Faculty of Advanced Science and Technology

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Rangsit
Faculty of Advanced Science and Technology

Faculty of Advanced Science and Technology (FAST)
Asian Institute of Technology (AIT)
Official page | Managed by the Dean’s Office

09/10/2026

𝐀𝐈𝐓 𝐒𝐜𝐡𝐨𝐥𝐚𝐫𝐬 𝐆𝐫𝐚𝐧𝐭𝐞𝐝 𝐑𝐨𝐲𝐚𝐥 𝐀𝐮𝐝𝐢𝐞𝐧𝐜𝐞 𝐰𝐢𝐭𝐡 𝐇.𝐑.𝐇. 𝐏𝐫𝐢𝐧𝐜𝐞𝐬𝐬 𝐌𝐚𝐡𝐚 𝐂𝐡𝐚𝐤𝐫𝐢 𝐒𝐢𝐫𝐢𝐧𝐝𝐡𝐨𝐫𝐧 𝐚𝐭 𝐒𝐚 𝐏𝐚𝐭𝐡𝐮𝐦 𝐏𝐚𝐥𝐚𝐜𝐞

8 October 2026 - An AIT delegation led by the Chairman of the AIT Board of Trustees, General Dr. Boonsrang Niumpradit, together with officials of the Asian Institute of Technology (AIT) and 73 students from 12 countries, was granted a Royal Audience with Her Royal Highness Princess Maha Chakri Sirindhorn at Sa Pathum Palace, Bangkok, on 8 October 2026.

During the ceremony, the students received their Royal Thai Government (RTG) Scholarship certificates directly from Her Royal Highness Princess Maha Chakri Sirindhorn, in recognition of their selection under the following scholarship categories:

- 𝗛𝗶𝘀 𝗠𝗮𝗷𝗲𝘀𝘁𝘆 𝘁𝗵𝗲 𝗞𝗶𝗻𝗴'𝘀 𝗦𝗰𝗵𝗼𝗹𝗮𝗿𝘀𝗵𝗶𝗽𝘀
- 𝗛𝗲𝗿 𝗠𝗮𝗷𝗲𝘀𝘁𝘆 𝘁𝗵𝗲 𝗤𝘂𝗲𝗲𝗻'𝘀 𝗦𝗰𝗵𝗼𝗹𝗮𝗿𝘀𝗵𝗶𝗽𝘀
- 𝗟𝗼𝗼𝗺 𝗡𝗮𝗺 𝗞𝗵𝗼𝗻𝗴 𝗣𝗶𝗷𝗮𝗶 (𝗚𝗠𝗦) 𝗦𝗰𝗵𝗼𝗹𝗮𝗿𝘀𝗵𝗶𝗽𝘀

The 73 scholars represent 12 countries, reflecting AIT's enduring role as a regional hub for postgraduate education and international development: 𝗕𝗮𝗻𝗴𝗹𝗮𝗱𝗲𝘀𝗵 (𝟭), 𝗜𝗻𝗱𝗶𝗮 (𝟭), 𝗜𝗻𝗱𝗼𝗻𝗲𝘀𝗶𝗮 (𝟯), 𝗜𝗿𝗮𝗾 (𝟭), 𝗠𝘆𝗮𝗻𝗺𝗮𝗿 (𝟭𝟱), 𝗡𝗲𝗽𝗮𝗹 (𝟲), 𝗣𝗮𝗸𝗶𝘀𝘁𝗮𝗻 (𝟭), 𝗣𝗵𝗶𝗹𝗶𝗽𝗽𝗶𝗻𝗲𝘀 (𝟱), 𝗦𝗿𝗶 𝗟𝗮𝗻𝗸𝗮 (𝟭), 𝗧𝗵𝗮𝗶𝗹𝗮𝗻𝗱 (𝟯𝟱), 𝗩𝗶𝗲𝘁𝗻𝗮𝗺 (𝟯), 𝗮𝗻𝗱 𝗞𝘆𝗿𝗴𝘆𝘇𝘀𝘁𝗮𝗻 (𝟭).

The Royal Audience marks one of the most cherished milestones of the scholars' academic journey, celebrating the longstanding Royal patronage of the Royal Thai Government scholarship programs at AIT - a partnership that has shaped generations of leaders, engineers, and development professionals across Asia and beyond.

09/10/2026

🌍 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐨𝐟 𝐌𝐢𝐧𝐡𝐨, 𝐏𝐨𝐫𝐭𝐮𝐠𝐚𝐥 | 𝐄𝐫𝐚𝐬𝐦𝐮𝐬+ 𝐓𝐞𝐚𝐜𝐡𝐢𝐧𝐠 𝐌𝐨𝐛𝐢𝐥𝐢𝐭𝐲

𝗣𝗿𝗼𝗳. 𝗔𝘁𝘁𝗮𝗽𝗵𝗼𝗻𝗴𝘀𝗲 𝗧𝗮𝗽𝗮𝗿𝘂𝗴𝘀𝘀𝗮𝗻𝗮𝗴𝗼𝗿𝗻 from the Faculty of Advanced Science and Technology (FAST), AIT, recently completed an Erasmus+ teaching mobility at the University of Minho (UMinho), Portugal, from 28 September to 2 October 2026.

Based at UMinho’s Azurém Campus in Guimarães, 𝗣𝗿𝗼𝗳. 𝗣𝗼𝗻𝗴 worked closely with 𝗣𝗿𝗼𝗳. 𝗧𝗶𝗮𝗴𝗼 𝗠𝗮𝗻𝘂𝗲𝗹 𝗥𝗶𝗯𝗲𝗶𝗿𝗼 𝗚𝗼𝗺𝗲𝘀 from the Department of Industrial Electronics and Centro ALGORITMI, delivering a block lecture to students and researchers covering areas including Artificial Intelligence of Things (AIoT), wireless technologies, edge and embedded AI, trustworthy AI, and intelligent systems.

Beyond the classroom, the visit opened doors for deeper collaboration between AIT and UMinho, with discussions on joint research publications, student supervision, collaborative projects, academic exchanges, and future funding proposals.

A meaningful reminder that teaching mobility is more than a classroom visit. It is a platform for building lasting academic
partnerships across borders. 🌏

07/10/2026

Congratulations 𝗠𝘀. 𝗦𝗮𝗽𝗻𝗮 𝗧𝗵𝗮𝗽𝗮 on the successful completion of her Final Defense for the Master of Engineering in Data Science and Artificial Intelligence at the Faculty of Advanced Science and Technology (FAST), AIT. 🌟

Her thesis, titled "𝗚𝘂𝗶𝗱𝗲𝗹𝗶𝗻𝗲𝘀 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝗼𝗳 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗶𝗻 𝗛𝗶𝗴𝗵𝗲𝗿 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗕𝗵𝘂𝘁𝗮𝗻", addresses a timely and critical gap: while Generative AI (GenAI) has been widely adopted across higher education worldwide, Bhutan's colleges currently lack formal guidelines for its ethical use.

Through a mixed-methods study spanning eight English-medium colleges under the Royal University of Bhutan (RUB), Sapna surveyed and interviewed both faculty and students, uncovering some striking findings. GenAI adoption is exceptionally high, with 94% of students and 87% of faculty actively using these tools, yet a majority on both sides were either unaware of any institutional policy or believed none existed. Importantly, statistical testing showed that neither teaching experience nor academic level meaningfully influences how GenAI is perceived, suggesting that the need for clear guidance is universal across the institution.

Drawing on UNESCO's policy framework for GenAI in education, the thesis delivers five contextualized guidelines targeting ethical use, competence building, technical upskilling, and practical teaching and learning adjustments, offering a grounded foundation for Bhutan's higher education system to move forward responsibly.

A heartfelt congratulations to Ms. Sapna Thapa and her examination committee:
🔹 𝗗𝗿. 𝗖𝗵𝘂𝘁𝗶𝗽𝗼𝗿𝗻 𝗔𝗻𝘂𝘁𝗮𝗿𝗶𝘆𝗮 — Chairperson
🔹 𝗗𝗿. 𝗩𝗮𝘁𝗰𝗵𝗮𝗿𝗮𝗽𝗼𝗿𝗻 𝗘𝘀𝗶𝗰𝗵𝗮𝗶𝗸𝘂𝗹 — Committee Member
🔹 𝗗𝗿. 𝗦𝗲𝗶𝗻 𝗠𝗶𝗻𝗻 — Committee Member

05/10/2026

𝐀𝐈𝐓 𝐑𝐨𝐚𝐝𝐬𝐡𝐨𝐰 𝐋𝐢𝐯𝐞 – 𝟏𝟒 𝐎𝐜𝐭𝐨𝐛𝐞𝐫 𝟐𝟎𝟐𝟔

Thinking about pursuing a Master’s or PhD? Join our online roadshow to explore academic programs, scholarships, admissions, and student life directly with our deans, faculty members, students, and admissions team.

✅ Register now: https://tinyurl.com/RSlive14Oct2026
🗓️ Date: Wednesday, 14 October 2026
🕖 Time: 7:00–8:30 p.m. (Bangkok time)
💻 Venue: Zoom

🎁 Special Gift: Eligible participants who join the session will receive a FREE AIT English Entry Test voucher.

01/10/2026

𝗠𝗿. 𝗞𝗶𝘁𝘁𝗶𝗽𝗶𝘁 𝗖𝗵𝗶𝗻𝘁𝗮𝗽𝗮𝗻𝘆𝗮𝗸𝘂𝗹, a Master's student in Mechatronics and Machine Intelligence (MMI) at FAST, AIT, has successfully completed his thesis on one of the most exciting frontiers in modern engineering: making autonomous vehicles work reliably in the real world.

His thesis, titled "𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗠𝗲𝗰𝗵𝗮𝗻𝗶𝗰𝗮𝗹 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗺𝗲𝗻𝘁 𝗳𝗼𝗿 𝗮𝗻 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗗𝗿𝗶𝘃𝗶𝗻𝗴 𝗚𝗼𝗹𝗳 𝗖𝗮𝗿𝘁", tackles the Sim-to-Real gap in autonomous vehicles, the challenge of translating high-level control policies into reliable physical vehicle maneuvers. Using the AIT campus as a real-world testing environment, he upgraded a previous golf cart prototype with smarter controls, better actuators, and a more capable perception system.

The work covers three key areas: a Hybrid Fuzzy-PID closed-loop controller for steering and braking, achieving a rise time of just 0.36 seconds and reducing steering tracking error by 22% over the open-loop baseline; a real-time obstacle detection pipeline fusing YOLOv8 object detection with monocular depth estimation, validated up to 17 meters with 13.3 ms inference latency; and UFLDv2 lane detection integrated into the PathRover GUI, proven robust against changing light conditions and faded road markings on campus roads. The system also features an Adaptive Cruise Control mechanism that triggers a full brake at 4 meters or less from an obstacle and automatically resumes cruising speed once the path is clear.

A heartfelt congratulations to Mr. Kittipit and his examination committee:
🔹 𝗣𝗿𝗼𝗳. 𝗠𝗼𝗻𝗴𝗸𝗼𝗹 𝗘𝗸𝗽𝗮𝗻𝘆𝗮𝗽𝗼𝗻𝗴 — Chairperson
🔹 𝗗𝗿. 𝗕𝗿𝗮𝗻𝗲𝘀𝗵 𝗠. 𝗣𝗶𝗹𝗹𝗮𝗶 — Committee Member
🔹 𝗗𝗿. 𝗖𝗵𝗮𝗻𝘁𝗿𝗶 𝗣𝗼𝗹𝗽𝗿𝗮𝘀𝗲𝗿𝘁 — Committee Member

30/09/2026

🌏 𝐁𝐞𝐲𝐨𝐧𝐝 𝐭𝐡𝐞 𝐒𝐚𝐭𝐞𝐥𝐥𝐢𝐭𝐞 𝐕𝐢𝐞𝐰 | 𝐀𝐧 𝐑𝐒𝐆𝐈𝐒 𝐒𝐭𝐮𝐝𝐞𝐧𝐭'𝐬 𝐉𝐨𝐮𝐫𝐧𝐞𝐲 𝐚𝐭 𝐭𝐡𝐞 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐨𝐟 𝐓𝐨𝐤𝐲𝐨

What happens when an FAST student takes his remote sensing skills to one of Asia's leading geospatial research hubs?

𝗣𝗵𝘂𝗺 𝗖𝗵𝘂𝗲𝗻𝗴𝗽𝗶𝘁𝘂𝗸-𝘂-𝗱𝗼𝗺, a student in the Remote Sensing and Geographic Information Systems (RSGIS) program at FAST, AIT, spent six months as an exchange student at the University of Tokyo, hosted by the W. Takeuchi Laboratory at the Institute of Industrial Science.

During his exchange, Phum immersed himself in cutting-edge research in satellite data processing and disaster monitoring, enrolled in five graduate courses, and participated in weekly lab seminars alongside researchers from across Asia. The multicultural environment pushed him to think about his own research in a far more comparative way, drawing connections between flood monitoring in Thailand, the Philippines, and Japan.

Beyond the lab, he experienced cherry blossom season, Japanese festivals, historic temples, and even visited sites affected by earthquakes and tsunamis, connecting lived experience directly with his academic work.

He returns to AIT with broader knowledge, stronger research skills, and a truly international outlook.

28/09/2026

🧠 𝐒𝐭𝐮𝐝𝐞𝐧𝐭 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐒𝐩𝐨𝐭𝐥𝐢𝐠𝐡𝐭 | 𝐌𝐚𝐤𝐢𝐧𝐠 𝐍𝐞𝐮𝐫𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥 𝐒𝐜𝐫𝐞𝐞𝐧𝐢𝐧𝐠 𝐌𝐨𝐫𝐞 𝐀𝐜𝐜𝐞𝐬𝐬𝐢𝐛𝐥𝐞 𝐰𝐢𝐭𝐡 𝐖𝐞𝐚𝐫𝐚𝐛𝐥𝐞 𝐄𝐄𝐆

𝗠𝘀. 𝗥𝗮𝗸𝘀𝗵𝘆𝗮 𝗟𝗮𝗺𝗮 𝗠𝗼𝗸𝘁𝗮𝗻, Master's student in 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 at FAST, AIT, is exploring whether affordable, consumer-grade EEG technology can open new doors for accessible neurological monitoring.

Her project, titled "𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗡𝗲𝘂𝗿𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗔𝗯𝗻𝗼𝗿𝗺𝗮𝗹𝗶𝘁𝘆 𝗳𝗿𝗼𝗺 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿-𝗚𝗿𝗮𝗱𝗲 𝗘𝗘𝗚: 𝗔 𝟭𝟬𝟬-𝗣𝗮𝗿𝘁𝗶𝗰𝗶𝗽𝗮𝗻𝘁 𝗥𝗲𝘀𝘁𝗶𝗻𝗴-𝗦𝘁𝗮𝘁𝗲 𝗗𝗮𝘁𝗮𝘀𝗲𝘁 𝗮𝗻𝗱 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲", uses an 8-channel g.tec Unicorn wearable EEG headset to collect resting-state brain activity recordings from 100 participants. The complete pipeline covers EEG signal acquisition, preprocessing, feature extraction, and machine learning classification, with a particular focus on alpha-band activity and alpha reactivity, known as the Berger effect.

With approximately 95.7% usable recordings across all 100 participants, the study explored logistic regression, random forest, and support vector machine models, achieving an overall classification performance of around 85.8%. The findings suggest that low-cost wearable EEG can provide meaningful signal characteristics for automated neurological abnormality screening, potentially supporting edge-based monitoring in resource-limited settings.

We would also like to acknowledge the faculty members who supported this research presentation:

🔹 𝗗𝗿. 𝗖𝗵𝗮𝗸𝗹𝗮𝗺 𝗦𝗶𝗹𝗽𝗮𝘀𝘂𝘄𝗮𝗻𝗰𝗵𝗮𝗶
🔹 𝗗𝗿. 𝗕𝗿𝗮𝗻𝗲𝘀𝗵 𝗠. 𝗣𝗶𝗹𝗹𝗮𝗶
🔹 𝗗𝗿. 𝗖𝗵𝗮𝗻𝘁𝗿𝗶 𝗣𝗼𝗹𝗽𝗿𝗮𝘀𝗲𝗿𝘁
🔹 𝗣𝗿𝗼𝗳. 𝗠𝗼𝗻𝗴𝗸𝗼𝗹 𝗘𝗸𝗽𝗮𝗻𝘆𝗮𝗽𝗼𝗻𝗴

This research was proudly supported by the 𝗧𝗵𝗮𝗶𝗹𝗮𝗻𝗱 𝗥𝗜𝗦𝗘 𝗙𝘂𝗻𝗱.

Note: This work is a research prototype and is not a medical device. Clinical validation on appropriate patient populations would be required before any diagnostic claims can be made.

24/09/2026

🧠 𝐒𝐭𝐮𝐝𝐞𝐧𝐭 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐒𝐩𝐨𝐭𝐥𝐢𝐠𝐡𝐭 | 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐧𝐠 𝐒𝐭𝐫𝐨𝐤𝐞 𝐑𝐢𝐬𝐤 𝐖𝐡𝐞𝐧 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐃𝐚𝐭𝐚 𝐢𝐬 𝐈𝐧𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞

𝗠𝘀. 𝗪𝘂𝘁 𝗬𝗲𝗲 𝗔𝘂𝗻𝗴, PhD student in Data Science and Artificial Intelligence at FAST, AIT, is tackling one of the most pressing challenges in clinical AI: what happens when the data needed to make a life-critical prediction is simply not there?

Her research, titled "Stroke Risk Prediction Using Graph Attention Networks for Handling Missing Data at Inference Time", addresses the reality that real-world Electronic Health Records are frequently incomplete when a patient arrives at the clinic. Instead of guessing missing values through imputation, which often introduces harmful biases, her approach uses a Graph Attention Network (G*T) that structures patient data as a graph and simply removes connections for missing data points, making predictions based only on what is actually observed.

Evaluated on 4,908 patient records, the model demonstrated remarkable resilience under extreme conditions. When 70% of patient data was missing, traditional models like Logistic Regression saw their recall collapse to just 0.25, while her G*T model maintained an AUC-ROC of 0.768 and an average recall of 0.730. The model also offers explainability, allowing clinicians to see exactly which data points are driving a prediction and how the model adapts when key indicators go missing.

Supervised by 𝗗𝗿. 𝗖𝗵𝗮𝗻𝘁𝗿𝗶 𝗣𝗼𝗹𝗽𝗿𝗮𝘀𝗲𝗿𝘁, this work is a meaningful step toward AI that works with the messy reality of clinical environments rather than against it. 🌏

22/09/2026

Congratulations 𝗠𝗿. 𝗣𝗮𝘄𝗮𝗻 𝗕𝗶𝗸𝗿𝗮𝗺 𝗥𝗮𝗻𝗮 on the successful completion of his Final Defense for the Master of Engineering in Information Management Systems at the Faculty of Advanced Science and Technology (FAST), AIT. 🌟

His thesis, titled "𝗔𝗿𝗴𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗥𝗲𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗜𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁 𝗗𝗶𝘀𝗽𝘂𝘁𝗲𝘀", takes a fascinating and rigorous approach to a real-world problem: how do we determine which arguments should survive in an insurance dispute?

Drawing on Dung's Abstract Argumentation Framework (AAF), Pawan applied formal argumentation theory to two real-world insurance dispute cases from the Indian legal system, modelling each claim, counter-claim, and defeating condition as a structured argument exchange. His analysis demonstrated that in both cases, the final High Court decisions produced semantically correct and uniquely stable outcomes, while earlier rulings diverged due to selective evidence acceptance and failure to apply key legal principles such as contra proferentem and burden-of-proof shifts.

A heartfelt congratulations to Mr. Pawan Bikram Rana and the examination committee:
🔹 𝗣𝗿𝗼𝗳. 𝗣𝗵𝗮𝗻 𝗠𝗶𝗻𝗵 𝗗𝘂𝗻𝗴 — Chairperson
🔹 𝗗𝗿. 𝗖𝗵𝘂𝘁𝗶𝗽𝗼𝗿𝗻 𝗔𝗻𝘂𝘁𝗮𝗿𝗶𝘆𝗮 — Committee Member
🔹 𝗗𝗿. 𝗖𝗵𝗮𝗻𝘁𝗿𝗶 𝗣𝗼𝗹𝗽𝗿𝗮𝘀𝗲𝗿𝘁 — Committee Member

21/09/2026

🎉 𝐅𝐀𝐒𝐓 𝐒𝐭𝐮𝐝𝐞𝐧𝐭𝐬 𝐑𝐞𝐜𝐞𝐢𝐯𝐞 𝐅𝐮𝐥𝐥 𝐌𝐚𝐬𝐭𝐞𝐫'𝐬 𝐃𝐞𝐠𝐫𝐞𝐞 𝐒𝐜𝐡𝐨𝐥𝐚𝐫𝐬𝐡𝐢𝐩𝐬 𝐟𝐫𝐨𝐦 𝐃𝐞𝐥𝐭𝐚 𝐄𝐥𝐞𝐜𝐭𝐫𝐨𝐧𝐢𝐜𝐬 (𝐓𝐡𝐚𝐢𝐥𝐚𝐧𝐝)

We are proud to share that two students from the Faculty of Advanced Science and Technology (FAST), AIT have been awarded full Master's degree scholarships under the Delta Master's Degree Program 2026 by Delta Electronics (Thailand) Public Company Limited.

𝗠𝗲𝗲𝘁 𝘁𝗵𝗲 𝗥𝗲𝗰𝗶𝗽𝗶𝗲𝗻𝘁𝘀

● 𝗠𝘀. 𝗠𝗼𝗲 𝗣𝘆𝗮𝗲 𝗣𝘆𝗮𝗲 𝗞𝘆𝗮𝘄
　◦ Computer Science and Software Engineering (𝗖𝗦𝗦𝗘)

● 𝗠𝗿. 𝗟𝘄𝗶𝗻 𝗠𝗼𝗲 𝗔𝘂𝗻𝗴
　◦ Digital Technology and Enterprise Information Management (𝗗𝗧𝗘𝗜𝗠)

(𝘉𝘰𝘵𝘩 𝘴𝘱𝘦𝘤𝘪𝘢𝘭𝘪𝘻𝘦𝘥 𝘶𝘯𝘥𝘦𝘳 𝘵𝘩𝘦 𝘊𝘰𝘮𝘱𝘶𝘵𝘦𝘳 𝘚𝘤𝘪𝘦𝘯𝘤𝘦 𝘢𝘯𝘥 𝘊𝘰𝘮𝘮𝘶𝘯𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 (𝘾𝙎𝘾𝙏) 𝘱𝘳𝘰𝘨𝘳𝘢𝘮)

𝗦𝗰𝗵𝗼𝗹𝗮𝗿𝘀𝗵𝗶𝗽 𝗩𝗮𝗹𝘂𝗲

● 𝗧𝗛𝗕 𝟭.𝟯𝟯 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗽𝗲𝗿 𝗿𝗲𝗰𝗶𝗽𝗶𝗲𝗻𝘁

The scholarship covers full tuition and registration fees, monthly bursary and accommodation allowances, medical insurance, and other related expenses, along with guaranteed employment at Delta Electronics (Thailand) after graduation.

The scholarship agreement signing ceremony was held on 15 September 2026 at the Delta R&D Center, Thailand, with 𝗗𝗿. 𝗦𝗲𝗶𝗻 𝗠𝗶𝗻𝗻, Assistant Professor in Data Science and AI at FAST, representing the faculty as academic advisor to one of the recipients.

Congratulations, Ms. Moe Pyae Pyae Kyaw and Mr. Lwin Moe Aung! 🌟

💡 𝐇𝐨𝐰 𝐭𝐨 𝐀𝐩𝐩𝐥𝐲 & 𝐋𝐞𝐚𝐫𝐧 𝐌𝐨𝐫𝐞
Apply via the 𝗔𝗜𝗧 𝗢𝗻𝗹𝗶𝗻𝗲 𝗔𝗱𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗣𝗼𝗿𝘁𝗮𝗹 and indicate your interest in the scholarship.
🔗 https://tinyurl.com/mp2htznt

ที่อยู่

Asian Institute Of Technology
Rangsit
12120

เว็บไซต์

https://fast.ait.ac.th/

แจ้งเตือน

เป็นคนแรกที่รู้ข่าว: เราจะส่งอีเมลแจ้งเมื่อ Faculty of Advanced Science and Technology โพสต์ข่าวสารและโปรโมชั่น อีเมลของคุณจะไม่ถูกนำไปใช้เพื่อวัตถุประสงค์อื่น และคุณสามารถยกเลิกการรับข่าวสารได้ทุกเมื่อ

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