Specializing in building efficient AI/ML models. My Research interests are Multimodal Large Language Models, Foundational AI Models, Domain-Adaptation, Knowledge Distillation, and Trustworthy AI through Science Guidance. I build AI architectures that bridge the gap between massive pre-trained models and data-scarce scientific applications.
I am a PhD Candidate and my research Focus is on bridging the gap between rigorous academic theory and impactful deployment. My work on optimizing Foundational Models for data-scarce environments has achieved a Best Paper Award at IEEE DSAA 2025 and active research contributor to NSF/NIFA funding projects, while my industrial experience includes building high-performance LLM based deep learning pipelines. With 8+ years of experience in research, education, and mentoring, I am seeking a position to lead Reliable AI innovations and mentor the next generation of talent in a collaborative research environment.
As AI transitions from static prediction to complex reasoning, my agenda pioneers Reliable Foundation Models for the engineering and natural sciences.
The Challenge: LMMs often "hallucinate" in scientific contexts where factual accuracy is non-negotiable.
Research Plan: Physics-Aware Multimodal RAG. I will be working on advancing agents that ground reasoning in verified observational data and physical laws.
The Challenge: High-stakes fields like precision agriculture require more than accuracy; they demand calibrated confidence.
Research Plan: Decomposing predictive uncertainty into Epistemic (reducible model knowledge) and Aleatoric (irreducible data noise) components to robustly detect out-of-distribution shifts.
We developed a novel framework that allows generalized knowledge from a widely capable but low-dimensional input based teacher to guide a high-dimensional input based student, solving the critical "dimensional scaling" challenge in foundational models.
Click to view the HyperKD Architecture
Colorado State University (CSU)
Fort Collins, Colorado, USA
Fellowship for exceptional research excellence
Colorado State University (CSU)
Fort Collins, Colorado, USA
Outstanding Graduate Student Fellowship
Rajshahi University of Engineering & Technology (RUET)
Rajshahi, Bangladesh
Topper & Vice Chancellor Gold Medalist
IEEE DSAA 2025
Awarded by IEEE DSAA, a flagship conference in data science and analytics.
Colorado State University, 2024
Prestigious fellowship awarded annually to one Ph.D. student for exceptional research excellence.
CSU Dept. of Computer Science, 2023
Recognition for top-performing graduate student in the department.
Highest academic honor awarded by RUET to the top-ranked B.Sc. graduate.
Awarded annually for highest performance (2012, 2013, 2014, 2015).
1st Place, Hosted by ICT Division, Rajshahi.
For outstanding results in Secondary & Higher Secondary Board examinations.
Integrates the Linear Spectral Mixing Model (LSMM) as a differentiable constraint within self-supervised learning to respect real-world spectral composition laws.
Click to view architecture
Introduced a novel masking strategy, HOGMAE, based on the Histogram of Oriented Gradients that incorporates rich information inherent within satellite images during the mask creation step.
Click to view architecture
Introduces the Spectral Adaptation Unit (SAU) to project high-precision lab spectroscopy and noisy satellite observations into a unified latent representation.
Click to view architecture
Proposed effective Masking for self-supervised MAE and Enforces structural and spectral coherence via specialized loss functions (SSIM/SID) to learn physically meaningful features from Earth observation data.
Click to view architecture
Bridges sparsity and resolution by distilling coarse-resolution predictions from a large teacher into high-resolution outputs for a lightweight student anchored by sparse sensors.
Click to view architecture
Interdisciplinary research projects I contributed to as a graduate research assistant (* indicates my Doctoral Committee Members).
Beyond my teaching duties, I have provided direct mentorship to more than 30 undergraduate and graduate students, supporting their undergraduate theses, research endeavors, and software development projects.
Listing research advisees and thesis students mentored across CSU and RUET.
| Student Name | Role | Research / Mentorship Topic | Outcome / Current Status |
|---|---|---|---|
| Rupasree Dey | Graduate Mentee | Research on DeepSalt: Domain Adaptation for Soil Salinity | Published in IEEE BigData '25 |
| Tanjim B. Faruk | Graduate Mentee | Research onTerraMAE: Hyperspectral Feature Learning | Published in ACM SIGSPATIAL '25 |
| Hafsa Binte Kibria | Undergrad Advisee | Research onCardiovascular Disease Prediction Models | Faculty Member @ ECE, RUET |
| Omaer Faruq | Undergrad Advisee | Engineering Projects & Cloud Segmentation | Faculty Member @ ECE, RUET |
| Hasinur Rahman | Undergrad Advisee | Data Structures & Algorithms | Software Engineer @ Google |
| Tonmoy Hasan | Undergrad Advisee | Research on Sentiment Analysis & Text Classification | Ph.D. Student @ UNC Charlotte |
| MD Rakibul Islam | Undergrad Advisee | Research on Deep Learning for Medical Imaging (CT/MRI) | Ph.D. Student @ Mälardalen Univ |
| Ettilla Mohiuddin Eumi | Undergrad Advisee | Research on Bengali News Categorization (NLP) | Ph.D. Student @ UNSW |
| Habib Ur Rahman | Undergrad Advisee | Undergraduate Project: Software Development & Machine Learning | Ph.D. Student @ CSU |
| S. Sarker | Undergrad Advisee | Research on Precipitation Prediction using LSTM | Published in IJCI 2022 |
| I. Z. Tonu | Undergrad Advisee | Project and Research on Human Action Classification (CNN) | Published in IEEE WIECON 2021 |
| S. Islam | Undergrad Advisee | Research on Hand Gesture Recognition (HCI) | Published in ICO 2021 |
| M. O. F. Goni | Undergrad Advisee | Research on Chronic Kidney Disease Prediction | Published in BIM 2021 |
| M. R. I. Sarker | Undergrad Advisee | Research on Collaborative Recommendation Systems | Published in ICTSD 2021 |
| M. A. I. Siddique | Undergrad Advisee | Research on White Blood Cell Classification | Published in IEEE ICECE 2020 |
| M. F. Ahamed | Undergrad Advisee | Software Developement Project and Research | Published in ICAICT 2020 |
Reviewer for high-quality international conferences and journals in Machine Learning domain.
RUET ECE Fest & IUPC 2019. Oversaw technical operations for national events with 90+ universities.
ICEEE 2017 & ICECTE (2016, 2019). Managed technical evaluation processes for IEEE-affiliated conferences.
RUET ECE Fest (Technocracy 2018). Coordinated logistics and student engagement for a major engineering festival.
NCPC 2015. Provided on-site support for system integrity during the National Collegiate Programming Contest.