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Dr. Sanjay Chakraborty

Education:

• Bachelor of Technology (WBUT/MAKAUT), India - 2009.

• Master of Technology - National Institute of Technology Raipur, India – 2011, Incremental Clustering.

• Ph.D. (Tech) (University of Calcutta, India) - 2022, Quantum Machine Learning

• Life-Member of IAENG & UACEE, International Computer Science and Engineering Society (ICSES), Internet Society Kolkata Chapter 

Current Place of Working:

Postdoc Researcher, Department of Computer and Information Science (IDA), AIICS, Linköping University, Sweden (2024-present).

and

Associate Professor (lien)

Department of Computer Science and Engineering 

Techno International New Town, India

Phone: +919038205310 / +46734752079

Email: sanjay.chakraborty@liu.se / schakraborty770@gmail.com 

Skype: schakraborty770

Biography:

Sanjay Chakraborty completed his PhD at the University of Calcutta in May 2022. I completed M.Tech from the National Institute of Technology, Raipur, India, in the year of 2011. I completed B-Tech from the West Bengal University of Technology, India, in the year 2009. I have published 85+ research papers in various international journals, conferences, and book chapters. I have published three internationally authored books. He published a total of five patents (IN and UK patents), including three granted. My areas of interest are data mining and machine learning, feature subset selection, and quantum computing. I am a professional member of the International Association of Engineers, Internet Society Kolkata Chapter, Institute of Research Engineers & Doctors, and International Computer Science and Engineering Society. I have a total of 15 years of teaching and research experience. I worked as a reviewer in several international conferences (ECAI, ACM KDD) and SCI, SCOPUS journals, including IEEE and ACM Transactions. I am the recipient of a silver medal during his M.Tech, IEEE Young Professional Best Paper Award in CICBA 2017 and "INNOVATION AWARD" for my outstanding achievement in the field of Innovation by Techno India Institution's Innovation Council 2019, Top 10 Best Scientists in JIS University at AD Scientific Index 2022, top 5 cited paper in ASEJ Elsevier journal and the 'Most Cited Author Award' 2022 by the biomedical journal Elsevier.

Employment Page:

https://liu.se/en/employee/sanch59

My Google Scholar:

https://scholar.google.co.in/citations?user=vtUt3S4AAAAJ&hl=en

My Linkedin:

https://www.linkedin.com/in/sanjay-chakraborty-90808a153/

My Research Gate:

https://www.researchgate.net/profile/Sanjay_Chakraborty

Amazon Author:

https://www.amazon.com/stores/Sanjay-Chakraborty/author/B0C6T2FMTW

My Scopus Profile:

https://www.scopus.com/authid/detail.uri?authorId=57169636900

Vidwan Portal:

https://vidwan.inflibnet.ac.in//profile/211783/MjExNzgz

GitHub:

https://github.com/sanjaylopa22

Objective:      

I aim to be an active member of the Research & Development wing in the fields of machine learning, deep learning, and quantum computing. Recently, I have focused on applying AI to industry-specific problems, including multivariate time series analysis and materials science. My PhD research interests lie in enhancing machine learning algorithms using quantum computing principles, such as quantum clustering with 1D DTQW, quantum feature selection, VQE, and QAOA, alongside applied AI in industrial contexts. I also have experience iTo be a part of the Research & Development wing in the field of machine learning, applied AI, and Quantum Computing. Recently, I have focused on applying AI to industry-specific problems, including multivariate time series analysis and materials science. My PhD research interests include the improvement of machine learning algorithms using quantum computing principles (quantum clustering using 1D DTQW, quantum feature selection, VQE, QAOA) and industry specific applied AI. I have also some experience working in the domain of ternary quantum image representation, edge extraction, image denoising, and segmentation. I would like to take up a challenging role in active Institute-Industrial Research activities which will fulfill my longing for relentless learning. My priority is to make significant contributions to the teaching, innovation, and research activity of the organization I belong to through a continuous process of application of mind and acquired expertise. I am really interested and enthusiastic about quantum Machine Learning techniques and their applications in R&D industry.

Core Technical Skills:

AI / ML: Machine learning and deep learning, Transformers, LLMs (RAG pipeline using Gemini/Ollama), Multimodal Models, Time Series (Forecasting, Classification, Anomaly Detection), Quantum ML, Explainable AI (XAI), Pretrained and fine-tuning large models (time series and materials science domain), MCP, LangGraph, Agentic AI

Frameworks & Tools: PyTorch, TensorFlow, Keras, Scikit-learn, HuggingFace, IBM Qiskit, Pandas, NumPy, MATLAB, Streamlit, MLFlow (MLOps)

Languages: Python, Java, C, SQL (Oracle), R

HPC & Infrastructure: BerzeLiUs National Supercomputer (NAISS), NVIDIA RTX 3090/5090/6000 GPU clusters (Docker framework), Linux, Windows

Research & Delivery: End-to-end ML pipelines, EU/WASP project delivery, interdisciplinary collaboration, technical writing & publication