Scholar
Divyansha Lachi
Google Scholar ID: pqNdStYAAAAJ
Graduate Student, University of Pennsylvania
Citations & Impact
Citations
92
H-index
5
i10-index
2
Publications
11
Co-authors
0
Publications
Resume
Academic Achievements
- Publication: GraphFM: A Scalable Framework for Multi-Graph Pretraining; Sep 2024, Genomic bottleneck published at PNAS; Aug 2024, Stochastic Genomic Bottleneck preprint released, to be presented at NAISys 2024; Jul 2024, GraphFM preprint released.
Research Experience
- Graduate Research Assistant, Georgia Institute of Technology, advised by Prof. Eva Dyer; Research Assistant, Cold Spring Harbor Lab, advised by Prof. Anthony Zador; Research Intern, Brown University, advised by Prof. Thomas Serre; Research Intern, Max Plank Institute for Brain Research, advised by Prof. Moritz Helmstaedter; Research Intern, International Institute of Information Technology Hyderabad, advised by Prof. Suryakanth V Gangashetty.
Education
- Ph.D. in Machine Learning, Georgia Institute of Technology, advised by Prof. Eva Dyer; B.Tech. in Computer Science and Engineering, National Institute of Technology Silchar; Intermediate Science (Physics, Chemistry, Mathematics, Biology), Rukmani Birla Modern High School, Jaipur.
Background
- Ph.D. student in Machine Learning at Georgia Institute of Technology, advised by Prof. Eva Dyer. Main areas of interest include graph machine learning and neuro-inspired AI. Current research focuses on developing scalable frameworks for multi-graph pre-training and new methods for representation learning, particularly in domains with complex and unstructured data.
Miscellany
- Passionate about understanding how the brain works and believes that by understanding the brain, we can unlock new insights for science and AI.