Lebenslauf und Publikationen Mirza Mohtashim Alam

• Education:
  2023-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)
  2018-2020: MSc in Computer Science, University of Bonn, Germany
  2012-2016: BSc in Computer Science at BRAC University, Dhaka, Bangladesh
• Master’s Thesis:
  Mirza Mohtashim Alam: Rulect: A System for Extraction, Representation and Learning of Relational Patterns on Knowledge Graph Embeddings, 2020 [local copy (PDF)].
   
• Experience:
  12.2020-05.2023: Scientific Researcher, Institute for Applied Informatics (InfAI)
  04.2018-09.2020: Student Research Assistant, Smart Data Analytics, Informatik III, University of Bonn, Germany
  09.2016-02.2018: Lecturer, Daffodil International University, Dhaka, Bangladesh
  02.2014-03.2016: Teaching Assistant/Student Tutor, BRAC University, Dhaka, Bangladesh
   
• Achievements, Honors and Awards:
  Deutscheland Stipendium: The German Federal Ministry of Education and Research (BMBF) for the academic year 2018/19
  Research Award for scholarly publication: Awarded by Daffodil International University, Dhaka, Bangladesh, for scholarly publication in reputed indexed Journals for the year of 2018.
  Vice Chancellor’s Gold Medalist: Awarded by BRAC University, for having obtained the highest CGPA 3.83 out of 4 among students receiving the degree of Bachelor of Science in Computer Science in the graduating batches of 11th Convocation held on 5th December 2016 and on the fulfillment of all the other requirements for the award.
  5 times Vice Chancellors list: Listed in Vice Chancellor’s list in different semesters for academic excellence. Awarded in Fall’12, Fall’13, Spring’14, Spring’15 and Spring’ 16.
  Board Scholarship in SSC Examination: Awarded Board Scholarships by the Ministry of Education board of Rajshahi for academic excellence.
   
• Research Interests:
  Machine Learning
  Natural Language Processing
  Large Language Models
  Knowledge Graph Embedding
  Question Answering
  Dialogue System

Google Scholar: https://scholar.google.com/citations?user=vIeulKIAAAAJ&hl=en
DBLP: https://dblp.org/pid/267/4877.html
Semantic Scholar: https://www.semanticscholar.org/search?q=Mirza+Mohtashim+Alam

2023:

• Mohiuddin, Karishma, Alam, M. A., Alam, M. M., Welke, P., Martin, M., Lehmann, J., & Vahdati, S. (2023). Retention Is All You Need. ArXiv Preprint ArXiv:2304. 03103.
• McTear, M., Jokinen, K., Alam, M. M., Saleem, Q., Napolitano, G., Szczepaniak, F., … Others. (2023). Interaction with a Virtual Coach for Active and Healthy Ageing. Sensors, 23(5), 2748.

2022:

• Alam, M. M., Rony, M. R. A. H., Nayyeri, M., Mohiuddin, K., Akter, M. M., Vahdati, S., & Lehmann, J. (2022). Language Model Guided Knowledge Graph Embeddings. IEEE Access, 10, 76008-76020.
• Alam, M. M., Rony, M. R. A. H., Ali, S., Lehmann, J., & Vahdati, S. (2022). Language Model-driven Negative Sampling. ArXiv Preprint ArXiv:2203. 04703.
• Nayyeri, M., Wang, Z., Akter, M., Alam, M. M., Rony, M. R. A. H., Lehmann, J., … Others. (2022). Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex Spaces. ArXiv Preprint ArXiv:2208. 02743.
• Nayyeri, M., Vahdati, S., Khan, M. T., Alam, M. M., Wenige, L., Behrend, A., & Lehmann, J. (2022). Dihedron Algebraic Embeddings for Spatio-Temporal Knowledge Graph Completion. The Semantic Web: 19th International Conference, ESWC 2022, Hersonissos, Crete, Greece, May 29--June 2, 2022, Proceedings, 253–269. Springer International Publishing Cham.

2021:

• Alam, M. M., Nayyeri, M., Xu, C., Al, M. R., Rony, H., Yazdi, H. S., … Lehmann, J. (2021). The Effect of Rule Injection in a Leakage Free Datasets.
• Nayyeri, M., Xu, C., Alam, M. M., Lehmann, J., & Yazdi, H. S. (2021). LogicENN: a neural based knowledge graphs embedding model with logical rules. IEEE Transactions on Pattern Analysis and Machine Intelligence.
• Nayyeri, M., Xu, C., Hoffmann, F., Alam, M. M., Lehmann, J., & Vahdati, S. (2021). Knowledge graph representation learning using ordinary differential equations. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 9529–9548.
• Nayyeri, M., Xu, C., Yaghoobzadeh, Y., Vahdati, S., Alam, M. M., Yazdi, H. S., & Lehmann, J. (2021). Loss-aware pattern inference: A correction on the wrongly claimed limitations of embedding models. Advances in Knowledge Discovery and Data Mining: 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11--14, 2021, Proceedings, Part III, 77–89. Springer International Publishing Cham.

2020:

• Nayyeri, M., Alam, M. M., Lehmann, J., & Vahdati, S. (2020). 3D Learning and Reasoning in Link Prediction Over Knowledge Graphs. IEEE Access, 8, 196459–196471.
• Alam, M. M., Jabeen, H., Ali, M., Mohiuddin, K., & Lehmann, J. (2020). Affinity Dependent Negative Sampling for Knowledge Graph Embeddings. DL4KG@ ESWC.
• Hasan, M. S., Ali, M., Rahman, M., Arju, H. A., Alam, M. M., Uddin, M. S., & Allayear, S. M. (2019). Heritage building era detection using CNN. IOP Conference Series: Materials Science and Engineering, 617, 012016. IOP Publishing.

2019:

• Rony, M. R. A. H., & Alam, M. M. (2019). Hand gesture recognition using image segmentation and deep neural network. Eleventh International Conference on Machine Vision (ICMV 2018), 11041, 290–295. SPIE.
• Islam, M. K., Alam, M. M., Rony, M. R. A. H., & Mohiuddin, K. (2019). Statistical Analysis and Identification of Important Factors of Liver Disease using Machine Learning and Deep Learning Architecture. Proceedings of the 2019 3rd International Conference on Innovation in Artificial Intelligence, 131–137.
• Alam, M. M., Mohiuddin, K., Islam, M. K., Hassan, M., Hoque, M. A.-U., & Allayear, S. M. (2019). A machine learning approach to analyze and reduce features to a significant number for employee’s turn over prediction model. Intelligent Computing: Proceedings of the 2018 Computing Conference, Volume 2, 142–159. Springer International Publishing.

2018:

• Alam, M. M., Mohiuddin, K., Das, A. K., Islam, M. K., Kaonain, M. S., & Ali, M. H. (2018). A reduced feature based neural network approach to classify the category of students. Proceedings of the 2nd International Conference on Innovation in Artificial Intelligence, 28–32.
• Islam, M. K., Alam, M. M., Islam, M. B., Mohiuddin, K., Das, A. K., & Kaonain, M. S. (2018). An adaptive feature dimensionality reduction technique based on random forest on employee turnover prediction model. Advances in Computing and Data Sciences: Second International Conference, ICACDS 2018, Dehradun, India, April 20-21, 2018, Revised Selected Papers, Part II 2, 269–278. Springer Singapore.

2017:

• Kabir, S. R., Allayear, S. M., Alam, M. M., & Munna, M. T. A. (2017). A computational technique for intelligent computers to learn and identify the human’s relative directions. 2017 International Conference on Intelligent Sustainable Systems (ICISS), 1037–1040. IEEE.
• Mohiuddin, Karishma, Alam, M. M., Das, A. K., Munna, M. T. A., Allayear, S. M., & Ali, M. H. (2019). Haar Cascade Classifier and Lucas--Kanade Optical Flow Based Realtime Object Tracker with Custom Masking Technique. Advances in Information and Communication Networks: Proceedings of the 2018 Future of Information and Communication Conference (FICC), Vol. 2, 398–410. Springer International Publishing.