FUSION
FUnctionality Sharing In Open eNvironments
Heinz Nixdorf Chair for Distributed Information Systems
 

Vamsi Krishna Kommineni

PhD Candidate

Leutragraben 1, Jentower , 07743 Jena , Room: 21N03

+49 (0) 3641-9-46448

Join date: 2020-11-01

https://orcid.org/0000-0001-6168-3085

Curriculum Vitae

2020 – present

PhD thesis “Identifying drivers of intra- and interspecific leaf trait variation in space and time from digitized herbarium specimen using computer vision approaches.” at the Friedrich-Schiller-Universität Jena, Germany

2019

Master thesis “Identifying drivers of intraspecific leaf trait variation in  space and time from digitized herbarium specimens using machine learning approaches.” at the Max Planck Institute for Biogeochemistry, Jena, Germany

2016-2020

Master Studies in the Scientific Instrumentation at Ernst-Abbe-Hochschule Jena, Jena, Germany

2016

Bachelor thesis “Design Analysis and fabrication of Multidimensional trolley” in the “Innovation Centre, Guru Nanak Institutions, Hyd” at the Guru Nanak Institute of Technology, Hyderabad, India

2012 – 2016

Bachelor Studies in the “Mechanical Engineering” at the Jawaharlal Nehru Technological University Hyderabad, Telangana, India

Professional Activities

Ph.D. Thesis Focus: 

Leaf traits are important and often used to understand plant and functional diversity, but the numbers of leaf trait values are still strongly limited in space and time. To overcome the leaf trait data limitations, interdisciplinary research is required. In my Ph.D. research, we mainly concentrate on the automatic extraction of leaf trait-related information for around 15 million Digital Herbarium Specimen (DHS) images using deep neural networks. In the second step, we focus on building an intelligent machine learning system and analyzing intra- and interspecific leaf trait variation in space and time.

Master Thesis Focus:

  • Evaluating global patterns of leaf size using machine learning approaches.
  • Extraction of leaf morphological traits from digital images using image processing tool (Trait Ex).
  • Creation of workflows to extract data from various environmental databases.
  • The work was performed in Python using the following libraries: Scikitlearn, Keras, Pdpbox, Matplotlib, Pandas, Numpy, Matplotlib, Pandas, Csv, PIL, time, etc.

Apart from the thesis focuses,

  • Acted as a vice president for the National Service Scheme (NSS) at the Guru Nanak Institute of Technology (GNIT), Hyderabad.
  • Lead the project “Design Analysis and fabrication of Multidimensional trolley,” which consists of four people.
  • Team member in different multi-disciplinary research groups

 

Research Area

  • Exploring different types of machine learning, deep learning, and computer vision techniques.
  • Data management and biodiversity informatics.

More details can be found here: https://www.bgc-jena.mpg.de/functionalbiogeography/index.php/People/VamsiKommineni

 

Publications

2021

Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries
Vamsi Krishna Kommineni, Susanne Tautenhahn, Pramod Baddam, Jitendra Gaikwad, Barbara Wieczorek, Abdelaziz Triki, Jens Kattge
Biodiversity Data Journal 13.7.2021

2020

Understanding Intraspecific Trait Variability Using Digital Herbarium Specimen Images
Vamsi Krishna Kommineni, Jens Kattge, Jitendra Gaikwad, Pramod Baddam, Susanne Tautenhahn
Biodiversity Information Science and Standards 1.10.2020