• Lecture materials (slides, Jupyter notebooks) can be found here.
  • Recorded lectures are available online here.
MLRS 2019 Schedule (public)

Poster Sessions

The poster sessions will be attended by fellow participants of various technical background, as well as our invited speakers. Presenting a poster creates a unique opportunity for you to exchange ideas with like-minded participants, learn from each other, and get feedback on your work from our speakers who are machine learning experts. We will have an award for the best poster presentation.

Here are some guidelines to help you prepare your best poster.

  • The poster does not have to be a completed work. It can just be an introduction to your field of expertise or problems you are encountering in your line of work.
  • The content of your poster does not have to be directly related to machine learning, but might benefit from having a machine learning component. Presenting a poster will allow you to interact with fellow MLRS participants, and get new ideas on how your work can be improved further.

The poster orientation is portrait and the size must be A1 (594 x 841mm). Please note that there may not be enough space to set up your poster if your poster is larger than this. There are five poster sessions (over lunch) taking place on five days. Each poster presenter is assigned to present in only one of these sessions. Please bring your poster on the day you are assigned to present (see below).


Session I: Monday 5th Aug 2019, 12:30 pm - 14:00 pm

  • Pornpra Chumnanvanichkul (Development of the air-conditioning and room thermal model environment for the air-conditioning control by reinforcement learning approach in Building Energy Management Systems.)
  • Chadapohn Chaosrikul (Modeling drug combination responses with graph neural networks)
  • Sira Sriswasdi (Accurate de novo peptide sequencing with artificial neural networks)
  • Porrameth Visuddhidham (Face Recognition System using FaceNet)
  • Chatree Asayatamanon (To predict the missing component in fuel gas supplying pipeline)
  • Yusuf Brima (Smart Meter Analytics: an ensemble approach towards granular load demand forecasting)
  • Thummanoon Kunanuntakij (Trading Simulation and Backtesting System)
  • Panyawut Sri-iesaranusorn (Virus Classification based on RNA Sequences using Machine Learning Platform)
  • Chanuwas Aswamenakul (Multimodal Analysis of Client Behavioral Change Coding in Motivational Interviewing)
  • Nitsawan Katerattanakul (PlanIt’s ML Roadmap)
  • Chuenchanok​ Nusaeng​ (TBC)
  • Rapeeporn Chamchong (Thai Handwritten Recognition using Deep Learning)
  • Aye Hninn Khine (Ensemble CNN and MLP with Nurse Notes for Intensive Care Unit Mortality)

Session II: Tuesday 6th Aug 2019, 12:30 pm - 14:00 pm

  • Chawan Piansaddhayanon (Race classification from face images)
  • Ishrat Malik (A Crowdsourcing translation: A knowledge sharing resource of Spatial and Temporal Cultural Heritage )
  • Muhammad Umair Hassan (Instance Retrieval Based on Combination of Geometric Features and Convolutional Neural Network)
  • Hafiz Muhammad Junaid Lodhi (Digital Eye for Everyone)
  • Watthanan Jatuviriyapornchai (Auto Diagnostics and Fault Detections in Manufacturing Processes)
  • Arthit Suriyawongkul (Masking non-public figure's personal information in social media text)
  • Pratch Piyawongwisal (TBC)
  • Kittipan Prasertsang (Hard Disk Drive Performance Improving)
  • Waqas Haider Khan Bangyal (TBC)
  • Xiangxi Gao (TBC)
  • Sathit Prasomphan (Mobile Application for Archaeological Site Image Content Retrieval and Automated Generating Image Descriptions with Neural Network)
  • Mahamat Moussa Abbas Ali (Integrated Deep Learning Model for High-Level Video Understanding)

Session III: Wednesday 7th Aug 2019, 12:30 pm - 14:00 pm

  • Wachiraphong Ratiphaphongthon (Data classification by using smooth generalized pinball-loss functions in Support Vector Machines)
  • Schwitz Thongpakdi (Machine learning for development of accelerator system design)
  • Tanakorn Likitapiwat (Long-term Investment Strategies with Machine Learning)
  • Chalat Limpongsawatt (Generating Thai Lyrics by Neural Network)
  • Thanarerk Thanakijsombat (Fraud Detection with Benford's Law)
  • Srisupang Thewsuwan (Enhancement of Complex Network-based Texture Characterization by Spatial Texture Analysis)
  • Parin Kittipongdaja (Opinion Sentiment Analysis of three Major Hospitals Services in Thailand using Machine Learning Techniques)
  • Khaing Hsu Wai (String Similarity Measures for Myanmar Language (Burmese))
  • Can Udomcharoenchaikit (Adversarial Evaluation of Robust Neural Sequential Tagging Methods for Thai Language)
  • Pranav Verma (Privacy preserving recommender system)
  • Isariya Suttakulpiboon (Machine Learning and Portfolio Risk Assessment)
  • Krittin Phornsiricharoenphant (Data Science at Scale with Pachyderm)
  • Worawich Phornsiricharoenphant (Structural variats in human genome)
  • Weerayut Buaphet (TBC)
  • Waiyawuth Euachongprasit (Clustering Tax Savers' Investment Pattern using K-Medoid and DTW for Marketing Analytics)

Session IV: Friday 9th Aug 2019, 12:30 pm - 14:00 pm

  • Raksit Raksasat (UV prediction with machine learning for skin diseases treatment with natural light)
  • Patsorn Sangkloy (Argoverse: 3D Tracking and Forecasting With Rich Maps)
  • Sachi Edirisinghe (Spatial Memory for a Social Robot Supporting Human-Robot Interactions)
  • Rabian Wangkeeree (Large-Scale Twin Parametric Support Vector Machine Using Generalized Pinball Loss Function)
  • Perasut Rungcharassang (How to handle streaming data for the classification problem)
  • Kerawit Somchaipeng (TBC)
  • Thanadon Fuengworatham (Cryptocurrency network analysis)
  • Teerada Teeravatcharoenchai (User quality classification)
  • Supachan Traitruengsakul (Building an Application of Correcting Grammatical Errors in Thai Deaf Students’ Written Thai Sentences)
  • MANON BOONBANGYANG (Protein structures predictions using machine learning techniques.)
  • Prin Mana-aporn (Lawlity: An advanced Thai-language legal research platform)
  • Ausdang Thangthai (TBC)
  • Sermkiat Lolak (Causal Inference of Thailand Road Accident)
  • Waradon Phokhinanan (Speech enhancement based on long short-term memory recurrent neural networks for hearing aids)
  • Panuthep Tasawong (Test case generator from human language)

Session V: Saturday 10th Aug 2019, 12:30 pm - 14:00 pm

  • Jatearoon Boondicharern (Using ML to Recognize First-Person Hand Gestures as Inputs)
  • Yufei Cui (Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex)
  • Sakkarin Krarat (TBC)
  • Jirasak Janrattana (Predictive Maintenance of Air Conditioning Units)
  • Sitapa Rujikietgumjorn (Sloth Search System for the Video Browser Showdown 2018)
  • Burin Naowarat (Automatic Speech Assessment for Dysarthria Rehabilitation)
  • Nuttapong Saelek (Scene recognition for waste management and city maintenance)
  • Arcchaporn Choukuljaratsiri (Abnormality Detection of User Amount in Home Buyer Website )
  • Ravit Pichayavet (Use of AI for estimation of object density from still images on low-cost devices)
  • Chatklaw Jareanpon (TBC)
  • Warin Poomarin (TBC)
  • Tanes Printechapat (Kernel-based copula processes in regression and classification)