Anand J Kulkarni

PhD, MASc, BEng, DME

Chairman: Optimization and Agent Technology Research (OAT Research) Lab

Email: anandmasc@gmail.com; kulk0003@{ntu.edu.sg; outlook.com}

ResearcherID: www.researcherid.com/rid/O-3585-2016

ORCID ID: orcid.org/0000-0001-6242-9492

Google Scholar

Areas of Interest:

Optimization Algorithms, Multi-objective Optimization, Continuous, Discrete and Combinatorial Optimization, Multi-Agent Systems, Complex Systems, Cohort Intelligence, Probability Collectives, Genetic Algorithms, Swarm Optimization, Artificial Neural Networks, Nash Equilibrium, Game Theory, Graph Theory, Computational Geometry, Numerical Methods, Fault-tolerant and Self-healing Systems, Self-organizing Systems

Career Snapshot

• Over 23 years of Research and Academic experience

• Research Fellow on the Cross-Border Supply Chain Disruption Project at Odette School of Business, University of Windsor, Canada

• Founder and Chair of Optimization and Agent Technology Research (OAT Research) Lab: An International Research Organization

• Developed Distributed Optimization Software

• A Doctor of Philosophy (PhD) from Nanyang Technological University, Singapore

• A Master of Applied Science (MASc) from University of Regina, Canada

Education

2007-2012    PhD (Mechanical and Aerospace Engineering) Nanyang Technological University,   Singapore

Thesis: A Distributed Multi-agent System Approach for Solving Constrained Optimization Problems using Probability Collectives

2004-2006    Master of Applied Science (MASc) (Industrial Systems Engineering) from University of Regina, SK, Canada

Thesis: Optimization of Connection Weights of Artificial Neural Networks through Layer Partition and Genetic Algorithms

Professional Work Experience

June 2021- till date: Professor & Associate Director of Institute of Artificial Intelligence at MITWPU, Pune, MH, India

March 2016-May 2021: Associate Professor at Symbiosis International University, Pune, MH, India

2014-Feb 2016: Assistant Professor at Symbiosis Institute of Technology ,Pune, MH, India

2012-till date: Chairman of OAT Research Lab

2013-2014: Research Fellow at Odette School of Business, University of Windsor, Canada

2011-2013: Assistant Professor at Maharashtra Institute of Technology, Pune, MH, India

2013-2022: Vice President of Central India Alumni Association: Nanyang Technological University, Singapore

2006-2007: Lecturer with Pune University, MH, India

2003-2004: Production Engineer with Poona Couplings Pvt. Ltd., Pune, MH, India

2002-2003: System Engineer with Yantra Automation, Pune, MH, India

2008-2011: Teaching Assistant with the Faculty of Mechanical and Aerospace Eng, Nanyang Technological University, Singapore

2005-2006: Teaching Assistant with the Faculty of Industrial Systems Engineering, University of Regina, SK, Canada

2004-2006: Research Assistant with the Faculty of Industrial Systems Engineering, University of Regina, SK, Canada

1. Kulkarni, A.J.: “Multiple Criteria Decision Making – Techniques, Analysis and Applications”, Studies in Systems, Decision and Control, Springer, 407, (2022), (ISBN 978-981-16-7414-3), (ISBN 978-981-16-7414-3)

Journal Papers

2025

1. Garg V., Deep K., Kulkarni, A.J. (2025): Laplacian biogeography-based algorithm using a gaining–sharing knowledge-based strategy for global optimization problems and the Lennard-Jones problem, Engineering Optimization, 1-32 (IF: 2.2)

2024

2. Nargundkar, A., Shastri, A.S., Silswal, S., Kulkarni, A.J. (2024): Optimization of Process Parameters for Printed Circuit Board Drilling for Micro Needle with Socio Inspired Optimization Algorithms, International Journal on Interactive Design and Manufacturing (In Press) (IF: 2.1)

3. Singh, A., Dutta, S., Agrawal, G., Sapre, M.S., Kulkarni, A.J. (2024): A machine learning approach to predict demand-to-capacity ratio for reinforced concrete jacketing of columns in seismic-deficient buildings, Journal of Building Pathology and Rehabilitation, 10(33), 2025

4. Kulkarni, A.J., Kale, I.R., Shastri, A.S., Khandekar, A. (2024): Snail Homing and Mating Search Algorithm: A Novel Bio-Inspired Metaheuristic Algorithm, Soft Computing, 28, pp 10629–10668 (IF: 3.1)

5. Reddy, R., Gupta, U., Kale, I.R., Shastri, A.S., Kulkarni, A.J. (2024): Modified Leader-Advocate-Believer Algorithm with Clustering-Based Search Space Reduction Method for Solving Engineering Design Problems, SN Computer Science, 5(4), 376

6. Jain D.K., Qamar, S., Sangwan, S. R., Ding, W., Kulkarni, A.J. (2024): Ontology based Natural Language Processing for Sentimental Knowledge analysis Using Deep Learning Architectures, ACM Transactions on Asian and Low-Resource Language Information Processing, 23(1), pp 1-17 (IF: 2.0)

7. Kashan A.H., Karimiyan, S., Kulkarni, A.J. (2024): Golf Sport Inspired Search metaheuristic algorithm and the game theoretic analysis of its operators’ effectiveness, Soft Computing, 28, pp 1073-1125 (IF: 4.1), (DOI: 10.1007/s00500-023-09151-3)

2023

8. Nargundkar, A., Kulkarni, A.J. (2023): Application of Cohort Intelligence Algorithm for Goal Programming Problems with Improved Constraint Handling Method, International Journal of Bio-Inspired Computation, 21(2), pp 94-105 (IF: 3.5)

9. Reddy, R., Kulkarni, A.J., Shastri, A.S., Krishnasamy, G., Gandomi, A.H. (2023): LAB: A Leader-Advocate-Believer based Optimization Algorithm, Soft Computing, 27, pp 7209–7243 (IF: 4.1)

2022

10. Marak, Z.R., Ambarkhane, D., Kulkarni, A.J. (2022): Application of Artificial Neural Network Model in Predicting Profitability of Indian Banks, International Journal of Knowledge-Based and Intelligent Engineering Systems, 26(3), pp 159-173 (IF: 0.7)

11. Patil, M.V., Kumar S., Kulkarni, A.J. (2022): Multi Stopping Criterion Multi Feature based Multiobjective Cohort Intelligence Algorithm for Thermoacoustic Engine Optimization, International Journal of Modelling, Identification and Control, 40(4), pp 356-370 (IF: 0.7)

2021

12. Kale, I.R., Kulkarni, A.J. (2021): Cohort Intelligence with self-adaptive penalty function approach hybridized with colliding bodies optimization algorithm for discrete and mixed variable constrained problems, Complex and Intelligent Systems, 7, pp 1565–1596 (IF: 5.8)

13. Shastri, A.S., Nargundkar, A., Kulkarni, A.J. Benedicenti, L. (2021): Optimization of Process Parameters for Turning of Titanium Alloy (Grade II) in MQL Environment using Multi-CI Algorithm, SN Applied Sciences, 3(2), pp 1-12 (IF: 2.6)

2020

14. Bannur P., Gujrathi, P., Jain, K., Kulkarni, A.J. (2020): Application of Swarm Robotic System in a Dynamic Environment using Cohort Intelligence, Soft Computing Letters, 2,  100006

15. Patil, M.V., Kulkarni, A.J. (2020): Pareto Dominance based Multiobjective Cohort Intelligence Algorithm, Information Sciences, 538, pp 69-118 (TR IF: 5.910)

16. Shastri, A.S., Nargundkar, A., Kulkarni, A.J. (2020): Multi-Cohort Intelligence Algorithm for solving Advanced Manufacturing Process Problems, Neural Computing and Applications, 32, pp  15055-15075 (TR IF: 4.774)

2019

17. Iyer, V.H., Mahesh, S., Malpani, R., Sapre, M.S., Kulkarni, A.J. (2019): Adaptive Range Genetic Algorithm: A Hybrid Optimization Approach and its Application in the Design and Economic Optimization of Shell-and-Tube Heat Exchanger, Engineering Applications of Artificial Intelligence, 85, pp 441-461 (TR IF: 3.526)

18. Sarmah, D., Kulkarni, A.J. (2019): Improved Cohort Intelligence-a High Capacity, Swift and Secure Approach on JPEG image Steganography, Journal of Information Security and Applications, 45, pp 90-106, (TR IF: 1.532)

2018

19. Sapre, M.S. Kulkarni, A.J., Chettiar, L., Deshpande, I. Piprikar, B. (2018): Mesh Smoothing of Complex Geometry using Variations of Cohort Intelligence Algorithm (In press: Evolutionary Intelligence)

20. Shastri, A.S., Kulkarni, A.J. (2018): Multi-Cohort Intelligence Algorithm: An Intra- and Inter-group Learning Behavior based Socio-inspired Optimization Methodology, International Journal of Parallel, Emergent and Distributed Systems, 33(6), pp 675-715 (TR IF: 0.550)

21. Sarmah, D., Kulkarni, A.J. (2018): “JPEG based Steganography Methods using Cohort Intelligence with Cognitive Computing and Modified Multi Random Start Local Search Optimization Algorithms”, Information Sciences, 430-431, PP 378-396 (TR IF: 4.305)

22. Kumar, M., Kulkarni, A.J., Satapathy, S.C. (2018): “Socio Evolution & Learning Optimization Algorithm: A Socio-inspired Optimization Methodology”, Future Generation Computer Systems, 81, pp 252-272 (TR IF: 4.639)

23. Sarmah, D., Kulkarni, A.J. (2018): “Image Steganography Capacity Improvement using Cohort Intelligence and Modified Multi Random Start Local Search Methods”, Arabian Journal for Science and Engineering, 43(8), pp 3927–3950 (TR IF: 1.092)

24. Patankar, N.S., Kulkarni, A.J. (2018): "Variations of Cohort Intelligence", Soft Computing 22(6), pp 1731-1747 (TR IF: 2.367)

2017

25. Chang, W.L., Kanesan, J., Kulkarni A.J., Ramiah, H. (2017): “Data clustering using seed disperser ant algorithm”, Turkish Journal of Electrical Engineering & Computer Sciences, Vol 2017(25), pp 4522-4532  (TR IF: 0.578)

26. Kale, I.R., Kulkarni A.J. (2017): “Cohort Intelligence Algorithm for Discrete and Mixed Variable Engineering Problems”, International Journal of Parallel, Emergent and Distributed Systems, 33(6), pp 627-662 (TR IF: 0.550)

27. Shah, P., Agashe, S., Kulkarni, A.J. (2018): “Design of Fractional PID Controller using Cohort Intelligence Method”, Frontiers of Information Technology & Electronic Engineering, 19(3), pp 437–445 (TR IF: 0.910)

28. Dhavle, S.V., Kulkarni, A.J., Shastri, A., Kale, I.R. (2017): “Design and Economic Optimization of Shell-and-Tube Heat Exchanger using Cohort Intelligence Algorithm”, Neural Computing and Applications, 30(1), pp 111–125 (TR IF: 4.213)

2016

29. Kulkarni, O., Kulkarni, N., Kulkarni, A.J., Kakandikar, G. (2016): “Constrained Cohort Intelligence using Static and Dynamic Penalty Function Approach for Mechanical Components Design” International Journal of Parallel, Emergent and Distributed Systems, 33(6), pp 570-588 (TR IF: 0.550)

30. Teo, T.H., Kulkarni, A.J., Kanesan, J., Chuah, J.H., Abraham, A. (2017): "Ideology Algorithm: A Socio-inspired Optimization Methodology”, Neural Computing and Applications, 28(1), pp 845-876 (TR IF: 4.213)

31. Kulkarni, A.J., Kale, I.R., Tai, K. (2016) “Probability Collectives for Solving Discrete and Mixed Variable Problems”, International Journal of Computer Aided Engineering and Technology, 8(4), pp 325-361

32. Kulkarni, A.J., Shabir, H. (2016): “Solving 0-1 Knapsack Problem using Cohort Intelligence Algorithm”. International Journal of Machine Learning and Cybernetics, 7(3), pp 427-441 (TR IF: 2.692)

33. Kulkarni, A.J., Baki, M.F., “Chaouch, B.A. (2016): “Application of the Cohort-Intelligence Optimization Method to Three Selected Combinatorial Optimization Problems”, European Journal of Operational Research, 250(2), pp 427-447 (TR IF: 3.428)

34. Kulkarni, A.J., Patankar, N.S., Tai, K. (2016) “Constraint Handling in Probability Collectives using A Modified Feasibility-based Rule”, International Journal of Computational Science and Engineering, 13(4), pp 303-321

2014

35. Patankar, N.S., Kulkarni, A.J., Tai, K., Ghate, T.D, Parvate, A.R. (2014): "Multi-criteria Probability Collectives", International Journal of Bio-Inspired Computation, 6(6), pp 369-383 (TR IF: 2.266)

36. Krishnasamy, G., Kulkarni A.J., Paramesaran, R. (2014): “A hybrid approach for data clustering based on modified cohort intelligence and K-means”, Expert Systems with Applications, 41(13), pp 6009-6016 (TR IF: 3.768)

2012

37. Azad, S.K., Azad, S.K., Kulkarni, A.J. (2012) “Structural Optimization using a Mutation-based Genetic Algorithm”, International Journal of Optimization in Civil Engineering, 2(1), pp 80-100

38. Kulkarni, A.J. and Tai, K. (2011) “Solving Constrained Optimization Problems Using Probability Collectives and a Penalty Function Approach”, International Journal of Computational Intelligence and Applications, 10(4), pp 445-470

2011

39. Kulkarni, A.J. and Tai, K. (2011) “A Probability Collectives Approach with a Feasibility-based Rule for Constrained Optimization”, Applied Computational Intelligence and Soft Computing, Vol. 2011, Article ID 980216

2010

40. Kulkarni, A.J. and Mayorga, R.V. (2010) "Artificial Neural Network Optimization using Layer Partition and Genetic Algorithms along with Statistical Analysis", Computational Intelligence Research, 6 (1), pp 77-87

41. Kulkarni, A.J. and Tai, K. (2010) "Probability Collectives: A Multi-Agent Approach for Solving Combinatorial Optimization Problems", Applied Soft Computing, 10(3), pp 759-771 (TR IF: 3.907) 

Book Chapters

1. Krishnasamy, G., Kulkarni, A.J., Shastri, A.S., (2021): An improved Cohort Intelligence with Panoptic Learning Behavior for solving constrained problems, in Kulkarni, A.J., Mezura-Montes, E., Wong, Y., Gandomi, A.H., Krishnasamy, G. (Eds), in Constraint Handling in Metaheuristics and Applications, Springer, pp 29-54

2. Kumar, M., Kulkarni, A.J., Satapathy, S.C. (2020): “A Hybridized Data Clustering for Breast Cancer Prognosis and Risk Exposure Using Fuzzy C-means and Cohort Intelligence”, in Kulkarni, A.J., Satapathy, S.C. (Eds.), in Optimization in Machine Learning and Applications, Algorithms for Intelligent Systems, Springer, pp 113-126

3. Kulkarni, A.J., Nargundkar, A. (2020): ‘Big Data in Supply Chain Management and Medicinal Domain’, in Kulkarni, A.J., Siarry, P., Singh, P.K., Abraham, A., Zhang, M., Zomaya, A., Baki, F.: Big Data Analytics in Healthcare, Studies in Big Data, Vol 66, Springer, pp 45-54

4. Roychowdhury, P., Mehra, S., Devarakonda, R., Shrivastava, P., Basu, S., Kulkarni, A.J. (2019): “A Self-organizing Multi-agent Cooperative Robotic System: An Application of Cohort Intelligence Algorithm”, in Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh, K. A., Tai, K. (Eds.), in Socio-cultural Inspired Metaheuristics, Studies in Computational Intelligence, Vol 828, Springer, pp 27-40

5. Marde, K. and Kulkarni, A.J. (2019): “Optimum Design of Four Mechanical Elements Using Cohort Intelligence Algorithm”, in Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh, K. A., Tai, K. (Eds.), in Socio-cultural Inspired Metaheuristics, Studies in Computational Intelligence, Vol 828, Springer, pp 1-25

6. Kale, I. and Kulkarni, A.J. (2019):  “A Socio-based Cohort Intelligence Algorithm for Engineering Problems”, in Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh, K. A., Tai, K. (Eds.), in Socio-cultural Inspired Metaheuristics, Studies in Computational Intelligence, Vol 828, Springer, pp 121-135

7. Shah, P. and Kulkarni, A.J. (2019): “Application of Variations of Cohort Intelligence in Designing Fractional PID Controller for Various Systems”, in Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh, K. A., Tai, K. (Eds.), in Socio-cultural Inspired Metaheuristics, Studies in Computational Intelligence, Vol 828, Springer, pp 175-192

8. Shastri, A.S., Jagetia, A., Sehgal, A., Patel, M., Kulkarni, A.J. (2019): “Expectation Algorithm (ExA): A Socio-inspired Optimization Methodology”, in Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh, K. A., Tai, K. (Eds.), in Socio-cultural Inspired Metaheuristics, Studies in Computational Intelligence, Vol 828, Springer, pp 193-214

9. Kumar, M. and Kulkarni, A.J. (2019): “Socio-inspired Optimization Metaheuristics: A Review”, Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh, K. A., Tai, K. (Eds.), in Socio-cultural Inspired Metaheuristics, Studies in Computational Intelligence, Vol 828, Springer, pp 241-265

10. Kulkarni, A.J. and Tai, K. (2013): “A Probability Collectives Approach for Multi-Agent Distributed and Cooperative Optimization with Tolerance for Agent Failure”, in Czarnowski, I, Jedrzejowicz, P. and Kacprzyk J. (Eds.), Agent Based Optimization, Studies in Computational Intelligence, Vol 456, Springer, pp 175-201

11. Kulkarni, A.J. and Tai, K. (2009): "Probability Collectives: A Decentralized, Distributed Optimization for Multi-Agent Systems", in J. Mehnen, M. Koeppen, A. Saad, A Tiwari (Eds.), Advances in Intelligent and Soft Computing, Applications of Soft Computing, Vol 58, Springer, pp 441-450

Conference Papers

1. Shastri, A.S., Nargundkar, A., Kulkarni, A.J. (2021): Modified Multi-cohort Intelligence Algorithm with Panoptic Learning for Unconstrained Problems, Intelligent Data Engineering and Analytics, Satapathy, S., Zhang, Y.D., Bhateja, V., Majhi, R. (Eds), Springer, Vol 1177, pp 145-153

2. Shastri, A.S., Thorat, E.V., Kulkarni, A.J., Jadhav, P.S. (2019): Optimization of Constrained Engineering Design Problems using Cohort Intelligence Method, Advances in Intelligent and Soft Computing, Kulkarni, A.J., Satapathy, S.C., Tai, K., Kashan, A.H. (Eds), Springer, Vol 828, pp. 1-11

3. Sapre, S.M., Kulkarni, A.J., Shinde, S.S. (2019): Finite Element Mesh Smoothing Using Cohort Intelligence, Advances in Intelligent and Soft Computing, Kulkarni, A.J., Satapathy, S.C., Tai, K., Kashan, A.H. (Eds), Springer, Vol 828, pp 469-480

4. Gaikwad, S., Joshi, R., Kulkarni, A.J. (2016): “Cohort Intelligence and Genetic Algorithm along with Modified Analytical Hierarchy Process to Recommend an Ice Cream to a Diabetic Patient”, Advances in Intelligent and Soft Computing, Satapathy, S.C., Bhateja, V. Joshi, A. (Eds), Springer, Vol 468, pp. 279-288

5. Gaikwad, S., Joshi, R., Kulkarni, A.J. (2015): “Cohort Intelligence and Genetic Algorithm along with AHP to recommend an Ice Cream to a Diabetic Patient”, Lecture Notes in Computer Science, Vol 9873, Springer, pp. 40-49

6. Shastri, A.S., Jadhav, P.S., Kulkarni, A.J., Abraham, A. (2016): “Solution to Constrained Test Problems using Cohort Intelligence Algorithm”, Advances in Intelligent and Soft Computing, Vol 424, Springer, pp. 427-435

7. Chang, W.L., Kanesan, J., Kulkarni, A.J. (2015): “Seed Disperser Ant Algorithm: Ant Evolutionary Approach for Optimization”, Lecture Notes in Computer Science, Vol 9028, Springer, pp. 643-654 

8. Metkar, S.J., Kulkarni, A.J. (2014): “Boundary Searching Genetic Algorithm: A Multi-objective Approach for Constrained Problems”, in Advances in Intelligent and Soft Computing, Satapathy, S.C., Biswal, B.N., Udgata, S.K. (Eds), Vol 247, Springer, pp. 269-276

9. Kulkarni, A.J., Baki, F., Chaouch, B. (2014): A New Variant of the Assignment Problem: Application, NP-hardness and Algorithms, Optimization Days, Montreal, Canada, May 5-7, 2014

10. Kulkarni, A.J., Durugkar I.P., Kumar M. (2013): “Cohort Intelligence: A Self Supervised Learning Behavior”, in Proceedings of IEEE International Conference on Systems, Man and Cybernetics, Manchester, UK, 13-16 October 2013, pp. 1396-1400

11. Deshpande, A.M., Phatnani G.M., Kulkarni, A.J. (2013): “Constraint Handling in Firefly Algorithm”, in Proceedings of IEEE International Conference on Cybernetics, Lausanne, Switzerland, 13-15 June 2013, pp. 186-190

12. Kulkarni, A.J., Kale, I.R., Tai, K. (2013) “Probability Collectives for Solving Truss Structure Problems”, in Proceedings of 10th World Congress on Structural and Multidisciplinary Optimization (WCSMO’ 2013), Orlando, Florida, USA, 19-24 May 2013, Paper ID: 5395

13. Kulkarni, A.J., Tai, K. Kale, I.R., Azad, S.K. (2012) “Discrete Optimization of Truss Structure using Probability Collectives”, in Proceedings of IEEE Hybrid Intelligent Systems (HIS 2012), Pune, India, 04-07 December 2012, pp. 225-230

14. Kulkarni, A.J., Tai, K., Patankar, N.S., Amani, S. (2012) “A Modified Feasibility-based Rule For Solving Constrained Optimization Problems Using Probability Collectives”, in Proceedings of IEEE Hybrid Intelligent Systems (HIS 2012), Pune, India, 04-07 December 2012, pp. 213-218

15. Kulkarni, A.J. and Tai, K. (2010) “Probability Collectives: A Distributed Optimization Approach for Constrained Problems”, in Proceedings of the 2010 IEEE World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain, 18-23 July 2010, pp. 3844-3851

16. Kulkarni, A.J. (2010) "A Probability Collectives Approach for Distributed Optimization of Complex Systems", in Proceedings of the 'Doctoral Consortium' of 2010 IEEE International Conference on Networking, Sensing and Control (ICNSC 2010), Chicago, USA, 10-12 April 2010

17. Kulkarni, A.J. and Tai, K. (2008) "Probability Collectives: A Decentralized, Distributed Optimization for Multi-Agent Systems", in Proceedings of the 2008 Online World Conference on Soft Computing in Industrial Applications (WSC 2008), 10-21 November 2008, paper no. 098

18. Kulkarni, A.J. and Tai, K. (2008) "Probability Collectives for Decentralized, Distributed Optimization: A Collective Intelligence Approach", in Proceedings of the 2008 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2008), Singapore, 12-15 October 2008, pp. 1271-1275

19. Kulkarni A.J. and Mayorga, R.V. (2008) "Optimizing Artificial Neural Networks through Layer Partition and Genetic Algorithms", in Proceedings of the 2008 SCIS & ISIS, Nagoya, Japan, 17-21 September 2008, pp. 76-81

20. Kulkarni, A.J. and Mayorga, R.V. (2005) "The Design of the Spindle of the Cylindrical Grinding Machine through Neural Networks and Genetic Algorithm", in Proceedings of the 2nd Indian International Conference on Artificial Intelligence (IICAI 2005), Pune, India, 20-22 December 2005, pp. 3323-3336

Workshops and Others

1.    Kulkarni, A.J. and Tai, K. (2012) ‘Probability Collectives: A Distributed Multi-Agent System Approach for Optimization of Complex Systems’ at IEEE Hybrid Intelligent Systems (HIS 2012), Pune, India, Dec’ 05, 2012

2.    Kulkarni, A.J. and Tai, K. (2010) "Probability Collectives: A Decentralized, Distributed Optimization of Complex Systems - II", in Graduate Student Workshop, Jointly Organized by IEEE Power & Eng. Society and IEEE Industry Applications / Power Electronics         Joint Chapter, National University of Singapore, 19 October 2010

3.    Kulkarni, A.J. and Tai, K. (2009) “Probability Collectives for Distributed, Decentralized Optimization of Complex Systems”, in Interdisciplinary Conference on Adaptation, Order and Emergence- A Tribute to Dr. John Holland, (Poster Presentation), Nanyang Technological  University, Singapore, February 12, 2009

4.    Kulkarni, A.J. and Kulkarni, S.P. (2002) “Advanced Trends in Production Technology”, in Proceedings of Quantum-2002, National Level Technical Symposium, Shivaji University, MH, India, March 26-27, 2002

5.    Kulkarni, A.J. and Hiremath, P.G. (2000) “Pollution Reducer for Stationary Diesel Engines”, in Proceedings of Vision-2000, 12th National Level Technical Meet, Shivaji University, MH, India, February 25-27, 2000

6.    Kulkarni, A.J. and Gangapure, A.T. (2000) “Smart Sensors in Hydro-Electric Power Station”, in Proceedings of Technoglimpse-2000, 4th State Level Paper Technical Symposium, Shivaji University, MH, India, March 2, 2000

Fellowships/Scholarships/Awards

• Swatantrya Veer Sawarkar Award for the Book Entitled ‘आर्टिफिशिअल इंटेलिएजन्सच्या वाटेवर’ on May 29, 2023

• Cross-border (USA-CANADA) Institute Fellowship from Nov’ 2013-Nov’ 2014

• Graduate Research Scholarship awarded from Aug’ 2007-Aug’ 2011

• IEEE SMC Conference Grant awarded by ‘IEEE SMC’ for the International Conference on Systems, Man, and Cybernetics (SMC 2008), Singapore, 12-15 Oct’ 2008

• ‘Best Research Proposal’ Award at the PhD Consortium ‘IEEE ICNSC’ at Chicago 10-12 Apr’ 2010

• NTU Student Oversea Travel Grant awarded for PhD Consortium held in conjunction with ‘IEEE ICNSC’ at Chicago 10-12 Apr’ 2010

• ICNSC Doctoral Consortium Grant awarded by ‘IEEE ICNSC’ for the PhD Consortium held in conjunction with ‘IEEE ICNSC’ at Chicago 10-12 Apr’ 2010 

Research Students

• PhD: Six (6) Completed

• Master’s: Five (5) Completed

• Bachelor’s: Forty five (45) Completed 

Research Talks/Visits

• MITWPU, School of ECE, August 21-25, 2023 (Topic: AI Nature-Inspired Optimization Methods Training)

• MITWPU, Polytechnic, Oct 10-14, 2023 (Artificial Intelligence Nature inspired optimization Methods and Introduction to Machine Learning)

• COEP Technological University, Pune, August 1-4, 2023, (Topic: AI based Optimization)

• Keynote Speaker at the VIIMS International Conference Metaverse, May 11, 2024 (Topic: Metaverse: Introduction, Applications & Opportunities)

• Keynote Speaker at the International conference BASIC 24 at the VBS, Mumbai, February 15, 2024 (Topic: Use of Optimization Techniques in Inventory Analysis)

• Keynote Speaker in the International Conference on Advances in Machine Intelligence and Cybersecurity Technologies (AMICT) 2023, Universiti, Malaysia Sabah, Malaysia, December 11-12, 2023

• SAE India, Pune Section, March 23, 2024, (Topic: Automotive Future Trends)

• SAE India, Pune Section, December 2, 2023, (Topic: Technical Revolution in Industry by AI & ML)

• Keynote Speaker in the International Conference on Advanced Technologies and Intelligent Automation (ICATIA 2024), Pune, May 18-19, 2024 (Topic: Artificial Intelligence and Everyday Applications)

• ATAL FDP, Balaji Institute of Management, Pune, Oct 30, 2023

• ATAL FDP, Balaji Institute of Management, Pune, Nov 3, 2023

• Amity University UP, India, 8th Global Leadership Research Conference (GLRC 2023), March 13, 2023 (Topic: Cohort Intelligence Method and Applications)

• JIT Nagpur, AI-based Nature Inspired Optimization Methods, Jan 9-13, 2023

• IGSMP International, VC, Australia, Dec 9, 2022, Artificial Intelligence, Machine Learning and Robotics (Topic: Cohort Intelligence for Swarm Robotics)

• Keynote Speaker at International Conference on Modeling, Simulations, and Optimizations (CoMSO-2022) December 21-23, 2022, NIT Silchar, Assam, India

• NIET, NIMS University, Jaipur, India Dec 8, 2022 (Topic: AI applications in healthcare)

• JSS Science and Technology University, National Workshop on Deep Learning and Its Applications, Nov 14, 2022 (Chief Guest and Speaker, Topic: Perceptron and Applications)

• KLE Technological University, Dr. MSSCET Belagavi, Oct 7, 2022 (Topic: Optimization Algorithms)

• JSS Science and Technology University, Mysuru, India, Sep 5, 2022, A National Level Workshop (Topic: Data Analytics and Learning)

• MITWPU Mechanical Engineering: Oct 11, 2021 (Topic: Cohort Intelligence for Mechanical Engineering Problems)

• Rajarambapu Institute of Technology, Sangli, October 1, 2021 STTP on Optimization (Topic: Evolutionary and Socio-inspired Optimization Algorithms)

• MITWPU Polymer Engineering: July 20, 2021 (Topic: Introduction to Artificial Intelligence with Applications to Polymer Engineering)

• MITWPU SCET: July 8, 2021 (Topic: Research Publications, Grants and Funding Proposals)

• Springer Conference: ISDA 2020, Dec 18, 2020 (Topic: AI based Optimization of Micro-machining Processes)

• RMK College of Engineering and Technology, TN, India, AICTE STTP, Oct 24, 2020 (Topic: Optimization of Micro-machining Processes)

• Coimbatore Institute of Technology, May 30, 2020, PMMMNMTT Govt of India (Topic: Cohort Intelligence Algorithm)

•  Keynote Speaker at E-Tonomy 2019, Les Mureaux, France, Oct 9-10, 2019 (A Cohort Intelligence based Cobotics for helping Disabled People for Swimming and Rescue) 

• Symbiosis International (Deemed University), Pune, March 25-29, 2019 (Faculty Development Program on Optimization Techniques and Computational Intelligence)

• Rajarambapu Inst of Tech, Sangli, April 16, 2018 (Basics of Optimization)

• Sinhgad College of Eng, Pune, January 9, 2018 (Basics of Optimization)

• Rajarambapu Inst of Tech, Sangli, November 23, 2017 (Socio-inspired Optimization Methods and Apps)

• Vishwakarma Inst of Info Tech, Pune, October 24, 2017 (Socio-inspired Optimization Methods)

• Optimization in Industry (2017) VIIT, India (June 05, 2017)

• PVP Siddhartha Institute of Technology, April 24-28, 2017, (Computational Intelligence & its Applications in Science and Engineering)

• University of Pune, India, (Workshop on Optimization Techniques with Research Perspective), Dec’ 24, 2016 (Socio-inspired Optimization Methods)

• 6th International Conference on Innovations in Bio-Inspired Computing and Applications IBICA, Kochi, India, Dec’ 17, 2015 (Introduction to Cohort Intelligence)

• Symbiosis International University, Oct’ 21, 2015 (Quantitative Methods)

• Symbiosis International University, Sep’ 15, 2015 (Encouraging Research and Writing)

• University of Malaya, Malaysia, July 01-11, 2015 (Cohort Intelligence and Recent Developments)

• University of Pune, India, (International Workshop on Advances in Optimization), Jan 30, 2015, (Distributed Optimization and Swarm Intelligence)

• University of Pune, India, (Design of Experiments and  Optimization Techniques), June 04, 2015 (Probability Collectives and Cohort Intelligence)

• University of Malaya, Malaysia, Dec’ 12-22, 2014 (Distributed Optimization)

• University of Windsor, Canada, April 17, 2014 (Distributed Optimization and Swarm Intelligence)

• University of Malaya, Malaysia, July 22-26, 2013 (Development in Distributed and Decentralized Optimization)

Computer Skills

MATLAB, AMPL

Part Time Experience

2004-2006  Chef with ARAMARK Food Services at University of Regina, SK, Canada

               Survey of the International People and Marketing of the International Food at the University

                Cook for Athletes at Canada Summer Games 2005

Last updated on Jan 2, 2025