Decisions are being published in NeSy and NIPS workshops.
2. Ontology Axiomatization:
Ontology Design Pattern Plugin for Desktop Protege
Accepted as a Software Demo at the 15th International Semantic Web Conference, ISWC2016, Kobe, Japan, October 2016: Md. Kamruzzaman Sarker, Adila A. Krisnadhi and Pascal Hitzler, OWLAx: A Protege Plugin to Support Ontology Axiomatization through Diagramming
Rule to OWL Axiom Conversion Plugin for Protege
Accepted as a Software Demo at the 15th International Semantic Web Conference, ISWC2016, Kobe, Japan, October 2016: Md. Kamruzzaman Sarker, David Carral, Adila A. Krisnadhi and Pascal Hitzler, Modeling OWL with Rules: The ROWL Protege Plugin.
Insurance company especially health insurance company need to calculate the cost of a new customer. Currently, they take user information and calculate the cost manually. We tried to automate this process using deep learning algorithms.
2. Samsung Android:
Worked on Android Connectivity team. Solved more than 100 issues related to Wi-Fi connectivity of 30+ Samsung Android Devices.
Developed music listener and sync with Android devices for Samsung Gear. Developed decryption method for I-Cloud contact being used in Smart Switch Migration. All code was reviewed, perfected, and pushed to production.
Here are my Online Profiles: