Sk Mamud Haque — AI Researcher

Sk Mamud Haque is a final-year Computer Science Engineering student at the University of Petroleum and Energy Studies, specializing in Artificial Intelligence and Machine Learning, graduating in 2025. My academic and professional journey has been shaped by a strong foundation in software development, machine learning, and NLP, combined with hands-on experience through research and industry internships. Project Highlights: SummaEase: Developed an LLM-powered summarization system using transformer models and ASR to condense text and low-quality speech. Achieved 95% summarization accuracy and 30% improvement in content clarity. Integrated with Docker and Flask for scalable deployment. CloudWise: Built an AI-powered news aggregator using BERT-based summarization, NER, and topic modeling (LDA, BERTopic). Improved user engagement by 40% and reduced reading time by 70%. Deployed using Docker, Kubernetes, and CI/CD pipelines. Velox: Designed an AI-based ride-sharing platform with ride-matching (KNN + Haversine), A* route optimization, and predictive cost modeling. Achieved 99.9% uptime with Dockerized microservices and cloud deployment. Computer Vision Research: Presented “Healthy & Ripped Dragon Fruit Identification” using CNNs at ICCIIoT 2023, focusing on agriculture-based image classification. Industry Experience: IBM (2024): Developed a multilingual real-time translation system using Whisper/Wav2Vec and MarianMT. Achieved 95%+ translation accuracy across 10+ languages. Reduced latency by 40% with model quantization and GPU acceleration (TensorRT, ONNX). IIIT Naya Raipur (2023): Researched Spiking Neural Networks with neuromorphic principles (LIF, STDP, BPTT). Improved limb control accuracy by 20% and reduced computational cost by 30% using surrogate gradient descent. Technical Proficiencies: Languages: Python, C++, SQL Frameworks & Tools: TensorFlow, PyTorch, Transformers (Hugging Face), Scikit-learn, NLTK, SpaCy DevOps: Docker, Kubernetes, Terraform, Jenkins, Flask, CI/CD (GitHub Actions), AWS/GCP Concepts: Transformer Models, BERT, GPT, CNN, LSTM, SNN, Attention Mechanisms, NER, Topic Modeling Currently, I’m engaged in research on LLM-based abstract summarization and Generative AI, with a keen interest in enhancing the efficiency and interpretability of AI-driven systems. I’m always eager to collaborate on innovative projects in deep learning, computer vision, or scalable AI solutions. 📬 Let’s connect if you're looking to collaborate, discuss ideas, or tackle exciting challenges in AI! 📧 Reach me at haquemamud@gmail.com

Stackforce AI infers this person is a Machine Learning and AI specialist with a focus on Computer Vision and Natural Language Processing.

Location: Burdwan, West Bengal, India

Experience: 1 yr 3 mos