AHC

Asif Hasan Chowdhury

Lecturer

asif.hasan@bracu.ac.bd

Address

CSE Department
4th floor, Room No # 4L92,
Brac University,
Kha 224 Bir Uttam Rafiqul Islam Avenue,
Merul Badda, Dhaka, Bangladesh

AHC

Biography Publication Professional Activity Awards Education

Asif Hasan Chowdhury completed his Bachelor in Computer Science and Engineering from BRAC University in the Summer of 2022. Currently, he is working as a software engineer at Spectrum Engineering & Consortium Ltd and as a contractual lecturer at Brac University's CSE Department. Previously, he has served as a student tutor at the CSE department of Brac University and as a software engineer intern at BNX Networks Inc. His primary research interests are Deep Learning, Graph Neural Networks, LLM

September 2023 – Current

LECTURER (CONTRACTUAL) – BRAC University, Dhaka, Bangladesh

Department of Computer Science and Engineering (CSE)

Courses Taught:

Software Engineering (CSE470),
System Analysis & Design Lab (CSE471)

October 2022 – Current

Software Engineer – Spectrum Engineering & Consortium LTD, Dhaka, Bangladesh

Technical Practice
C#, Java, ASP.NET CORE, ASP.NET Framework, Angular, Typescript

April 2022 – September 2022

Software Engineer Intern – BNX Networks

C#, ASP.NET Webforms, Javascript

System Analysis and Design (CSE)

June 2021 – Septembr 2022

STUDENT TUTOR (PART TIME) – BRAC University, Dhaka, Bangladesh

Department of Computer Science and Engineering (CSE)

Courses Taught:

VLSI (CSE460)

Electronic Devices and Circuits (CSE 251),
Algorithm (CSE221)

2023 – current

MASTER OF SCIENCE AND ENGINEERING (M.SC. ENGG.)

Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh

Field of study: Computer Science and Engineering

2018 – 2022

BACHELOR OF SCIENCE (B.SC.)

BRAC University, Dhaka, Bangladesh

Field of study: Computer Science and Engineering

Final grade: 3.92 out of 4

Thesis

Accepting

As:	Supervisor Co-supervisor
Level:	Undergraduate
Type:	Thesis Project Internship

Research Interest

Research Interests

Multi-Modal Machine Learning: Learning joint representations from heterogeneous data such as images, text, audio, and biological sequences.
Computational Biology: Applying machine learning to protein, genomic, and other biological data.
Large Language Models & Vision-Language Models: Prompt-based learning, weak supervision, efficient adaptation, and reliability of generative models.
Parameter-Efficient & Hardware-Efficient Computing: Low-cost training and inference, efficient fine-tuning, and model optimization for resource-constrained environments.
Federated & Privacy-Preserving Learning: Collaborative model training across decentralized data sources.
AI in Healthcare: Trustworthy and practical machine learning for medical diagnosis and clinical decision support.
Reinforcement Learning: Adaptive decision-making for optimization and system-level control.
Meta-Heuristics & Combinatorial Optimization: Evolutionary and hybrid search methods for complex real-world problems.
Learning-Augmented Systems: Integrating machine learning into memory management, caching, and other core computer systems.
Software Engineering & Architecture: Scalable, maintainable system design.

BRACU CSE

AHC

AHC

Thesis

Research Interest

BRACU CSE