Hello, I'm Nafis Karim, a Lecturer at the at Department of CSE, Brac University and I have just completed my B.Sc. in Computer Science And Engineering from BUET. I enjoy
I am a passionate Computer Science student who enjoys learning new stuffs about technology and research methodology. I am always eager to learn new things and apply them in real life. My undergraduate thesis was done under the supervision of Dr. Md. Shohrab Hossain in collaboration with Professors Ren-Hung Hwang and Ying-Dar Lin of NYCU. It focused on exploring the effectiveness of in-context learning for Named Entity Recognition in Cyber Threat Intelligence, along with fine-tuning and prompting Large Language Models for the task.
When I am not studying, I enjoy listening to music, playing the guitar, and watching movies. I enjoy performing on stage in various cultural programs with my own band and have done so on quite a few occasions during my undergraduate life.
Starting from Summer 2024, I joined the CSE Department at the School of Data and Sciences (SDS) in BRAC University as a Lecturer. I am actively looking for fully-funded Graduate Research Student positions in top CS research labs. You are also welcome to knock me with startup ideas and educational content creation opportunities.
Here is a collection of my research projects, collaborations, and contributions in various fields.
Developed and evaluated methods for Named Entity Recognition (NER) in Cyber Threat Intelligence using transformer models (BERT, SecureBERT) and few-shot learning models (GPT-3.5, GPT-4.0, Gemini) on DNRTI and APTNER datasets. Results demonstrated that fine-tuned transformers outperformed few-shot models in accuracy and precision, highlighting the value of domain-specific training for CTI applications.
Status: Under review at ACM Transactions on Privacy and Security
Developed a deep learning model to predict COVID-19 cases, incorporating factors like vaccination rates and hospital admissions often overlooked in traditional models. The fusion-type network architecture combined channel-wise and global convolution with recurrent networks to capture complex time series dependencies. Tested on US and UK datasets, the model outperformed state-of-the-art methods, emphasizing the impact of vaccination on controlling case spread.
We investigate the potential of a deceased animal brain to process signals. Specifically, we examine the brain’s responses to external stimuli in the form of electrical signals and its ability to act as a memory unit. We also explore the transfer characteristics of the deceased goat brain and elucidate the corresponding function through representative circuits.
Status: Under review
This project is inspired by the seminal paper from Gatys et al., on neural style transfer. The goal of this project is to explore and implement the neural style transfer technique where the style of one image is combined with the content of another using convolutional neural networks.
A collection of simulation and modeling assignments for the CSE412 course, each designed to address a unique real-world problem. These projects utilize various simulation techniques, including queueing systems, inventory management, project scheduling, and Monte Carlo methods.
Implemented a public key cryptography system with AES, Diffie-Hellman, and RSA key exchanges over client-server sockets. Explored malware functionalities, buffer overflow attacks, and experimented with firewall configurations and browser exploitation using BeEF.
Dhaka, Bangladesh
Dhaka, Bangladesh
Dhaka, Bangladesh
BRAC University - Dhaka, Bangladesh
July 2024 - Present
Please contact me directly at nafiskarim1999@gmail.com or through this form.
