Q97454550

Franco-Slovak Artificial Intelligence scientist

Person human Q97454550

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Q97454550

Summary

Q97454550 is a human^[1]. His place of birth was Košice^[2]. He worked as a university teacher^[3], computer scientist^[4], researcher^[5], artificial intelligence researcher^[6], and entrepreneur^[7].

Key Facts

Born in Košice^[2], Q97454550…
Q97454550 held citizenship in Slovakia^[8].
Q97454550 held citizenship in France^[9].
Slovak was Q97454550's native language^[10].
Q97454550's professions included university teacher^[3].
Q97454550's professions included computer scientist^[4].
Q97454550's professions included researcher^[5].
Q97454550's professions included artificial intelligence researcher^[6].
Q97454550 worked as an entrepreneur^[7].
Q97454550 worked as an angel investor^[11].
Q97454550's field of work was machine learning^[12].
Q97454550's field of work was artificial intelligence^[13].
Q97454550's field of work was deep learning^[14].
Q97454550's field of work was game theory^[15].
Q97454550's field of work was multi-armed bandit^[16].
Q97454550's field of work was natural language processing^[17].
Q97454550 held the position of Principal Llama Scientist^[18].
Q97454550 held the position of Founding Researcher^[19].
Q97454550 held the position of External Lecturer^[20].
Q97454550 held the position of ESET Science Award Envoy^[21].
Q97454550 held the position of ambassador^[22].
Q97454550 was employed by Institut National de Recherche en Informatique et en Automatique^[23].
Q97454550 was employed by École normale supérieure Paris-Saclay^[24].
Among Q97454550's employers was Isara Labs^[25].
Q97454550's doctoral advisor was Milos Hauskrecht^[26].

Body

Origins and Family

Q97454550 was born in Košice^[2]. Slovak was his native language^[10].

Education

Q97454550's doctoral advisor was Milos Hauskrecht^[26]. Academic degrees include habilitation to Supervise Research^[27], Doctor of Philosophy^[28], and Master of Science^[29].

Career and Affiliations

Recorded occupations include university teacher^[3], computer scientist^[4], researcher^[5], artificial intelligence researcher^[6], entrepreneur^[7], and angel investor^[11]. Fields of work include machine learning^[12], an academic discipline^[30]; artificial intelligence^[13], a type of technology^[31]; deep learning^[14]; game theory^[15], a branch of mathematics^[32]; multi-armed bandit^[16]; and natural language processing^[17], an academic discipline^[33]. Employers include Institut National de Recherche en Informatique et en Automatique^[23], a French public establishment of a scientific and technological character^[34], in France^[35], founded in 1967^[36], headquartered in Le Chesnay^[37]; École normale supérieure Paris-Saclay^[24], an educational institution^[38], in France^[39], founded in 1912^[40], headquartered in Gif-sur-Yvette^[41]; and Isara Labs^[25], a business^[42], in France^[43], headquartered in San Francisco^[44]. Positions held include Principal Llama Scientist^[18]; Founding Researcher^[19]; External Lecturer^[20]; ESET Science Award Envoy^[21]; and ambassador^[22], a diplomatic rank^[45]. Doctoral students include Jean-Bastien Grill^[46], Daniele Calandriello^[47], Giorgio Racca^[48], Côme Fiegel^[49], Daniil Tiapkin^[50], and Lisa Bedin^[51].

Recognition

Awards received include ICML Best Paper Award^[52], an award^[53]; Inria Prime d'excellence scientifique^[54], an award^[55]; ICML Top 10 Reviewer Award^[56]; ICML Reviewer Award^[57]; Distinguished Alumni of Comenius University^[58]; and Google Best Paper Award^[59].

FAQs

Where was Q97454550 born?

Q97454550's place of birth was Košice^[2].

What did Q97454550 do for work?

Q97454550 worked as university teacher^[3], computer scientist^[4], researcher^[5], artificial intelligence researcher^[6], and entrepreneur^[7].

What awards did Q97454550 receive?

Honors received include ICML Best Paper Award^[52], Inria Prime d'excellence scientifique^[54], Inria Prime d'excellence scientifique^[60], and ICML Top 10 Reviewer Award^[56].

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Quick Facts

Instance of human

Sex or gender male

Place of birth Košice

Country of citizenship Slovakia, France

Occupation university teacher, computer scientist, researcher, artificial intelligence researcher, entrepreneur, angel investor

Employer Google DeepMind, Institut National de Recherche en Informatique et en Automatique, Meta, University of Pittsburgh, Intel, Slovak Academy of Sciences, École normale supérieure Paris-Saclay, Isara Labs

Field of work machine learning, artificial intelligence, deep learning, game theory, multi-armed bandit, natural language processing, self-supervised learning, large language model, statistics, computer science, reinforcement learning from human feedback, preference learning, Monte Carlo tree search, graph theory, recommender system, online machine learning, kernel method, mathematical optimization

Position held Principal Llama Scientist, Founding Researcher, External Lecturer, ESET Science Award Envoy, council member, ambassador

Educated at University of Pittsburgh, NOVA University Lisbon, Comenius University, Gymnasium Alejová, École normale supérieure Paris-Saclay

Award received ICML Best Paper Award, Inria Prime d'excellence scientifique, Inria Prime d'excellence scientifique, ICML Top 10 Reviewer Award, ICML Reviewer Award, Distinguished Alumni of Comenius University, Google Best Paper Award, Homer Warner Award, Compunetix Best Research Award, University of Pittsburgh Honors Convocation Recognition, Andrew Mellon Predoctoral Fellowship, Andrew Mellon Predoctoral Fellowship, Fellow of the Slovak Academy of Sciences, University of Pittsburgh Honors Convocation Recognition, Forbes Changemakers, Compunetix Best Research Award, Compunetix Best Research Award, ICML Outstanding Paper Award

Notable work Bootstrap your own latent: A new approach to self-supervised Learning, Nash Learning from Human Feedback, BYOL-Explore: Exploration by Bootstrapped Prediction, Large-Scale Representation Learning on Graphs via Bootstrapping, Bandits on Graphs and Structures, Llama 3, Spectral Bandits for Smooth Graph Functions, Finite-Time Analysis of Kernelised Contextual Bandits, Gamification of Pure Exploration for Linear Bandits, The AI Book: Prepare for the future, Adapting to game trees in zero-sum imperfect information games, Human alignment of large language models through online preference optimisation, Generalized preference optimization: A unified approach to offline alignment, Fast rates for maximum entropy exploration, Quantile credit assignment, UCB Momentum Q-learning: Correcting the bias without forgetting, From Dirichlet to Rubin: Optimistic exploration in RL without bonuses, Optimistic posterior sampling for reinforcement learning with few samples, Model-free learning for two-player zero-sum partially observable Markov games, Stochastic shortest path: minimax, parameter-free and towards horizon-free regret, The Llama 3 herd of models, A general theoretical paradigm to understand learning from human preferences, Broaden your views for self-supervised video learning, Retrieval-augmented reinforcement learning, Self-Supervised Representation Learning Using Bootstrapped Latent Representations, Reinforcement Learning by Directly Learning an Advantage Function, Reinforcement Learning Using Hindsight to Model Unpredictable Aspects of the Future, Planning in entropy-regularized Markov decision processes and games, Monte-Carlo tree search as regularized policy optimization, Metacognitive capabilities of LLMs: An exploration of model confidence, DPPy: Sampling determinantal point processes with Python, Gaussian process optimization with adaptive sketching, Spectral Thompson Sampling, Stochastic Simultaneous Optimistic Optimization, BYOL works even without batch statistics, Local and adaptive mirror descents in extensive-form games, Decoding-time realignment of language models, VA-learning as a more efficient alternative to Q-learning, Curiosity in hindsight: Intrinsic exploration in stochastic environments, Understanding self-predictive learning for reinforcement learning, Demonstration-regularized RL, Unlocking the power of representations in long-term novelty-based exploration, Accelerating Nash learning from human feedback via Mirror Prox, Bayesian policy gradient and actor-critic algorithms, Mine Your Own vieW: Self-supervised learning through across-sample prediction, Maximum Entropy Semi-Supervised Inverse Reinforcement Learning, Conditional Anomaly Detection with Soft Harmonic Functions, Online semi-supervised learning on quantized graphs, Middle-mile logistics through the lens of goal-conditioned reinforcement learning, Revealing graph bandits for maximizing local influence, Influence maximization of informed agents in social networks, Graph based anomaly detection and description: a survey, Optimal design for reward modeling in RLHF, Understanding the performance gap between online and offline alignment, Proximal Point Nash Learning from Human Feedback, Preference optimization with multi-sample comparisons, RL-finetuning LLMs from on- and off-policy data with a single algorithm, A new bound on the cumulant generating function of Dirichlet processes, Sharp deviations bounds for Dirichlet weighted sums with application to analysis of Bayesian algorithms, KL-entropy-regularized RL with a generative model is minimax optimal, On the approximation relationship between optimizing ratio of submodular (RS) and difference of submodular (DS) functions, Learning to Act Greedily: Polymatroid Semi-Bandits, The Harder Path: Last iterate convergence for uncoupled Learning in zero-sum games with bandit feedback, rlberry: A Reinforcement Learning Library for Research and Education, Model-free posterior sampling via learning rate randomization, DoMo-AC: Doubly multi-step off-policy actor-critic algorithm, Regularization and variance-weighted regression achieves minimax optimality in linear MDPs: Theory and practice, Half-Hop: A graph upsampling approach for slowing down message passing, Scaling Gaussian process optimization by evaluating a few unique candidates multiple times, Adaptive multi-goal exploration, Marginalized operators for off-policy reinforcement learning, Drop, Swap, and Generate: A self-supervised approach for generating neural activity, A provably efficient sample collection strategy for reinforcement learning, Unifying gradient estimators for meta-reinforcement learning via off-policy evaluation, Fast active learning for pure exploration in reinforcement learning, Revisiting Peng's Q(λ) for modern reinforcement learning, Taylor expansion of discount factors, Online A-optimal design and active linear regression, Kernel-based reinforcement Learning: A finite-time analysis, Game Plan: What AI can do for Football, and What Football can do for AI, A kernel-based approach to non-stationary reinforcement learning in metric spaces, Episodic reinforcement learning in finite MDPs: Minimax lower bounds revisited, Sample complexity bounds for stochastic shortest path with a generative model, Adaptive reward-free exploration, Fast sampling from β-ensembles, Density-based bonuses on learned representations for reward-free exploration in deep reinforcement learning, Geometric entropic exploration, Improved sample complexity for incremental autonomous exploration in MDPs, Sampling from a k-DPP without looking at all items, Statistical efficiency of Thompson sampling for combinatorial semi-bandits, Planning in Markov decision processes with gap-dependent sample complexity, Taylor expansion policy optimization, Budgeted online influence maximization, No-regret exploration in goal-oriented reinforcement learning, Improved sleeping bandits with stochastic action sets and adversarial rewards, Stochastic bandits with arm-dependent delays, Near-linear time Gaussian process optimization with adaptive batching and resparsification, Covariance-adapting algorithm for semi-bandits with application to sparse rewards, Fixed-confidence guarantees for Bayesian best-arm identification, Adaptive multi-fidelity optimization with fast learning rates, Derivative-free & order-robust optimisation, A single algorithm for both restless and rested rotting bandits, Reward-free exploration beyond finite-horizon, Spectral Bandits, Multiagent evaluation under incomplete information, Exact sampling of determinantal point processes with sublinear time preprocessing, On two ways to use determinantal point processes for Monte Carlo integration, Scale-free adaptive planning for deterministic dynamics & discounted rewards, Exploiting structure of uncertainty for efficient matroid semi-bandits, A simple dynamic bandit-based algorithm for hyper-parameter tuning, Rotting bandits are not harder than stochastic ones, Active multiple matrix completion with adaptive confidence sets, Finding the bandit in a graph: Sequential search-and-stop, A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption, General parallel optimization without metric, Les processus ponctuels déterminantaux en apprentissage automatique, Optimizing human learning workshop eliciting adaptive sequences for learning (WeASeL), Optimistic optimization of a Brownian, Adaptive black-box optimization got easier: HCT needs only local smoothness, Compressing the input for CNNs with the first-order scattering transform, Improved large-scale graph learning through ridge spectral sparsification, Best of both worlds: Stochastic & adversarial best-arm identification, Efficient second-order online kernel learning with adaptive embedding, Online influence maximization under independent cascade model with semi-bandit feedback, Second-order kernel online convex optimization with adaptive sketching, Zonotope hit-and-run for efficient sampling from projection DPPs, Distributed adaptive sampling for kernel matrix approximation, Trading off rewards and errors in multi-armed bandits, Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning, Pack only the essentials: Adaptive dictionary learning for kernel ridge regression, Rewards and Errors in Multi-armed Bandit for Interactive Education, Pliable rejection sampling, Analysis of Nyström method with sequential ridge leverage scores, Online learning with Erdős-Rényi side-observation graphs, Online learning with noisy side observations, Black-box optimization of noisy functions with unknown smoothness, Simple regret for infinitely many armed bandits, Cheap Bandits, Large-scale semi-supervised learning with online spectral graph sparsification, Efficient Learning by Implicit Exploration in Bandit Problems with Side Observations, Extreme Bandits, Online Combinatorial Optimization with Stochastic Decision Sets and Adversarial Losses, Bandits attack function optimization, Learning from a Single Labeled Face and a Stream of Unlabeled Data, Outlier detection for patient monitoring and alerting, Semi-supervised apprenticeship learning, Identification of microbial and proteomic biomarkers in early childhood caries, Adaptive Graph-Based Algorithms for Conditional Anomaly Detection and Semi-Supervised Learning, Semi-Supervised Learning with Max-Margin Graph Cuts, Conditional outlier detection for clinical alerting, Online Semi-Supervised Perception: Real-Time Learning without Explicit Feedback, Feature importance analysis for patient management decisions, Distance Metric Learning for Conditional Anomaly Detection, Evidence-based anomaly detection in clinical domains, Feature Selection and Dimensionality Reduction in Genomics and Proteomics, Evolutionary Feature Selection for Spiking Neural Network Pattern Classifiers

Official website misovalko.github.io

Doctoral advisor Milos Hauskrecht

Doctoral student Jean-Bastien Grill, Daniele Calandriello, Giorgio Racca, Côme Fiegel, Daniil Tiapkin, Lisa Bedin, Jean Tarbouriech, Omar Darwiche Domingues, Xuedong Shang, Julien Seznec, Tomáš Kocák, Guillaume Gautier

Work location Paris, San Francisco, Pittsburgh, Lille, Lyon, London, Bratislava, Lisbon

Languages spoken, written or signed Slovak, English, French

Short name Michal Valko

Properties

Academic degree habilitation to Supervise Research, Doctor of Philosophy, Master of Science

Academic thesis Adaptive Graph-Based Algorithms for Conditional Anomaly Detection and Semi-Supervised Learning, Bandits on Graphs and Structures

Affiliation Google DeepMind, Institut National de Recherche en Informatique et en Automatique, Doctolib, Sword Health, Entalpic AI

Birth name Michal Valko

Family name Valko

Given name Michal

Hashtag misovalko

Maintained by wikiproject WikiProject Mathematics

Member of Slovak Mathematicians and Physicists Scientific Society, Inria Evaluation Committee, Association for Computing Machinery, Institut National de Recherche en Informatique et en Automatique, European Laboratory for Learning and Intelligent Systems

Name Michal Valko

Name in native language Michal Valko

Native language Slovak

On focus list of wikimedia project WikiProject Slovakia

Residence France, United States, Slovakia

Social media followers +15000

Writing language English

External References (25)

Acm digital library author id 99661016893

Crunchbase person id michal-valko

Dblp author id 03/5455

Dimensions author id ur.011674244541.25

Github account misovalko

Google knowledge graph id /g/11f3_36tjr

Google scholar author id jrazNCQAAAAJ

Hal author id michal

Hugging face user or organization id misovalko

Idref id 22360934X

Isni 0000000351150335

Justia patents inventor id michal-valko

Linkedin personal profile id michalvalko

Mathematics genealogy project id 156876

Mr author id 1169452

National library of poland mms id 9814293093705606

Openalex id A5106038276

Orcid id 0009-0009-2673-0144

Quora topic id Michal-Valko

Researchgate profile id Michal-Valko

Scopus author id 25642222500

Semantic scholar author id 1806291

Viaf cluster id 177151836609520402601, 3284171191086658030003

X (twitter) username misovalko

Zbmath author id valko.michal

References

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APA 4ort.xyz Knowledge Graph. (2026). Q97454550. Retrieved May 7, 2026, from https://4ort.xyz/entity/q97454550

MLA “Q97454550.” 4ort.xyz Knowledge Graph, 4ort.xyz, 7 May. 2026, https://4ort.xyz/entity/q97454550.

BibTeX

@misc{4ortxyz_q97454550_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Q97454550}}, year = {2026}, url = {https://4ort.xyz/entity/q97454550}, note = {Accessed: 2026-05-07}}

LLM prompt

According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Q97454550 — https://4ort.xyz/entity/q97454550 (retrieved 2026-05-07)

Canonical URL: https://4ort.xyz/entity/q97454550 · Last refreshed: May 7, 2026

Edit History

Rolling log of changes to this entity's Wikidata record. Values shown reflect the current state of each edited property — follow the history link to see the precise diff for any edit.

4d ago · KrBot bot · 2026-07-01 view diff on Wikidata ↗

Participant in → LOD 2024, Sword AI Summit 2025, Reinforcement Learning Summer School 2019 +70

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22d ago · Kolja21 · 2026-06-13 view diff on Wikidata ↗

Viaf cluster id → 3284171191086658030003, 177151836609520402601

"/* wbeditentity-statements-multiple-properties-update:0||0 */ Changing order of values for [[Property:P214|P214]]"
22d ago · P227human · 2026-06-12 view diff on Wikidata ↗

Work location → Paris, San Francisco, Pittsburgh +5

Award received → ICML Best Paper Award, Inria Prime d'excellence scientifique, Inria Prime d'excellence scientifique +15

Idref id → 22360934X

X (twitter) username → misovalko

+ 59 other properties edited (see Wikidata diff for full list)

"/* wbsetclaim-create:2||1 */ [[Property:P213]]: 0000000351150335"

Live feed via Wikidata EventStreams. New edits appear within minutes of being made on Wikidata.

Q97454550

Q97454550

Summary

Key Facts

Body

Origins and Family

Education

Career and Affiliations

Recognition

FAQs

Where was Q97454550 born?

What did Q97454550 do for work?

What awards did Q97454550 receive?

References

Direct Wikidata claims

Inline context (facts about related entities)

Class ancestry

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