Mokhlesur R. Maruf is a multi-faceted professional with a wealth of experience in both academia and software industry. Currently serving as the Head of Engineering at iQuantile LLC and a Research Assistant at the Department of Computer Science and Engineering at United International University, he is also the CTO of TYPR LTD, a pioneering technology company that specializes in creating AI-driven writing assistants.

As Head of Engineering, he leads a 20+ member team at iQuantile LLC, driving successful project completion and fostering a culture of collaboration and innovation. He collaborates with cross-functional teams to define product features and objectives, establish scalable engineering processes, and mentor team members to support their career growth. Additionally, he facilitates Scrum events, guides teams in self-organization and collaboration, and removes obstacles to ensure successful and agile software development.

As a research assistant, He is working on a project named “Onubad: English to Bangla Machine Translator.” Under Professor Dr. Mohammad Nurul Huda's principle investigation, his work involved developing a neural machine translator that can translate English to Bangla (widely known as Bengali).  Mokhlesur's work on this project has involved the use of the latest deep learning techniques, including neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs).

In addition to his work on the "Onubad" project, Mokhlesur is also the CTO of TYPR LTD.,  overseeing the development of typr.ai's AI-powered copywriting assistant. He ensures the system's scalability, security, and reliability, collaborating with the product team to prioritize customer needs. Maruf also creates microservices for plagiarism-free content across various templates.

He achieved his M.Sc. in Computer Science & Engineering (MSCSE) Degree from United International University in 2020. His thesis is titled “Analysis of Gene Expression Data for Glioma Grade Classification and Survival Time Prediction.” In this work, He focused on a comparative study of different feature selection methods and proposed a new methodological approach to identify gene expression patterns effectively to classify unknown samples. If the tumor types are classified correctly and predict survival time, the treatment plan can be improved for brain tumor patients, so he proposes a novel pipeline framework for glioma analysis that uses several feature selection algorithms followed by effective classifier selection to predict the tumor type based on gene expression data and find the top n number of genes as features for tumor type and find the possible survival time in days.

He completed his BSc. in Computer Science and Engineering from Ahsanullah University of Science & Technology (AUST) in 2012. During his BSc. he has a number of quality publications in both national and international conferences and journals. His first paper, titled "Comparison between FDD and TDD frame structure in SC-FDMA,” was published at International Conference on Informatics, Electronics & Vision (ICIEV) in 2012. The second paper was titled “Performance Analysis of SC-FDMA and OFDMA in LTE Frame Structure” in 2012 in the International Journal of Computer Applications, Volume 45 - Number 23.

The research interest of Mr. Rahman Includes bioinformatics, Natural language Processing (NLP), machine learning, deep learning, and data Mining. In his current research, Maruf is conducting a systematic review of machine learning-based glioma prediction using gene expression data. This work aims to identify the most effective approaches for predicting the occurrence and progression of glioma, a type of brain tumor. By analyzing the available literature, Maruf hopes to provide insights into the state-of-the-art in glioma prediction and identify areas for further research.

Also, Maruf is currently contributing to a research project alongside Bikram Das, a Masters's student at the University of Massachusetts Dartmouth, to develop a privacy-critical mobile application for a campus safety escort program. The goal of the project is to empower campus communities to safely and effectively organize volunteer-based safety escort programs. Maruf's role in the project is focused on developing the backend and REST API, while Bikram leads the design and develop the mobile application for both iOS and Android. Together, they aim to create a solution tailored to the unique needs and concerns of the campus community.

He has worked as a Graduate Assitant at United International University from Nov 2017 – April 2020.

Overall, Maruf is an experienced and dedicated computer scientist and engineer with expertise in bioinformatics, natural language processing, machine learning, deep learning, data mining, and in the software industry. His work shows his dedication to using technology to improve the lives of people, particularly those with brain tumors, and his strong publication record demonstrates his ability to communicate his findings effectively.