Dr. Adham Salih

Refereed Papers
1. Salih, A., and Eisenstadt Matalon, E. (2025), Game-based Multi-objective Evolution of Robust Controllers. ISA Transactions. doi: 10.1016/j.isatra.2025.09.006.
2. Weiss, A., Ben-Hanan, U. & Salih, A., (2025), Dynamics Mimicking – Enabling Robot Operation for Wheelchair Users. IEEE Sensors Journal, doi: 10.1109/JSEN.2025.3559666.
3. Salih, A., Roth, N., Buganim, O., Pelosi, A.D. (2024), A Low-Cost Open-Source Uniaxial Tensile System for Soft Tissue Testing. Hardware 2024, 2, 292-305.
4. Salih, A., and Eisenstadt Matalon, E. (2024), Solving Multi-objective Robust Optimization Problems via Stackelberg-based Game Model. Swarm and Evolutionary Computation 91, 101734.
5. Roth, N., Salih, A., and Rosenblum, S. (2024), Subjective and objective day-to-day performance measures of people with essential tremor. Sensors, 24(15), 4854.
6. Salih, A., Gabbay, J., & Moshaiov, A. (2024). Transferability of multi-objective neuro-fuzzy motion controllers: Towards cautious and courageous motion behaviors in rugged Terrains. Mathematics, 12(7), 992.
7. Salih, A., & Moshaiov, A. (2024). Neuro-evolution-based generic missile guidance law for many-scenarios. Applied Soft Computing, 152, 111210.
8. Salih, A., & Moshaiov, A, (2022). Evolving topology and weights of specialized and non-specialized neuro-controllers for robot motion in various environments. Neural Computing and Applications.
9. Salih, A., & Moshaiov, A. (2022). Promoting transfer of robot neuro-motion-controllers by many-objective topology and weight evolution. IEEE Transactions on Evolutionary Computation.
10. Benyamin, O. B., Juvinao, D., Berlinsky, T., Salih, A., Solomonov, E., Waksman, I., & Biswas, S. (2022). Designing engineering solutions to surgical problems: how to translate physiology to biomechanics. Journal of The Institution of Engineers (India): Series C, 103(5), 1095–1102.

Conference Proceedings and Abstract
Salih, A., & Moshaiov, A. (2022). Benchmarking many-objective topology and weight evolution of neural networks: A study with NEWS/D. In the proceedings of the 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021, 1–6. 

1. Moshaiov, A., & Salih, A. (2022). Multi-objective structure and parameter evolution of neuro-fuzzy systems. In the proceedings of the 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021. 01-07.
2. Salih, A., & Moshaiov, A. (2021). Modified decomposition framework and algorithm for many-objective topology and weight evolution of neural networks. In the proceedings of the 2021 IEEE Congress on Evolutionary Computation (CEC), 1478–1485. 
3. Salih, A., & Moshaiov, A. (2017). Multi-objective neuro-evolution: Should the main reproduction mechanism be crossover or mutation? In the proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)2017, pp. 4585–4590.

Academic Appointments
2018 – Present Faculty Member, Braude College, Department of Mechanical Engineering
2020 – Present Head of the mechatronics track, Braude College
2018 – 2021 Member of the discipline committee, Braude College
2018 – 2021 Member of the exemption based on practical engineering studies committee, Department of Mechanical Engineering, Braude College
2014 – 2018 Adjunct Lecturer, Braude College, Department of Mechanical Engineering.
2014 – 2018 Lecturer, Practical Eng. School, Ort Braude College.

Teaching Experience
Dynamic of Rigid Bodies
Signals and Systems
Introduction to Mechatronics
Mechatronics Laboratory
Integrated Systems
Modern Control
Evolutionary Algorithms and Machine Learning

Academic and Professional Awards and Grants
2022-2024 Outstanding Faculty Member, Braude College – three consecutive years
2019-2021 Zvi Ynai PhD Scholarship, awarded by the Israeli Ministry of Science & Technology./250 kNIS
2016 IEEE SMC Student Travel Grant.
2016 Scholarship for Excellence, awarded by the Iby and Aladar Fleischman Faculty of Eng., Tel-Aviv Univ.
2015 Instructor and supervisor of a team of students in the course "Aerial Robotics" to win 2nd place in a national aerial robotics competition, with prize money of 10 kNIS.
2015 Outstanding Teacher, Braude College.
2014 Instructor and supervisor of a team of students in the course "Aerial Robotics" to win 2nd place in a national aerial robotics competition, with prize money of 15 kNIS.
2014 Outstanding Teacher, Braude College.
2013 Research Assistant Prize, awarded by Braude College.

Professional Appointments
2017 – Present Flagship Project Supervisor and Technical Consultant for Rehabilitation Biomechanics Projects
• Flagship Project: the foundation of an interdisciplinary academic knowledge center of applied research for developing engineering solutions for disabled people.

2016 – 2018 Teacher at Biomechanics program for outstanding high school students, Atidim and Galilee Development Ministry.
2013 Research assistant in Robotic Cognition, the Department of Mechanical Eng., Braude College.

Computational Intelligence
Computational Intelligence (CI) encompasses the development of bio-inspired computational tools aimed at addressing various applications. It primarily concentrates on Artificial Neural Networks, Fuzzy Logic, and Evolutionary Computation.
My interest lies in the development and application of these tools within engineering contexts, particularly in the area of multi-objective optimization.

Evolutionary Multi-objective Optimization
Optimization problems in real-world scenarios frequently involve conflicting objectives. In such a case, a single solution cannot optimize all the objective functions without prior scalarization.
Performance trade-offs become significant in the selection process when objectives conflict. To comprehend these trade-offs, vector-based optimization essential, as evidenced by the extensive body of literature on evolutionary multi-objective optimization. The primary objective of these algorithms is to accurately and diversely approximate the set of Pareto-optimal solutions, which are defined as those solutions that cannot be improved in one objective without compromising another.
I am particularly interested in utilizing these tools for engineering optimization tasks, including multi-objective robust optimization and multi-objective neuro-evolution.

Evolutionary Robotics and Neuro-control
Evolutionary robotics is a computational framework aimed at autonomously creating robot controllers and other crucial robotic elements, such as mechanics, sensors, and actuators. In this field, robots are evolved to maximize rewards, typically gained through interactions with simulated or real-world environments.
I am particularly interested in developing and utilizing tools for designing neuro controllers, which are artificial neural networks that serve as controllers for robotic tasks. Additionally, I keen on using these tools to explore brain-computer interfaces.