Janardhan Rao Doppa
30 papers · 2011–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (12) π£ Hot Topic Early Bird
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Academic Marathon
(13)
π€
Dynamic Duo
(12)
π±
Topic Pioneer
π¬
Deep Specialist
(12)
π
Keyword Champion
(2)
π
Trend Setter
ποΈ
Keyword Collector
(135)
π
Century Club
(29)
π₯
Unstoppable
(6)
β‘
Prolific Year
(7)
Conferences
AAAI (11)
IJCAI (7)
ACML (3)
NIPS (3)
AISTATS (2)
CVPR (1)
EMNLP (1)
ICML (1)
JMLR (1)
Top co-authors
Research topics
Keywords
bayesian optimization
(11)
uncertainty quantification
(6)
multi-objective optimization
(5)
surrogate model
(5)
structured prediction
(4)
gaussian process
(4)
combinatorial optimization
(4)
pareto front
(3)
conformal prediction
(3)
hyperparameter optimization
(3)
prediction set
(2)
energy harvesting
(2)
black-box optimization
(2)
entropy search
(2)
acquisition function
(2)
time-series classification
(2)
discrete optimization
(2)
deep neural network
(2)
black-box function
(2)
pareto optimization
(2)
Papers
Sustainable Wearables for Health Applications and Beyond via Uncertainty-Aware Energy Management
IJCAI 2025
Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach
IJCAI 2024
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
NIPS 2024
Energy-Efficient Missing Data Imputation in Wearable Health Applications: A Classifier-aware Statistical Approach
IJCAI 2024
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
NIPS 2024
Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization
AAAI 2024
Offline Model-Based Optimization via Policy-Guided Gradient Search
AAAI 2024
Preference-Aware Constrained Multi-Objective Bayesian Optimization (Student Abstract)
AAAI 2024
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach
AISTATS 2023
Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis
AAAI 2023
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings
AISTATS 2023
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features (Extended Abstract)
IJCAI 2023
Adaptive Energy Management for Self-Sustainable Wearables in Mobile Health
AAAI 2022
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis
AAAI 2022
Bayesian Optimization over Permutation Spaces
AAAI 2022
Adaptive Experimental Design for Optimizing Combinatorial Structures
IJCAI 2021
Mercer Features for Efficient Combinatorial Bayesian Optimization
AAAI 2021
Bayesian Optimization over Hybrid Spaces
ICML 2021
Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach
AAAI 2020
Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework
AAAI 2020
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization
AAAI 2020
Max-value Entropy Search for Multi-Objective Bayesian Optimization
NIPS 2019
Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning
IJCAI 2019
Learning and Inference for Structured Prediction: A Unifying Perspective
IJCAI 2019
Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms
ACML 2017
Select-and-Evaluate: A Learning Framework for Large-Scale Knowledge Graph Search
ACML 2017
HC-Search for Structured Prediction in Computer Vision
CVPR 2015
Prune-and-Score: Learning for Greedy Coreference Resolution
EMNLP 2014
Structured Prediction via Output Space Search
JMLR 2014
Learning Rules from Incomplete Examples via Implicit Mention Models
ACML 2011