Best PhD Thesis Award
Launched in 2023, the Remote Sensing Best PhD Thesis Award is presented annually to recognize young scholars who are deemed to have completed the most outstanding PhD thesis in the field of remote sensing with the hope of encouraging them to continue their work and make further contributions to their field. Applications for this award are open from January to July every year, and winners are announced in September.
The Prizes:
– CHF 800;
– A certificate;
– A voucher covering our Article Processing Charge (valid for one year).
Number of Winners: 1
Remote Sensing Best PhD Thesis Award
Winners announced
Eligibility and Requirements
– The candidate must be a PhD student or have recently completed a PhD who has produced a highly anticipated thesis with great academic potential;
– The PhD thesis must be their original work;
– The PhD thesis must have been defended in 2025.
– The PhD thesis must be their original work;
– The PhD thesis must have been defended in 2025.
List of Documents for Application
– An executive summary of the PhD thesis, in English, of around 3000 words;
– A letter from the PhD supervisor recommending the candidate for consideration for this award;
– The candidate’s CV, including a list of publications connected with the thesis;
– An electronic copy of the PhD thesis;
– A scanned copy of the PhD diploma (or certificate verifying the candidate’s study at a school or research institute as a PhD student who will graduate or participate in graduation thesis defenses).
– A letter from the PhD supervisor recommending the candidate for consideration for this award;
– The candidate’s CV, including a list of publications connected with the thesis;
– An electronic copy of the PhD thesis;
– A scanned copy of the PhD diploma (or certificate verifying the candidate’s study at a school or research institute as a PhD student who will graduate or participate in graduation thesis defenses).
Past Winners
Winner
- EAElena AragonesesElena AragonesesInstituto Geográfico Nacional, Spain
Award Committee
- DWDongdong WangProf. Dr. Dongdong WangPeking University, ChinaChairman
Riccardo BuccolieriProf. Dr. Riccardo BuccolieriUniversity of Salento, Italy
Ran MengProf. Dr. Ran MengHarbin Institute of Technology, China; National Key Laboratory of Smart Farming Technologies and Systems, China
Junshi XiaDr. Junshi XiaRIKEN Center for Advanced Intelligence Project (AIP), Japan
Remote Sens. - ISSN 2072-4292