Gnana Bharathy is a lecturer (Behavioural & Systems Modeling) in the School of Information, Systems & Modeling at UTS, where he is also a member of Centre on Persuasive Systems for Wise Adaptive Living (PERSWADE).
Outside academia, Gnana has over 15+ years of experience applying data science (and other advanced analytics approaches), in a powerful combination with design sciences such as design thinking, architecture (business, information, data, product) and diagnostics to add radical transformational value to clients.
Gnana has been working in both pure industry consulting as well as university-based, external consulting in the capacities of modeller/ analyst and project manager in several countries (mostly in United States, Australia, New Zealand, and to a lesser extent in Canada, Jamaica, India and Malaysia) for over 15 years.
Despite being in non-academic roles, Gnana has continued to research on a part-time basis, and has published regularly. Some of his research work have been recognized with awards.
Gnana has also developed several modelling (human behaviour modelling) and risk management products, including for the governments, health sectors in Australia and USA and has served a range of private sector clients.
Gnana was trained at the University of Pennsylvania (PhD, MS), University of Canterbury (ME) and National Institute of Technology (Bachelors with distinction).
- Institution of Engineers Australia (MIEAust)
- Project Management Professional (PMP) from Project Management Institute (PMI)
- Certified Scrum Master (CSM)
Can supervise: YES
Application of design and data science techniques to study complex, intractable problems in the society. e.g. Sustainability, Energy, Water, Healthcare, Safety, Security and Engineering/ Tech Risks.
- Social Systems Modeling with Human Behavior
- Investigating Socio-Technical Systems with Mixed Methods
- Advanced Analytics, Modeling and Simulation, Machine Learning, and Deep Learning
- Design Thinking, Systems Thinking and Scenario Planning
- Socio-Ecology of Data Science and AI Implementation: Ethics, Implementation Issues, Architecture, Application of Collaborative Processes in Advanced Analytics: Design Thinking, Participatory Modelling and Project Management (Waterfall, Evolutionary Scrum)
Teaching and Coordinating:
Collaborative Business Processes (2020 Autumn)
Design of new Micro-Credit Courses:
- Complex Systems Modelling
- Participatory Modelling
Jia, M, Srinivasan, RS, Ries, R, Weyer, N & Bharathy, G 2019, 'A systematic development and validation approach to a novel agent-based modeling of occupant behaviors in commercial buildings', Energy and Buildings, vol. 199, pp. 352-367.View/Download from: Publisher's site
Silverman, BG, Bharathy, G & Weyer, N 2019, 'What is a good pattern of life model? Guidance for simulations', SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, vol. 95, no. 8, pp. 693-706.View/Download from: Publisher's site
Silverman, BG, Hanrahan, N, Bharathy, G, Gordon, K & Johnson, D 2015, 'A systems approach to healthcare: Agent-based modeling, community mental health, and population well-being', ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 63, no. 2, pp. 61-71.View/Download from: Publisher's site
Bharathy, GK & Silverman, B 2013, 'Holistically evaluating agent-based social systems models: a case study', SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, vol. 89, no. 1, pp. 102-135.View/Download from: Publisher's site
Ilanko, S & Bharathy, GK 2012, 'Positive and negative penalty parameters in optimisation subjected to continuous constraints', COMPUTERS & STRUCTURES, vol. 108, pp. 83-92.View/Download from: Publisher's site
Silverman, BG, Bharathy, G, Nye, B & Smith, T 2008, 'Modeling factions for 'effects based operations', part II: behavioral game theory', COMPUTATIONAL AND MATHEMATICAL ORGANIZATION THEORY, vol. 14, no. 2, pp. 120-155.View/Download from: Publisher's site
Silverman, BG, Normoyle, A, Kannan, P, Pater, R, Chandrasekaran, D & Bharathy, G 2008, 'An embeddable testbed for insurgent and terrorist agent theories: Insurgisim', Intelligent Decision Technologies, vol. 2, no. 4, pp. 193-203.View/Download from: Publisher's site
Many simulators today contain traditional opponents and lack an asymmetric insurgent style adversary. InsurgiSim prototypes an embeddable testbed containing a threat network of agents that one can easily configure and deploy for training and analysis purposes. The insurgent network was constructed inside a socio-cognitive agent framework (FactionSim-PMFserv) that includes: (a) a synthesis of best-of-breed models of personality, culture, values, emotions, stress, social relations, mobilization, as well as (b) an IDE for authoring and managing reusable archetypes and their task-sets (Section 2). Agents and markups in this library are not scripted, and act to follow their values and fulfill their needs. So it's desirable to profile the agents (eg, faction leaders, cell logisticians, followers, bomb maker, financier, recruiter, etc.) as faithfully to the real world as possible. Doing this will improve the utility of InsurgiSim for studying what may be driving the insurgent agents in a given area of operation as Section 3 explains. InsurgiSim's bridge is an HLA federate and can be embedded to drive all or some of the insurgent agents in a 3rd party simulator. Three such examples are summarized in Section 4. The paper closes with next steps to improve InsurgiSim's capabilities and utility. © 2007 - IOS Press and the authors.
Silverman, BG, Bharathy, G, Johns, M, Eidelson, RJ, Smith, TE & Nye, B 2007, 'Sociocultural games for training and analysis', IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, vol. 37, no. 6, pp. 1113-1130.View/Download from: Publisher's site
Silverman, BG, Bharathy, G, Nye, B & Eidelson, RJ 2007, 'Modeling factions for "effects based operations": Part I - Leaders and followers', Computational and Mathematical Organization Theory, vol. 13, no. 4, pp. 379-406.View/Download from: Publisher's site
This paper presents a synthetic approach for generating role playing simulation games intended to support analysts (and trainees) interested in testing alternative competing courses of action (operations) and discovering what effects they are likely to precipitate in potential ethno-political conflict situations. Simulated leaders and followers capable of playing these games are implemented in a cognitive modeling framework, called PMFserv, which covers value systems, personality and cultural factors, emotions, relationships, perception, stress/coping style and decision making. Of direct interest, as Sect. 1.1 explains, is mathematical representation and synthesis of best-of-breed behavioral science models within this framework to reduce dimensionality and to improve the realism and internal validity of the agent implementations. Sections 2 and 3 present this for leader profiling instruments and group membership decision-making, respectively. Section 4 serves as an existence proof that the framework has generated several training and analysis tools, and Sect. 5 concludes with lessons learned. Part II turns to the question of assessment of the synthesis and its usage in course of action studies. © Springer Science+Business Media, LLC 2007.
Silverman, BG, Bharathy, G, O'Brien, K & Cornwell, J 2006, 'Human behavior models for agents in simulators and games: Part II: Gamebot engineering with PMFserv', Presence: Teleoperators and Virtual Environments, vol. 15, no. 2, pp. 163-185.View/Download from: Publisher's site
Many producers and consumers of legacy training simulator and game environments are beginning to envision a new era where psycho-socio-physiologic models could be interoperated to enhance their environments' simulation of human agents. This paper explores whether we could embed our behavior modeling framework (described in the companion paper, Part I) behind a legacy first person shooter 3D game environment to recreate portions of the Black Hawk Down scenario. Section I amplifies the interoperability needs and challenges confronting the field, presents the questions that are examined, and describes the test scenario. Sections 2 and 3 review the software and knowledge engineering methodology, respectively, needed to create the system and populate it with bots. Results (Section 4) and discussion (Section 5) reveal that we were able to generate plausible and adaptive recreations of Somalian crowds, militia, women acting as shields, suicide bombers, and more. Also, there are specific lessons learned about ways to advance the field so that such interoperabilities will become more affordable and widespread. © 2006 by the Massachusetts Institute of Technology.
Silverman, BG, Sun, DQ, Weyer, N & Bharathy, GK 2016, 'Rapid generation of political conflict simulations for scenarios around the world' in Modeling Sociocultural Influences on Decision Making: Understanding Conflict, Enabling Stability, pp. 335-360.View/Download from: Publisher's site
© 2011 by Taylor & Francis Group, LLC. This chapter describes a prototype of a rapid scenario generator that has been demonstrated in a field setting in 2014. The generator consists of a set of screens that assists a human in quickly specifying political conflict scenarios around the world. The goal is to produce models that can simulate the scenarios and thereby help to assess the impact of the alternative COA the user might take to influence the scenario outcomes. The generator is able to speed up scenario construction since it uses analogical or case-based reasoning (CBR), and it is built upon a repository of hundreds of past StateSim models of political groups, actors, institutions, and other conhict scenario elements. This chapter introduces the generator purpose in the section "Introduction and Purpose." Background on CBR and StateSim are in the section "Architecture and Cycle of the Case-Based Generator." This walks through a fictional state use case to create a scenario and a set of StateSim models in the section "The Generator Elicitation Screens." We then explain the repository of past models and some tools to explore what is in it in the section "CBR and the Repository of Past Cases." Finally, it discusses the results to date and next steps in the section "Conclusions and Next Steps." At the end of the chapter, we discuss the detailed application of our platform to the attached megacity use case.
Risk is inexplicably linked to complex inter-related structural and behavioral factors. Of these, human factors tend to be overarching and predominant. Any model that would assist with exploring the inter-relationships among structural and human factors would be immensely valuable to risk management. A social system model constructed with a valid set of software agent framework and complete with factions, institutions and other organizational descriptors, all based on best-of-breed social science theories, can act as the desired testbed to evaluate effects that may arise from alternative courses of action. Through our past case studies, we describe in this article, how social systems modeling and associated intelligent system tools could be applied to assess and manage political risk (and by extension other social systems based risks). We also enumerate the challenges of such a testbed and describes best-of-breed theories drawn from across the social sciences and synthesized and implemented in an agent-based framework. These predictions are examined in a real world cases (Bangladesh) where the agent models are subjected to a validity check and the political risks are estimated. © Springer-Verlag Berlin Heidelberg 2012.
Bharathy, GK, Yilmaz, L & Tolk, A 2012, 'Agent Directed Simulation for Combat Modeling and Distributed Simulation' in Engineering Principles of Combat Modeling and Distributed Simulation, pp. 669-713.View/Download from: Publisher's site
Silverman, BG, Bharathy, GK, Nye, B, Kim, GJ, Roddy, M & Poe, M 2010, 'M&S Methodologies: A Systems Approach to the Social Sciences' in Modeling and Simulation Fundamentals: Theoretical Underpinnings and Practical Domains, pp. 227-270.View/Download from: Publisher's site
Silverman, BG, Bharathy, GK, Nye, B, Kim, GJ, Roddy, M & Poe, M 2010, 'M&S Methodologies: A Systems Approach to the Social Sciences' in Modeling and Simulation Fundamentals, John Wiley & Sons, Inc., pp. 227-270.View/Download from: Publisher's site
This chapter begins by describing a universally recurring socio-cultural game of inter-group competition for control of resources. It next describes efforts to author software agents able to play the game as real humans would - which suggests the ability to study alternative ways to influence them, observe PMESII effects, and potentially understand how best to alter the outcomes of potential conflict situations. These agents are unscripted, but use their decision making to react to events as they unfold and to plan out responses. For each agent, a software called PMFserv operates its perception and runs its physiology and personality/value system to determine fatigue and hunger, injuries and related stressors, grievances, tension buildup, impact of rumors and speech acts, emotions, and various collective and individual action decisions. The chapter wraps up with a correspondence test from a SE Asian ethnic conflict, the results of which indicate significant correlation between real and agentbased outcomes. © 2009 Springer-Verlag Berlin Heidelberg.
Jia, M, Srinivasan, RS, Ries, R & Bharathy, G 2019, 'Exploring the validity of occupant behavior model for improving office building energy simulation', Proceedings - Winter Simulation Conference, pp. 3953-3964.View/Download from: Publisher's site
© 2018 IEEE Building energy use is significantly influenced by building occupants or users. The integration of a robust occupant behavior model that captures energy-related behaviors and a building energy model will have the potential to improve energy simulation performance, as current virtual model of building lacks dynamic and practical occupant information input. Agent-based Modeling (ABM) has been successfully applied to model interactions between occupants and building components, but most of the models were developed on a simulation basis without actual data involvement. To address on this issue, this paper proposes an approach to modeling occupant behaviors in office buildings via the design of a novel ABM and relevant data collection for model testing and validation. A case study is conducted to investigate the performance of the model. The results show the applicability of the ABM and provide a feasible direction for tuning ABM for the purpose of building energy simulation improvement.
Jia, M, Srinivasan, RS, Ries, R & Bharathy, G 2018, 'A framework of occupant behavior modeling and data sensing for improving building energy simulation', Simulation Series, pp. 110-117.
© 2018 Society for Modeling & Simulation International (SCS). Studies have shown the influence of building occupants on building energy use. However, current building energy simulation tools lack dynamic and realistic occupant information inputs in modeling. The development of a robust occupant behavior model that can generate occupant schedules for use in building energy simulation algorithms will have the potential to improve accuracy of energy estimation. One such approach is the use of Agent-based Modeling (ABM) which has been successfully applied to model interactions between occupants and building systems. Yet, most of the models were developed with simulated data rather than actual data inputs from indoor environment. This paper proposes a framework for tracking indoor environmental data and occupant-building system interactions to model occupant behaviors in educational buildings using ABM. The data collection approach combines both smart sensor node deployments and paperbased surveys for future validation of the framework. A pilot study is conducted to explore the effectiveness of the framework. The results show the feasibility of integrating ABM for occupant behavior modeling to obtain improved energy use estimates.
Magpili, L, Pinto, CA, Bharathy, G & Babiker, M 2017, 'Systematic Capacity-Based Risk Assessment: Application to Water Service Project in Kassala, Sudan', INCOSE International Symposium, Wiley, pp. 1782-1794.View/Download from: Publisher's site
Lowe, DB, Bharathy, GK, Stumpers, BD & Yeung, H 2012, 'Laboratory lesson plans: Opportunities created by remote laboratories', 2012 9th International Conference on Remote Engineering and Virtual Instrumentation (REV), International Conference on Remote Engineering and Virtual Instrumentation, IEEE, Bilbao, USA, pp. 1-6.View/Download from: Publisher's site
Over the last decade remote laboratories have emerged as valuable educational resources, providing the potential for improved educational outcomes, student flexibility, richer laboratory experiences, and cross-institutional resource sharing. While there has been increasing attention given to the pedagogy that underpins the use of remote labs, the focus on the design of the lessons that take advantage of remote laboratories has been much more limited. In this paper it is argued that remote laboratories provide an exciting opportunity to provide system-supported adaptation. In particular, because the interactions with the equipment are now mediated through software, it becomes possible to monitor these interactions, as well as the state of the apparatus, and use this to provide guidance to the student. The paper discusses the opportunities that are created, the requirements this places on the design of remote laboratory systems, and preliminary work on implementing such a system that has highlighted potential challenges.
Nye, BD, Bharathy, GK, Silverman, BG & Eksin, C 2012, 'Simulation-based training of ill-defined social domains: The Complex Environment Assessment and Tutoring System (CEATS)', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 642-644.View/Download from: Publisher's site
Bharathy, GK & Silverman, B 2010, 'VALIDATING AGENT BASED SOCIAL SYSTEMS MODELS', PROCEEDINGS OF THE 2010 WINTER SIMULATION CONFERENCE, 2010 Winter Simulation Conference, IEEE, Baltimore, MD, pp. 441-453.View/Download from: Publisher's site
Ilanko, S & Bharathy, GK 2010, 'Introducing Negative Penalty Functions in Least Square Optimisation', PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY, 10th International Conference on Computational Structures Technology, CIVIL COMP PRESS, Valencia, SPAIN.
McDonald, D, Lazarus, R, Leung, A, Hussain, T, Bharathy, G, Eidelson, RJ, Pelechano, N, Sandhaus, E & Silverman, BG 2006, 'Interoperable human behavior models for simulations', Simulation Interoperability Standards Organization - 15th Conference on Behavior Representation in Modeling and Simulation 2006, pp. 273-280.
Modern simulations and games have limited capabilities for simulated characters to interact with each other and with humans in rich, meaningful ways. Although significant achievements have been made in developing human behavior models (HBMs) that are able to control a single simulated entity (or a single group of simulated entities), a limiting factor is the inability of HBMs developed by different groups to interact with each other. We present an architecture and multi-level message framework for enabling HBMs to communicate with each other about their actions and their intents, and describe the results of our crowd control demonstration system which applied it to allow three distinct HBMs to interoperate within a single training-oriented simulation. Our hope is that this will encourage the development of standards for interoperability among HBMs which will lead to the development of richer training and analysis simulations.
MacMillan, I, Boisot, M, Abrahams, A & Bharathy, G 2005, 'Simulating the knowledge transfer dilemma: Lessons for security and counter-terrorism', Summer Computer Simulation Conference 2005, SCSC 2005, Part of the 2005 Summer Simulation Multiconference, SummerSim 2005, pp. 189-196.
Intelligence agencies face a knowledge transfer dilemma. They have compelling reasons to invest in codification, to structure and store knowledge about critical infrastructure and terrorist threats, and enable sharing with allied departments and governments. Threat information has a high obsolescence rate and short half-life: it is actionable before the attack, but not after. Timely response to terrorist chatter requires rapid diffusion of information, in codified form, to enforcement personnel. But, problematically, codification of infrastructure and threat information increases the diffusability of such knowledge, making it increasingly accessible to terrorists, who can use the information in planning new attacks or revising existing plans. This paper introduces a graphical simulation environment, I-Space 2, which has been built for simulating knowledge management processes, and illustrates its potential application to the knowledge-transfer dilemma facing the counter-terrorism community.
Silverman, BG & Bharathy, GK 2005, 'Modeling the personality & cognition of leaders', Simulation Interoperability Standards Organization - 14th Conference on Behavior Representation in Modeling and Simulation 2005, pp. 158-165.
This paper summarizes efforts at adapting a personality profiling framework to model behavior and choices of political and military leaders. This is part of a larger project to create a role-playing, decision-making game to allow you to play out scenarios of interest against other leaders. In this modeling exercise we implement the Hermann leader personality profile tool to create historic leaders (Saladin, Richard I, etc.). We then attempt to validate the leader agents against scenarios of the 3rd Crusade.