Jyotiraditya Sikder | Machine Learning | Young Scientist Award
Mr. Jyotiraditya Sikder, Birla Institute of Technology & Science Pilani, India.
Jyotiraditya Sikder is a dynamic ComputationalโExperimental Chemist ๐งช and Industrial Engineer ๐ญ currently serving as a Guest Scientist at the Max Planck Institute of Colloids & Interfaces, Potsdam ๐ฉ๐ช. A dual-degree candidate at BITS Pilani ๐, heโs pursuing M.Sc. (Hons.) Chemistry and B.E. (Hons.) Chemical Engineering, graduating in 2026. His work bridges machine learning ๐ค, material simulations ๐งฌ, and experimental thermodynamics. From assisting in core chemical engineering courses to contributing to IEEE Access and Tribology International ๐ฐ, Jyotiraditya showcases remarkable interdisciplinary skills. With interests spanning academic and industrial research ๐, he brings computational rigor and hands-on engineering insight to the evolving world of science and technology ๐.
Publication Profiles
Scopus
Orcid
ย Education & Experienceย
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๐ M.Sc. (Hons.) Chemistry, BITS Pilani (2026)
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๐๏ธ B.E. (Hons.) Chemical Engineering, BITS Pilani (2026)
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๐งช Guest Scientist, Max Planck Institute of Colloids & Interfaces, Potsdam
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๐งโ๐ซ Teaching Assistant, Systems Engineering Principle (RMITโBITS Collaboration)
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๐ TA, Chemical Engineering Thermodynamics (BITS Pilani)
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๐ฐ๏ธ Delegate, DefSat Conference 2024, SIAโIndia
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๐ ๏ธ Fabrication Head, MBF Tinkerer’s Lab, BITS Pilani
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๐ Representative, Space Revolution Conf., California (2019)
Suitability for the Award
Mr. Jyotiraditya Sikder is a highly promising and industrious young scientist whose early accomplishments in the fields of materials characterization, computational chemistry, and industrial engineering make him a standout candidate for the Young Scientist Award. Currently serving as a Guest Scientist at the Max Planck Institute of Colloids & Interfaces, Potsdam, while pursuing an integrated M.Sc. (Hons.) in Chemistry and B.E. (Hons.) in Chemical Engineering at BITS Pilani, Jyotiraditya has demonstrated exceptional potential to contribute transformative advancements in science and technology. His interdisciplinary expertise spans from molecular simulations and machine learning to hands-on fabrication and data-driven materials discoveryโreflecting not only academic excellence but also a forward-looking vision essential for next-generation researchers.
ย Professional Development
Jyotiraditya’s professional journey is marked by a hands-on approach to science and interdisciplinary learning ๐ง ๐ฌ. As a Teaching Assistant in core engineering courses at BITS Pilani ๐จโ๐ซ, he has created tutorials, designed assessments, and supported student learning. At RMIT, he co-instructed system engineering modules ๐ฆ๐บ. His fabrication skills span FDM/SLA 3D printing, CNC machining, and welding ๐งฐ. He has contributed to defense-tech interactions at DefSat 2024 and MIT’s Sustainability Hackathon ๐ฑ. Heโs skilled in simulation software, coding, and data analytics ๐, aiming to translate theory into innovation across both academia and industry ๐.
ย Research Focusย
Jyotiradityaโs research spans computational chemistry ๐งช, molecular modeling ๐งฌ, materials tribology ๐ฉ, and machine learning-driven material design ๐ค. His work combines atomistic simulations (Gromacs, LAMMPS, AmberTools), drug design, and multi-objective optimization techniques like MOORA to analyze experimental deviation. He also uses SEM/XRD data for predictive analysis of materials. His contributions to journals like Tribology International and IEEE Access showcase his analytical depth ๐. With proficiency in deep learning (CNNs, Autoencoders), and statistical modeling, his goal is to drive innovation in materials science, sustainability, and industrial process design ๐ฟโ๏ธ.
ย Awards & Honorsย
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๐ฐ๏ธ DefSat 2024 Delegate, SIAโIndia, representing BITS Pilani
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๐ Space Revolution Conf. 2019, Southern California โ Paper Presentation on Martian Economy
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๐ Guest Scientist, Max Planck Institute, Germany
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๐ MIT Sustainable & Energy Hack 2023, Boston โ Developed green business solutions
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๐ฌ Publication Credit, Tribology International, ML-based material analysis
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๐ Contributor, IEEE Access, regional data analytics in atmospheric science
Publication Top Noted
๐ “Enhanced tribological performance of MoSโ and hBN-based composite friction materials” โ Tribology International, 2024ย ๐ |๐
๐ “Gravimetric Detection of Earthโs Rotation Using Crowdsourced Smartphone Observations” โ IEEE Access, 2019 ๐ | Cited by: 11 ๐ ๐