Kedar Hippalgaonkar

Agency for Science, Technology and Research, Institute of Materials Research and Engineering

Papers

9

Total Citations

227

H-Index

7

About

No biography available yet.

Research Focus

Computer science7 · 201 citations
Engineering5 · 186 citations
Workflow3 · 170 citations
Machine learning3 · 159 citations
Database2 · 156 citations
Software engineering2 · 156 citations
Data science2 · 156 citations
Automation2 · 156 citations
Artificial intelligence2 · 143 citations
Robot2 · 143 citations
Deep learning1 · 134 citations
Domain (mathematical analysis)1 · 134 citations

Key Achievements

7
H-Index
9
Papers
227
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics
134 citations · 2023
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 51
🏛 Institutions: Agency for Science, Technology and Research, Institute of Materials Research and Engineering

Top Papers

  1. 1
    Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics
    134 citations · 2023
  2. 2
    An object-oriented framework to enable workflow evolution across materials acceleration platforms
    22 citations · 2022
  3. 3
    Closed‐Loop Multi‐Objective Optimization for Cu–Sb–S Photo‐Electrocatalytic Materials’ Discovery
    19 citations · 2023
  4. 4
    Accelerated automated screening of viscous graphene suspensions with various surfactants for optimal electrical conductivity
    14 citations · 2022
  5. 5
    Automated pipetting robot for proxy high-throughput viscometry of Newtonian fluids
    11 citations · 2023
  6. 6
    Optimization of liquid handling parameters for viscous liquid transfers with pipetting robots, a “sticky situation”
    9 citations · 2024
  7. 7
    Field‐Effect Transistors: Low‐Symmetry PdSe<sub>2</sub> for High Performance Thermoelectric Applications (Adv. Funct. Mater. 52/2020)
    7 citations · 2020
  8. 8
    pHbot: Self‐Driven Robot for pH Adjustment of Viscous Formulations via Physics‐informed‐ML**
    7 citations · 2023
  9. 9
    pHbot: Self-Driven Robot for pH Adjustment of Viscous Formulations via Physics-informed-ML
    4 citations · 2023

Key Collaborators

JJJayce Jian Wei Cheng6 shared papersACAniket Chitre3 shared papersAAAlexei A. Lapkin2 shared papersAKAndre K. Y. Low2 shared papersPQPablo Quijano Velasco2 shared papersTBTonio Buonassisi2 shared papersRCRobert C. M. Querimit2 shared papersCJChang Jie Leong2 shared papersJKJatin Kumar2 shared papersRIRiko I Made2 shared papersDBDaniil Bash2 shared papersYBYang Bai2 shared papersYLYee‐Fun Lim2 shared papersZHZi Hui Jonathan Khoo2 shared papersJKJames Kirkpatrick1 shared papersHXHuiqing Xie1 shared papersCYCarina Yi Jing Lim1 shared papersGZGang Zhang1 shared papersLWLong Wang1 shared papersJRJose Recatala‐Gomez1 shared papers
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