Amit Ranjan Trivedi

University of Illinois Chicago, University of Illinois Urbana-Champaign

Papers

9

Total Citations

73

H-Index

4

About

No biography available yet.

Research Focus

Computer science9 · 73 citations
Artificial intelligence9 · 73 citations
Machine learning5 · 55 citations
Dropout (neural networks)2 · 45 citations
Mathematics3 · 42 citations
Inference1 · 32 citations
Monte Carlo method1 · 32 citations
Probabilistic logic1 · 32 citations
Enhanced Data Rates for GSM Evolution5 · 23 citations
Robot2 · 16 citations
Pattern recognition (psychology)2 · 16 citations
Robotics2 · 16 citations

Key Achievements

4
H-Index
9
Papers
73
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
MC-CIM: Compute-in-Memory With Monte-Carlo Dropouts for Bayesian Edge Intelligence
32 citations · 2022
📈 Most Prolific Year: 2024 (4 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: University of Illinois Chicago, University of Illinois Urbana-Champaign

Top Papers

  1. 1
    MC-CIM: Compute-in-Memory With Monte-Carlo Dropouts for Bayesian Edge Intelligence
    32 citations · 2022
  2. 2
    Lightweight, Uncertainty-Aware Conformalized Visual Odometry
    13 citations · 2023
  3. 3
    Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge
    9 citations · 2024
  4. 4
    STARNet: Sensor Trustworthiness and Anomaly Recognition via Lightweight Likelihood Regret for Robust Edge Autonomy
    7 citations · 2024
  5. 5
    Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D Sensing
    4 citations · 2024
  6. 6
    Navigating the Unknown: Uncertainty-Aware Compute-in-Memory Autonomy of Edge Robotics
    3 citations · 2024
  7. 7
    Intelligent Sensing-to-Action for Robust Autonomy at the Edge: Opportunities and Challenges
    2 citations · 2025
  8. 8
    STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy
    2 citations · 2023
  9. 9
    Uncertainty-Aware Deep Reinforcement Learning with Calibrated Quantile Regression and Evidential Learning
    1 citations · 2025

Key Collaborators

TTTheja Tulabandhula6 shared papersNDNastaran Darabi5 shared papersACAlex C. Stutts4 shared papersSTSina Tayebati4 shared papersSNSathya N. Ravi3 shared papersDJDinithi Jayasuriya3 shared papersDEDanilo Erricolo3 shared papersPSPriyesh Shukla2 shared papersDKDivake Kumar2 shared papersMMMohit Mittal1 shared papersKRKaushik Roy1 shared papersAKAdarsh Kumar Kosta1 shared papersSMSaibal Mukhopadhyay1 shared papersHKHemant Kumawat1 shared papersPPPriyadarshini Panda1 shared papersWGWilfred Gomes1 shared papersYVYeshwanth Venkatesha1 shared papersSSS. Sureshkumar1 shared papersNJNethmi Jayasinghe1 shared papersSSS. Senthilkumar1 shared papers
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