About me
I’m Tahajib Jakir Khan — a Machine Learning and Data Science enthusiast with hands-on expertise in deep learning, federated learning, and large language models. With a strong foundation in research-backed innovation and intelligent automation, I focus on building scalable AI solutions, impactful dashboards, and optimized ML pipelines that solve real-world problems effectively and efficiently.
Over the years, I’ve combined academic excellence with impactful research and projects, ranging from adversarial robustness in CNN-LSTM models to federated leaf disease detection systems (BetelNet-10). My published and in-progress work reflects a balance of scientific rigor and implementation efficiency. I’ve also led the development of intelligent dashboards in Power BI and Tableau, and LLM-based tools using LangChain and Hugging Face. With solid fundamentals in algorithms and practical experience as a Data Science Intern, I thrive at the intersection of innovation and execution. Whether it’s building real-time applications, securing machine learning models, or presenting insights to decision-makers — I ensure my work creates real impact.
What i'm passionate about
-
Data Science
Turning raw data into actionable insights through statistical analysis, visualization, and intelligent modeling.
-
Applied Machine Learning
Designing and deploying practical ML models to solve real-world problems across diverse domains.
-
Deep Learning & Neural Networks
Building multi-layered neural architectures for complex pattern recognition in images, text, and beyond.
-
Privacy-Preserving AI
Developing secure, ethical AI systems using techniques like federated learning and adversarial defense.
-
Generative AI & Intelligent Systems
Creating adaptive, human-like systems capable of generating text, images, or decisions with context awareness.
-
Data-Driven Analysis
Leveraging data insights through Power BI and Tableau to drive strategic decisions, enhance performance, and optimize business outcomes.
Technical Skills
-
Machine Learning
Deep Learning Algorithms (Convolutional Neural Networks, Adversarial Robustness, Generative AI, Federated Learning, LLM), Data Analysis, Decision Analysis, and Statistical Analysis.
-
ML Packages
Keras, Tensorflow, Sci-kit learn,NumPy, Pandas, OpenCV, Matplotlib, Seaborn, TensorBoard, Tensorflow Federated, Hugging Face Transformers, LangChain, SimCLR, NLTK, Gradio, Streamlit.
-
Analytical Tools & clouds
PowerBI, Tableau, Excel, AWS, CleverHans.
-
Data Structures and Algorithms
Data structures, Graph Theory, Trees, Linked Lists, Stacks & Queues, Hash Maps.
-
Programming Language
C, C++, Python, Java, java Script, Dart.
-
Other Skills
Git, Latex, Arduino, Microsoft Word, Excel, PowerPoint, Access, Jupyter Notebook, Google Colab, VS Code, PyCharm, Spyder.
