Dr Mohan Sridharan PhD

Dr Mohan Sridharan

School of Computer Science
Reader in Cognitive Robot Systems

Contact details

Telephone
+44 (0)121 414 2793
Email
m.sridharan@bham.ac.uk
View my research portal
Address
UG38, School of Computer Science
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr. Mohan Sridharan is a Reader in Cognitive Robot Systems in the School of Computer Science at University of Birmingham. He designs and algorithms and architectures to address challenges in knowledge representation and reasoning, cognitive systems, machine learning, and computational vision, as applied to adaptive robots and agents collaborating with humans. In addition, he also designs and adapts algorithms to address estimation and prediction problems in non-robotics domains such as intelligent transportation, agricultural automation, and climate informatics. For more information, please visit Mohan's (personal) home page.

Qualifications

  • PhD in Electrical and Computer Engineering, The University of Texas at Austin (USA).
  • MS in Electrical and Computer Engineering, The University of Texas at Austin (USA).

Biography

Mohan obtained his Masters and PhD degrees in Electrical and Computer Engineering from The University of Texas at Austin (USA). Prior to his current appointment, he held academic positions in the US (Texas Tech University) and NZ (University of Auckland), where he currently holds honorary positions. For more details, please see his personal web site and his CV (pdf, 225KB).

Teaching

  • Intelligent Robotics + Intelligent Robotics Extended
  • Advanced Robotics

You can also view my teaching statement (pdf, 53KB).

Research

My primary research interests include knowledge representation and reasoning, cognitive systems, machine learning, and computational vision, as applied to adaptive robots and software agents. Specifically, I design algorithms and architectures to address the following research questions:

  • How best to enable robots to represent and reason reliably and efficiently with qualitative and quantitative descriptions of incomplete knowledge and uncertainty?
  • How best to enable robots to learn interactively and cumulatively from sensor inputs and limited human feedback?
  • How best to enable designers to understand the robot’s behavior and establish that it satisfies desirable properties?

I take an integrated cognitive systems approach to address these questions, i.e., my algorithms and architectures explicitly exploit the dependencies between (and jointly explore) the representation, reasoning, learning, and control problems.

In parallel to my research in human-robot collaboration, I develop and adapt algorithms to address estimation and prediction problems in domains such as intelligent transportation, agricultural irrigation management, climate informatics, and software project management. For more information, please see my personal web site and research statement (pdf, 125KB).

Publications

Recent publications

Article

Dodampegama, H & Sridharan, M 2023, 'Knowledge-based Reasoning and Learning under Partial Observability in Ad Hoc Teamwork', Theory and Practice of Logic Programming, pp. 1-19. https://doi.org/10.1017/S1471068423000091

Sridharan, M & Mota, T 2023, 'Towards combining commonsense reasoning and knowledge acquisition to guide deep learning', Autonomous Agents and Multi-Agent Systems, vol. 37, no. 1, 4. https://doi.org/10.1007/s10458-022-09584-4

Daruna, A, Gupta, M, Sridharan, M & Chernova, S 2021, 'Continual learning of knowledge graph embeddings', IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 1128-1135. https://doi.org/10.1109/LRA.2021.3056071

Mota, T, Sridharan, M & Leonardis, A 2021, 'Integrated Commonsense Reasoning and Deep Learning for Transparent Decision Making in Robotics', SN Computer Science, vol. 2, no. 4, 242. https://doi.org/10.1007/s42979-021-00573-0

Gomez, R, Sridharan, M & Riley, H 2021, 'What do you really want to do? Towards a Theory of Intentions for Human-Robot Collaboration', Annals of Mathematics and Artificial Intelligence, vol. 89, no. 1-2, pp. 179-208. https://doi.org/10.1007/s10472-019-09672-4, https://doi.org/10.1007/s10472-019-09672-4

Weerasekera, R, Sridharan, M & Ranjitkar, P 2020, 'Implications of Spatiotemporal Data Aggregation on Short-Term Traffic Prediction Using Machine Learning Algorithms', Journal of Advanced Transportation, vol. 2020, 7057519, pp. 1-21. https://doi.org/10.1155/2020/7057519, https://doi.org/10.1155/2020/7057519

Riley, H & Sridharan, M 2019, 'Integrating Non-monotonic Logical Reasoning and Inductive Learning With Deep Learning for Explainable Visual Question Answering', Frontiers in Robotics and Artificial Intelligence, vol. 6, 125. https://doi.org/10.3389/frobt.2019.00125, https://doi.org/10.3389/frobt.2019.00125

Sridharan, M, Gelfond, M, Zhang, S & Wyatt, J 2019, 'REBA: a refinement-based architecture for knowledge representation and reasoning in robotics', Journal of Artificial Intelligence Research, vol. 65, pp. 87-180. https://doi.org/10.1613/jair.1.11524, https://doi.org/10.1613/jair.1.11524

Sridharan, M & Meadows, B 2018, 'Knowledge representation and interactive learning of domain knowledge for human-robot interaction', Advances in Cognitive Systems, vol. 7, pp. 69-88. <http://www.cogsys.org/papers/ACSvol7/papers/paper-7-6.pdf>

Conference contribution

Mota, T & Sridharan, M 2019, Commonsense reasoning and knowledge acquisition to guide deep learning on robots. in A Bicchi, H Kress-Gazit & S Hutchinson (eds), Robotics: Science and Systems XV., 77, Robotics: Science and Systems Proceedings, vol. 15, Robotics: Science and Systems, Robotics, Freiburg, Baden-Württemberg, Germany, 22/06/19. https://doi.org/10.15607/RSS.2019.XV.077, https://doi.org/10.15607/RSS.2019.XV.077

Mota, T & Sridharan, M 2018, Incrementally Grounding Expressions for Spatial Relations between Objects. in J Lang (ed.), Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18). International Joint Conferences on Artificial Intelligence, International Joint Conference on Artificial Intelligence 2018, Stockholm, Sweden, 13/07/18. <https://www.ijcai.org/proceedings/2018/0266.pdf>

Mota, T & Sridharan, M 2018, Incrementally Grounding Expressions for Spatial Relations between Objects. in Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18).

Sridharan, M & Meadows, B 2018, Knowledge Representation and Interactive Learning of Domain Knowledge for Human-Robot Interaction. in T Vaquero, M Roberts, S Bernardini, T Niemueller & S Fratini (eds), Proceedings of the 2nd Workshop on Integrated Planning, Acting, and Execution (IntEx 2018). International Conference on Automated Planning and Scheduling, pp. 60-68, Workshop on Integrated Planning, Acting and Execution at ICAPS 2018, Delft, Netherlands, 25/06/18. <http://icaps18.icaps-conference.org/fileadmin/alg/conferences/icaps18/workshops/workshop09/docs/proceedings.pdf>

Sridharan, M & Meadows, B 2018, Knowledge Representation and Interactive Learning of Domain Knowledge for Human-Robot Interaction. in Proceedings of the 2nd Workshop on Integrated Planning, Acting, and Execution (IntEx 2018).

Paper

Rudorfer, M, Suchi, M, Sridharan, M, Vincze, M & Leonardis, A 2022, 'BURG-toolkit: robot grasping experiments in simulation and the real world', Paper presented at 39th IEEE International Conference on Robotics and Automation, ICRA 2022, Philadelphia, United States, 23/05/22 - 27/05/22. <https://arxiv.org/abs/2205.14099>

View all publications in research portal