Arun Verma
I am a Postdoctoral Research Fellow
in Department of Computer Science
at National University of Singapore, where
I am advised by Prof. Bryan Kian Hsiang Low.
Prior to this, I obtained my Doctor of Philosophy (Ph.D.) degree from Indian Institute of Technology Bombay (IIT Bombay),
where Prof. Manjesh K. Hanawal
and Prof. N. Hemachandra supervised me.
My doctoral thesis received two awards:
Naik and Rastogi Excellence in Ph. D. Thesis Award
and COMSNETS Best Ph.D. Thesis Award.
My research interests primarily lie in developing and analyzing efficient and practical algorithms
for sequential decision-making problems by exploiting the underlying problem structures.
My recent research has focused on sequential decision-making under uncertainty problems,
with special emphasis on multi-armed bandits, Bayesian optimization, and reinforcement learning,
with their practical applications in a wide range of domains such as
LLMs, AutoML, Collaborative ML, and AI for Science.
Email   •  
Google Scholar   •  
Twitter
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Research
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"Basically, I'm not interested in doing research and I never have been... I'm interested in understanding,
which is quite a different thing. And often to understand something you have to work it out yourself
because no one else has done it." — David Blackwell
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Preprints
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Publications
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Exploiting Correlated Auxiliary Feedback in Parameterized Bandits
Arun Verma,
Dai Zhongxiang,
Yao Shu,
Bryan Kian Hsiang Low
NeurIPS, 2023
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Quantum Bayesian Optimization
Dai Zhongxiang,
Gregory Kang Ruey Lau,
Arun Verma,
Yao Shu,
Bryan Kian Hsiang Low,
Patrick Jaillet
NeurIPS, 2023
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Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-Linear Function Approximation
Chi Thanh Lam,
Arun Verma,
Bryan Kian Hsiang Low,
Patrick Jaillet
ICLR, 2023
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Federated Neural Bandit
Dai Zhongxiang,
Yao Shu,
Arun Verma,
Flint Xiaofeng Fan,
Bryan Kian Hsiang Low,
Patrick Jaillet
ICLR, 2023
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Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation
Yao Shu,
Dai Zhongxiang,
Weicong Sng,
Arun Verma,
Patrick Jaillet,
Bryan Kian Hsiang Low
ICLR, 2023
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FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery
Xinyi Xu,
Zhaoxuan Wu,
Arun Verma,
Chuan Sheng Foo,
Bryan Kian Hsiang Low
AISTATS, 2023
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Bayesian Optimization under Stochastic Delayed Feedback
Arun Verma*,
Dai Zhongxiang*,
Bryan Kian Hsiang Low (* denotes equal contribution)
ICML, 2022
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Stochastic Multi-Armed Bandits with Control Variates
Arun Verma,
Manjesh K. Hanawal
NeurIPS, 2021
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Online Algorithm for Unsupervised Sequential Selection with Contextual Information
Arun Verma,
Manjesh K. Hanawal,
Csaba Szepesvári,
Venkatesh Saligrama
NeurIPS, 2020
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Thompson Sampling for Unsupervised Sequential Selection
Arun Verma,
Manjesh K. Hanawal,
N. Hemachandra
ACML, 2020
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Learning and Fairness in Energy Harvesting: A Maximin Multi-Armed Bandits Approach
Debamita Ghosh
Arun Verma,
Manjesh K. Hanawal
IEEE SPCOM, 2020
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Stochastic Network Utility Maximization with Unknown Utility: Multi-Armed Bandits Approach
Arun Verma,
Manjesh K. Hanawal
IEEE INFOCOM, 2020
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Unsupervised Online Feature Selection for Cost-Sensitive Medical Diagnosis
Arun Verma,
Manjesh K. Hanawal,
N. Hemachandra
COMSNETS, 2020
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Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback
Arun Verma,
Manjesh K. Hanawal,
Arun Rajkumar,
Raman Sankaran
NeurIPS, 2019
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Distributed Algorithms for Efficient Learning and Coordination in Ad Hoc Networks
Arun Verma,
Manjesh K. Hanawal,
Rahul Vaze
WiOPT, 2019
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Online Algorithm for Unsupervised Sensor Selection
Arun Verma,
Manjesh K. Hanawal,
Csaba Szepesvári,
Venkatesh Saligrama
AISTATS, 2019
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Unsupervised Cost Sensitive Predictions with Side Information
Arun Verma,
Manjesh K. Hanawal
CoDS-COMAD, 2018
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Benchmarking Fast Data Platforms for the Aadhaar Biometric Database
Yogesh Simmhan,
Anshu Shukla,
Arun Verma,
WBDB, 2015
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Talks
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Invited talk on Sequential Decision Problems with Weak Feedback, as part of the Multi-Armed Bandits (CS6046) course at IIT Madras on May 4, 2021.
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Virtual seminar on Sequential Decision Problems with Weak Feedback, at RIKEN AIP, Japan on November 27, 2020.
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SequeL seminar on Censored Semi- Bandits: A Framework for Resource Allocation withCensored Feedback, at INRIA Lille, France on November 24, 2019.
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Talk on Online Algorithm for Cost-Sensitive Unsupervised Learning, at RIKEN AIP, Japan during my visit to Approximate Bayesian Inference (ABI) Team from April 9 — 16, 2019.
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Lighting talk on Unsupervised Cost Sensitive Predictions with Contextual Information at IEOR Day 2018, IIT Bombay on March 17, 2018.
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Awards
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COMSNETS 2022 Best Ph.D. Thesis Award for my Ph.D. thesis.
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Naik and Rastogi Excellence in Ph. D. Thesis Award (Best Thesis Award of IIT Bombay) for doctoral research.
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Microsoft Travel Grant (not used due to Covid-19 travel restrictions) and COMSNETS Association and LRN Foundation Travel Award for attending IEEE INFOCOM 2020.
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Travel Award from LinkedIn for attending FATE-ML workshop 2020 at IISc, Bengaluru, India.
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Google Travel Grant and NeurIPS Student Travel Award for attending NeurIPS 2019.
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Raman-Charpak Fellowship 2018 for visiting
SequeL Team of INRIA Lille, France.
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ACM-India/IARCS and Microsoft Travel Grant for attending AISTATS 2019.
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Technical Color Award of Hostel-14, IIT Bombay for year 2017-18 and 2018-19.
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Sports Color Award (Cricket) of Hostel-14, IIT Bombay for year 2017-18.
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Conference Travel Awards from HiPC 2016, CoDS 2017, CoDS-COMAD 2018, AUAPAF 2018.
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IITB Research Internship Award 2013-14 from Indian Institute of Technology Bombay.
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Academic Excellence Award (Gold Medal) for having the highest CGPA in B.Tech.(CSE).
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Services
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Program Committee Board member of IJCAI 2022-2024.
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Program Committee (PC) member/reviewer of
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2024: AAAI-24, ICLR-24, AISTATS-24, AAMAS-24, TMLR
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2023: AAAI-23, ICLR-23, AISTATS-23, AAMAS-23, IJCAI-23, ICML-23, NeurIPS-23, TMLR
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2022: AAAI-22, ICLR-22, AISTATS-22, IJCAI-22, ICML-22, NeurIPS-22, TMLR
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2021: AAAI-21, ICLR-21, IJCAI-21, ICML-21, NeurIPS-21
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2020: NeurIPS-20
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Website style cloned from here,
here, and
here.
Last updated on: September 22, 2023.
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