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AHU

Md. Ahasanul Alam

Lecturer

ahasanul.alam@bracu.ac.bd

Address

CSE Department
4th floor, Room No # 4M133,
Brac University,
Kha 224 Bir Uttam Rafiqul Islam Avenue,
Merul Badda, Dhaka, Bangladesh

Biography Publication Professional Activity Awards

Md. Ahasanul Alam is currently working at BRAC University as a Lecturer. He received the bachelor’s degree in Computer Science and Engineering from the University of Dhaka, Bangladesh. He is currently pursuing a Master's Degree from the same institution.  Previously he worked as a Research Assistant (RA) with the Cognitive Agents and Interaction Laboratory (CAIL), University of Dhaka. His research interests include Multi-Agent Systems, Multi-Agent Coordination, Multi-Agent Path Finding (MAPF), and Natural Language Processing (NLP).

Here is my CV

  • Md Ahasanul Alam,  Mustafizur Rahman, Md Mofijul Islam, Ismat Rahman, Md Mosaddek Khan, and Tariq Iqbal. "An Adaptive Agent-Specific Sub-Optimal Bounding Approach for Multi-Agent Path Finding." IEEE Access 10 (2022): 22226-22237.
  • Lecturer, Dept. of CSE
    BRAC University, Bangladesh
    January 2023 – Present
     
  • Research Assistant (RA)
    Cognitive Agents and Interaction Laboratory (CAIL)
    University of Dhaka, Bangladesh
    November 2020 – December 2022
  • Fellowship grant on M.Sc thesis, Ministry of Information and Communication Technology (ICT), Government of Bangladesh
  • Government Scholarship based on the result on B.Sc examination 2020 (Merit Position: 04).
  • Scholarship for Higher Secondary School Certificate (HSC) examination result in Dinajpur Board (2016)
  • Scholarship for Secondary School Certificate (SSC) examination result in Dinajpur Board (2014)

Thesis

Accepting

As:
  • Supervisor
  • Co-supervisor

Level:

Undergraduate

Type:
  • Thesis

Research Interest

Multi Agent Path Finding
The Multi-Agent Pathfinding (MAPF) problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently without colliding with each other. Research on MAPF has been flourishing in the past couple of years. Although a MAPF problem needs to be solved for many real-world deployments, solving such a problem optimally is NP-hard. Consequently, the main focus is to find sub-optimal algorithms to improve scalability and solution runtime. 

 

Course Related: Data Structure and Algorithms, Discrete Mathematics, Numerical Methods, Artificial Intelligence


Natural Language Processing

 

Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. Although several works have been done in recent years on English and other languages, scope for improvement in Bangla NLP is still very wide. Efficient techniques would help computers to communicate with humans in their own language and scales other language-related tasks. 

Course Related: Algorithms, Numerical Methods, Artificial Intelligence, Neural Networks, Machine Learning, Linear Algebra, Probability and Statistics

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