Devdatt Dubhashi

Full Professor at Data Science and AI

My main interests are in design and analysis of randomized algorithms, machine learning for Big Data and computational biology.

Source: chalmers.se
Image of Devdatt Dubhashi

Showing 63 publications

2024

Pure Exploration in Bandits with Linear Constraints

Emil Carlsson, Debabrota Basu, Fredrik Johansson et al
Proceedings of Machine Learning Research. Vol. 238, p. 334-342
Paper in proceeding
2023

Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework

Arman Rahbar, Ashkan Panahi, Morteza Haghir Chehreghani et al
Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, UAI 2022. Vol. 202, p. 28549-28577
Paper in proceeding
2023

Do Kernel and Neural Embeddings Help in Training and Generalization?

Arman Rahbar, Emilio Jorge, Devdatt Dubhashi et al
Neural Processing Letters. Vol. 55 (2), p. 1681-1695
Journal article
2023

Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves

David Bosch, Ashkan Panahi, Ayca Ozcelikkale et al
Proceedings of Machine Learning Research. Vol. 206, p. 11371-11414
Paper in proceeding
2023

Using Satellite Images and Deep Learning to Measure Health and Living Standards in India

Adel Daoud, Felipe Jordán, Makkunda Sharma et al
Social Indicators Research. Vol. 167 (1-3), p. 475-505
Journal article
2023

Hybrid Quantum-Classical Heuristic to Solve Large-Scale Integer Linear Programs

Marika Svensson, Martin Andersson, Mattias Grönkvist et al
Physical Review Applied. Vol. 20 (3)
Journal article
2023

A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns

Çaglar Tozluoglu, Swapnil Vilas Dhamal, Sonia Yeh et al
Data in Brief. Vol. 48
Journal article
2022

Analysis of Knowledge Transfer in Kernel Regime

Ashkan Panahi, Arman Rahbar, Chiranjib Bhattacharyya et al
International Conference on Information and Knowledge Management, Proceedings, p. 1615-1624
Paper in proceeding
2022

Can Universities Combat the 'Wrong Kind of AI'?

Devdatt Dubhashi
Communications of the ACM. Vol. 65 (12), p. 24-26
Other text in scientific journal
2022

Synthetic Sweden Mobility (SySMo) Model Documentation

Çaglar Tozluoglu, Swapnil Vilas Dhamal, Yuan Liao et al
Preprint
2022

Controlling gene expression with deep generative design of regulatory DNA

Jan Zrimec, Xiaozhi Fu, Muhammad Azam Sheikh et al
Nature Communications. Vol. 13 (1), p. 5099-
Journal article
2022

Pragmatic Reasoning in Structured Signaling Games

Emil Carlsson, Devdatt Dubhashi
Proceedings of the 44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022, p. 2831-2837
Paper in proceeding
2021

Thompson Sampling for Bandits with Clustered Arms

Emil Carlsson, Devdatt Dubhashi, Fredrik Johansson
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Paper in proceeding
2021

Melting together prediction and inference

Adel Daoud, Devdatt Dubhashi
Observational Studies. Vol. 7 (1), p. 1-7
Journal article
2021

AI futures

Devdatt Dubhashi
Communications of the ACM. Vol. 64 (10), p. 30-31
Other text in scientific journal
2021

Learning Approximate and Exact Numeral Systems via Reinforcement Learning

Emil Carlsson, Devdatt Dubhashi, Fredrik Johansson
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021. Vol. 43
Paper in proceeding
2020

Accelerated proximal incremental algorithm schemes for non-strongly convex functions

Ashkan Panahi, Morteza Haghir Chehreghani, Devdatt Dubhashi
Theoretical Computer Science. Vol. 812, p. 203-213
Journal article
2020

Mathematical Models for COVID-19 Pandemic: A Comparative Analysis

Aniruddha Adiga, Devdatt Dubhashi, Bryan Lewis et al
Journal of the Indian Institute of Science. Vol. 100 (4), p. 793-807
Review article
2020

A reinforcement-learning approach to efficient communication

Mikael Kågebäck, Emil Carlsson, Devdatt Dubhashi et al
PLoS ONE. Vol. 15 (7)
Journal article
2019

A Non-Convex Optimization Approach to Correlation Clustering

Erik Thiel, Morteza Haghir Chehreghani, Devdatt Dubhashi
33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, p. 5159-5166
Paper in proceeding
2019

Bayesian optimization in ab initio nuclear physics

Andreas Ekström, Christian Forssen, Christos Dimitrakakis et al
Journal of Physics G: Nuclear and Particle Physics. Vol. 46 (9)
Journal article
2018

DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning

Mikael Kågebäck, Devdatt Dubhashi, Asad Sayeed
Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018, p. 1895-1900
Paper in proceeding
2017

Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery

Ashkan Panahi, Devdatt Dubhashi, Fredrik Johansson et al
Proceedings of Machine Learning Research. Vol. 6, p. 4247-4260
Paper in proceeding
2017

Thompson Sampling for Stochastic Bandits with Graph Feedback

Aristide Tossou, Christos Dimitrakakis, Devdatt Dubhashi
31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States, 4-10 February 2017, p. 2660-2666
Paper in proceeding
2017

AI Dangers: Imagined and Real

Devdatt Dubhashi, Shalom Lappin
Communications of the ACM. Vol. 60 (2), p. 43-45
Other text in scientific journal
2015

Visions and open challenges for a knowledge-based culturomics

Nina Tahmasebi, Lars Borin, Gabriele Capannini et al
International Journal on Digital Libraries. Vol. 15 (2-4), p. 169-187
Journal article
2015

Extractive summarization by aggregating multiple similarities

Olof Mogren, Mikael Kågebäck, Devdatt Dubhashi
International Conference Recent Advances in Natural Language Processing, RANLP. Vol. 2015-January, p. 451-457
Paper in proceeding
2015

Classifying large graphs with differential privacy

Fredrik Johansson, Otto Frost, Carl Thufvesson Retzner et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9321, p. 3-7
Paper in proceeding
2015

Neural context embeddings for automatic discovery of word senses

Mikael Kågebäck, Fredrik Johansson, Richard Johansson et al
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing. Denver, United States, p. 25-32
Paper in proceeding
2015

Weighted theta functions and embeddings with applications to Max-Cut, clustering and summarization

Fredrik Johansson, A. Chattoraj, C. Bhattacharyya et al
Advances in Neural Information Processing Systems. Vol. 2015-January, p. 1018-1026
Paper in proceeding
2015

Learning with similarity functions on graphs using matchings of geometric embeddings

Fredrik Johansson, Devdatt Dubhashi
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Vol. 2015-August, p. 467-476
Paper in proceeding
2014

Global graph kernels using geometric embeddings

Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi et al
Proceedings of the 31st International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014. Vol. 3, p. 694-702
Paper in proceeding
2014

Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed

C. Mazurek, J. Pukacki, M. Kosiedowski et al
2014 IEEE 3rd International Conference on Cloud Networking, CloudNet 2014, p. 294-299
Paper in proceeding
2014

Extractive Summarization using Continuous Vector Space Models

Mikael Kågebäck, Olof Mogren, Nina Tahmasebi et al
Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC) EACL, April 26-30, 2014 Gothenburg, Sweden, p. 31-39
Paper in proceeding
2013

Mining semantics for culturomics: towards a knowledge-based approach

Lars Borin, Devdatt Dubhashi, Markus Forsberg et al
2013 ACM International Workshop on Mining Unstructured Big Data Using Natural Language Processing, UnstructureNLP 2013, Held at 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013; San Francisco, CA; United States; 28 October 2013 through 28 October 2013, p. 3-10
Paper in proceeding
2013

Lovasz θ, SVMs and applications

Vinay Jethava, Jacob Sznajdman, C. Bhattacharyya et al
2013 IEEE Information Theory Workshop - ITW 2013, Seville, Spain, 9-13 September 2013, p. 1-5
Paper in proceeding
2013

Computational approaches for reconstruction of time-varying biological networks from omics data

Vinay Jethava, Chiranjib Bhattacharyya, Devdatt Dubhashi
Systems Biology: Integrative Biology and Simulation Tools. Vol. 1, p. 209-239
Book chapter
2013

DLOREAN: Dynamic Location-aware Reconstruction of multiway Networks

Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi
2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013; Dallas, TX; United States; 7 December 2013 through 10 December 2013, p. 1012-1019
Paper in proceeding
2013

Lovasz theta function, SVMs and Finding Dense Subgraphs

Vinay Jethava, Anders Martinsson, C. Bhattacharyya et al
Journal of Machine Learning Research. Vol. 14, p. 3495-3536
Journal article
2013

Entity disambiguation in anonymized graphs using graph kernels

Linus Hermansson, Tommi Kerola, Fredrik Johansson et al
22nd ACM International Conference on Information and Knowledge Management, CIKM 2013; San Francisco, CA; United States; 27 October 2013 through 1 November 2013, p. 1037-1046
Paper in proceeding
2012

The Lovász v function, SVMs and finding large dense subgraphs

Vinay Jethava, Anders Martinsson, C. Bhattacharyya et al
Advances in Neural Information Processing Systems. Vol. 2, p. 1160-1168
Paper in proceeding
2011

Scalable multi-dimensional user intent identification using tree structured distributions

Vinay Jethava, L. Calderón-Benavides, R.A. Baeza-Yates et al
SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, p. 395-404
Paper in proceeding
2011

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Vinay Jethava, C. Bhattacharyya, Devdatt Dubhashi et al
BMC Bioinformatics. Vol. 12
Journal article
2011

The IncP-1 plasmid backbone adapts to different host bacterial species and evolves through homologous recombination.

Peter Norberg, Maria Bergström, Vinay Jethava et al
Nature Communications. Vol. 2 (1), p. 268-
Journal article
2009

Adaptive Dynamics of Realistic Small-World Networks

Olof Mogren, Oskar Sandberg, Vilhelm Verendel et al
European Conference on Complex Systems 2009, p. 12-
Paper in proceeding
2009

Bridging the gap between systems biology and medicine

Gilles Clermont, Charles Auffray, Yves Moreau et al
Genome Medicine. Vol. 1 (9), p. 88-
Journal article
2008

A note on conditioning and stochastic domination for order statistics

Devdatt Dubhashi, Olle Häggström
Journal of Applied Probability. Vol. 45, p. 575-579
Journal article
2007

Distributed approximation algorithms via LP-duality and randomization

Devdatt Dubhashi, Fabrizio Grandoni, Alessandro Panconesi
Handbook of Approximation Algorithms and Metaheuristics
Book chapter
2007

Blue pleiades, a new solution for device discovery and scatternet formation in multi-hop bluetooth networks

Devdatt Dubhashi, Olle Häggström, Gabriele Mambrini et al
Wireless Networks. Vol. 13 (1), p. 107--125-
Journal article
2007

Probabilistic analysis for a multiple depot vehicle routing problem

A. Baltz, Devdatt Dubhashi, A. Srivastav et al
Random Structures and Algorithms. Vol. 30 (1-2), p. 206-225
Journal article
2007

positiv influence and negative dependence

Devdatt Dubhashi, Johan Jonasson, Desh Ranjan
Combinatorics, Probability and Computing. Vol. 16, p. 29-41
Journal article
2007

Localized techniques for broadcasting in wireless sensor networks.

Devdatt Dubhashi, Olle Häggström, Lorenzo Orrechia et al
Algorithmica. Vol. 49 (4), p. 412--446-
Journal article
2006

Distributed Approximation Algorithms via Randomization

Devdatt Dubhashi, Fabrizio Grandoni, Alessandro Panconesi
Handbook of Approximation Algorithms and Metaheuristics
Book chapter
2006

A New Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity

Daniel Dalevi, Devdatt Dubhashi, Malte Hermansson
Statistical Applications in Genetics and Molecular Biology. Vol. 5 (1), p. i-24
Journal article
2006

Bayesian classifiers for detecting HGT using fixed and variable order Markov models of genomic signatures

Daniel Dalevi, Devdatt Dubhashi, Malte Hermansson
Bioinformatics. Vol. 22 (5), p. 517-522
Journal article
2006

Randomization in Constraint Programming for Airline Planning

Devdatt Dubhashi, Lars Otten, Mattias Gronkvist
Principles and Practice of Constraint Programming. Vol. LNCS (4204)
Paper in proceeding
2005

The Peres-Shields Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity.

Devdatt Dubhashi, Daniel Dalevi
Workshop on Algorithms in Bioinformatics. Vol. 2005
Paper in proceeding
2005

Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons

Devdatt Dubhashi, Alessandro Panconesi, Jaikumar Radhakrishnan et al
J. Comput. System Sci.. Vol. 71 (4), p. 467-479
Journal article
2005

Probabilistic Analysis for a Multiple Depot Vehicle Routing Problem.

Andreas Baltz, Devdatt Dubhashi, Libertad Tansini et al
Foundations of Software Technology and Theoretical Computer Science.. Vol. 2005
Paper in proceeding
2005

Irrigating ad hoc networks in constant time

Devdatt Dubhashi, Christoffer Johansson, Olle Häggström et al
Symposium on Parallel Algorithms and Architectures. Vol. 2005
Paper in proceeding
2003

Connectivity Properties of Bluetooth Wireless Networks

Devdatt Dubhashi, Olle Häggström, Alessandro Panconesi
Preprint
2003

Analysis and Experimental Evaluation of a Simple Algorithm for Collaborative Filtering in Planted Partition Models

Devdatt Dubhashi
Foundations of Software Technology and theoretical Computer Science. Vol. 2003
Paper in proceeding
2003

Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons

Devdatt Dubhashi
Symposium on Discrete Algorithms. Vol. 2003
Paper in proceeding

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Showing 16 research projects

2023–2026

Public policies and indicators for well-being and sustainable development

Devdatt Dubhashi Data Science and AI 1
European Commission (EC)

2022–2027

Quantumstack: Programmering av kvantdatorn

Devdatt Dubhashi Data Science and AI 1
Swedish Foundation for Strategic Research (SSF)

2020–2020

Yata – Intelligent systems to improve and support education

Simon Pettersson Fors Subatomic, High Energy and Plasma Physics
Christian Forssén Subatomic, High Energy and Plasma Physics
Devdatt Dubhashi Data Science
Fredrik Johansson Data Science
Dag Wedelin Data Science
Chalmers AI Research Centre (CHAIR)
Chalmers

2019–

Deep Reinforcement Learning: Principles and Applications in Cognitive Science and Networks (

Devdatt Dubhashi Data Science
Fredrik Johansson Data Science
Chalmers AI Research Centre (CHAIR)

1 publication exists
2019–2019

Sweden-India AI Summit

Devdatt Dubhashi Data Science
VINNOVA

2018–2022

The new future of mobility: Using a Synthetic Sweden to study transition pathways to autonomous, shared, and electromobility

Sonia Yeh Physical Resource Theory
Devdatt Dubhashi Data Science
Frances Sprei Physical Resource Theory
Formas

3 publications exist
2018–2018

A synthetic Sweden decision supporting tool for future urban mobility – Autonomous and electromobility infrastructure planning

Sonia Yeh Physical Resource Theory
Frances Sprei Physical Resource Theory
Devdatt Dubhashi Data Science
Chalmers

2017–2018

Big data for smart society (GATE)

Devdatt Dubhashi Computing Science (Chalmers)
European Commission (EC)

2015–2018

Centre of excellence for Global Systems Science (CoeGSS)

Patrik Jansson Software Technology (Chalmers)
Devdatt Dubhashi Computing Science (Chalmers)
Michal Palka Software Technology (Chalmers)
Oskar Allerbo Computing Science (Chalmers)
Cezar Ionescu Software Technology (Chalmers)
European Commission (EC)

5 publications exist
2015–2018

ACE: Approximate Algorithms and Computing Systems

Per Stenström Computer Engineering (Chalmers)
Johan Karlsson Computer Science and Engineering (Chalmers)
Sally A McKee Computer Engineering (Chalmers)
Ulf Assarsson Computer Engineering (Chalmers)
Ioannis Sourdis Computer Engineering (Chalmers)
Devdatt Dubhashi Computing Science (Chalmers)
Christos Dimitrakakis Computing Science (Chalmers)
Alexandra Angerd Computer Engineering (Chalmers)
Jacob Lidman Computer Engineering (Chalmers)
Behrooz Sangchoolie Computer Engineering (Chalmers)
Fatemeh Ayatolahi Computer Engineering (Chalmers)
Albin Eldstål Damlin Computer Engineering (Chalmers)
Miquel Pericas Computer Engineering (Chalmers)
Erik Sintorn Computer Engineering (Chalmers)
Swedish Research Council (VR)

9 publications exist
2015–2017

Big data Analytics and Infrastructure for Business Intelligence, Biomedicine and Health

Devdatt Dubhashi Computing Science (Chalmers)
VINNOVA

2013–2014

Framtidens stad med syntetiska populationer

Devdatt Dubhashi Computing Science (Chalmers)
VINNOVA

2012–2016

Towards a knowledge-based culturomics

Devdatt Dubhashi Computing Science (Chalmers)
Swedish Research Council (VR)

2 publications exist
2012–2016

Data-Driven Secure Business Intelligence (DataBIN)

David Sands Software Technology (Chalmers)
Devdatt Dubhashi Computing Science (Chalmers)
Peter Damaschke Computing Science (Chalmers)
Gerardo Schneider Software Technology (Chalmers)
Olof Mogren Computing Science (Chalmers)
Raul Pardo Jimenez Software Technology (Chalmers)
Hamid Ebadi Tavallaei Software Technology (Chalmers)
Fredrik Johansson Computing Science (Chalmers)
Andrei Sabelfeld Software Technology (Chalmers)
Swedish Foundation for Strategic Research (SSF)

2012–2014

Algorithms for Inference of Temporal Dynamics in Networks and Concentration of Measure Techniques for their Analysis

Devdatt Dubhashi Computing Science (Chalmers)
Swedish Research Council (VR)

There might be more projects where Devdatt Dubhashi participates, but you have to be logged in as a Chalmers employee to see them.