Romrawin (Jin) Chumpu
Proud to stay multidisciplinary!
I'm an RA at VISTEC, working on Vision-Language Models and WangchanX fine-tuning models.
romrawin.c [at] vistec.ac.th |
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Github
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Non mi legga chi non e matematico. - Leonardo da Vinci
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I think my brain π§ processes visual things easily; my interests mainly lie on visual computing, which are physical simulation, computational engineering design, vision, graphics, and machine learning - all of these began with math.
I'm grateful to be supported by SCiUS and Junior Science Talent Project (JSTP) scholarship in mathematics since high school until now.
I love granny activities - crocheting, planting, or reading π§Άπͺ΄π
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Physics-informed graph neural networks accelerating microneedle simulations towards novelty of micro-nano scale materials discovery
Romrawin Chumpu,
Chun-Lin Chu,
Tanyakarn Treeratanaphitak,
Sanparith Marukatat,
Shu-Han Hsu
Engineering Application of Artificial Intelligence, 2023
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Synthetic face generation from in-the-wild face components swapping
Romrawin Chumpu,
Pitchayagan Temniranrat,
Sanparith Marukatat
17th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP), 2022
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Code
Presented online at OAMLS: Online Asian Machine Learning School as a part of 14th Asian Conference on Machine Learning (ACML 2022), Hyderabad, India.
Poster
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Z-Face Sketch : Automatic Placement of Face Composites for Composite Sketches
Wisarut Bholsithi,
Nonlapas Wongwaen,
Chanjira Sinthanayothin,
Romrawin Chumpu,
Police Colonel Nitiphat,
Police Colonel Chaiwat Burana
International Conference on Digital Government Technology and Innovation (DGTi-CON), 2022
Paper
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Simulation and Control of Drug Release on Microneedle using Machine Learning Technique
Romrawin Chumpu
Advisor: Assoc. Prof. Dr. Shu-Han Hsu
Co-Advisor: Dr. Sanparith Marukatat
Functional Advanced Materials Engineering (FAME) laboratory
Thammasat University Library, 2021
Thesis
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Summary
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Asian Face Generation
Romrawin Chumpu
Advisors: Dr. Sanparith Marukatat,
Nonlapas Wongwaen
National Electronics and Computer Technology Center (NECTEC)
Super AI Engineer Development Program Season 1, Level 3 Apprenticeship
π₯ Advanced AI and Best Poster Award, 2021
Poster
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Two-Way Coupling Computational Fluid Dynamics with Explicit Dynamics Modeling and Simulation of Microneedle
Romrawin Chumpu,
Shu-Han Hsu,
Chun-Lin Chu
International Conference in Mathematics and Applications (ICMA-MU), 2020
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The association between dengue incidences and provincial-level weather variables in Thailand from 2001 to 2014
Romrawin Chumpu,
Nirattaya Khamsemanan,
Cholwich Nattee
PLOS One, 2019
Paper
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Simulation-based Design of Aeroponics Nutrient Distribution System Using multiple CFD
Romrawin Chumpu
Advisor: Assoc. Prof. Nasser Mohieddin Abukhdeir
Computational MultiPhysics (CoMPhys) Research Group
CHE499 Directed Research Project Department of Chemical Engineering, University of Waterloo, 2019
Paper
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Influenza Activity and Province-level Weather Variations in Thailand, 2009 to 2014, Using Random Forest Time-series Approach
Romrawin Chumpu,
Nirattaya Khamsemanan,
Cholwich Nattee
Chiang Mai Journal of Science, 2018
Paper
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Computational Fluid Dynamics (CFD) analysis of an antibiotic drug eluting on orthopedic implants simulation
Romrawin Chumpu
Advisor: Prof. Peter L. Douglas
Summer Research Internship Department of Chemical Engineering, University of Waterloo, 2018
Paper
Acknowledgement- Thank you for being the first who introduced me to the world of physics simulation, especially CFD.
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Modern Image Search
Romrawin Chumpu
Super AI Engineer Development Program Season 4, January, 2024
Course Page
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Slide
An introductory course on modern image search, including introduction of SOTA multimodal models and hands-on coding tutorials.
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Super AI Engineer the Reality Show
One of the ten cast members selected from 8000 competitors nationalwide
Representative of woman in AI (3/10) and a role in AI commutiy as a researcher
π Finalist Team
On-air via national TV channel in 5/5 episodes from November 2022 to January 2023
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Ad Poster
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NRL Lab Seminar: Re-thinking Inverse Graphics with Large Language Models
by Kulits et al., 2024, accepted at TMLR
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