Biologically Inspired Algorithms Professors and Supervisors | ApplySharif

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Samaneh BerenjianView profile

Senior Lecturer

New Jersey Institute of Technology (NJIT)United States

Samaneh Berenjian is a Senior Lecturer in the Department of Computer Science at New Jersey Institute of Technology (NJIT). Her academic journey includes a Ph.D. from Stevens Institute of Technology (2022), and M.S. degrees from Stevens (2018) and Amirkabir University of Technology (2013), alongside a B.S. from the University of Isfahan (2011). Her research focuses on cybersecurity, network security, and peer-to-peer systems, with contributions to secure protocol design, intrusion response mechanisms, and privacy-preserving technologies. She has also explored navigation models in AI and wireless sensor networks. Her research interests span cybersecurity frameworks, P2P network anonymity, and intelligent systems. Notable work includes encryption-based protocols, incentive models for secure P2P fairness, and fuzzy logic-based intrusion detection systems. Her 2020 GridCell navigational model highlights interdisciplinary AI contributions. Her publications reflect expertise in secure communication, network architecture, and optical fiber error control. While no awards are listed, her work demonstrates consistent engagement with cutting-edge topics in computer science and information security.

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Andrew VardyView profile

Professor

Memorial University of NewfoundlandCanada

Andrew Vardy is a Professor jointly appointed to the Faculty of Engineering and Applied Science and the Department of Computer Science at Memorial University of Newfoundland. He holds a B.Eng. in Electrical Engineering (Memorial), M.Sc. in Evolutionary and Adaptive Systems (University of Sussex), and PhD in Computer Science (Carleton University). His research explores swarm robotics, biologically inspired algorithms, autonomous navigation, and multi-robot systems. Key areas include visual homing, distributed construction, environmental sensing, and robotic simulation tools. He leads the Memorial University Bots Lab, developing applications for marine and terrestrial environments. Vardy teaches courses in autonomous robotics, computer programming, software design, and control systems. His publications emphasize computational complexity in swarm algorithms, reinforcement learning for coordination, and novel applications like drum accompaniment AI and marine urchin detection. Recent work integrates attention mechanisms, transformer networks, and edge computing paradigms.

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Chris HuyckView profile

Professor

Middlesex UniversityUnited Kingdom

Prof Chris Huyck is a Professor of Artificial Intelligence at Middlesex University's Faculty of Science and Technology, Department of Computer Science, with 25 years of academic experience. His career spans institutions including the University of Sheffield, Microsoft, and the American University in Cairo, culminating in a PhD from the University of Michigan (1994). Dr. Huyck's research focuses on Cell Assemblies (CAs) grounded in mammalian neural circuitry, extending to cognitive architectures , neuromorphic hardware , and NLP applications . Key projects include modeling associative memory , category learning , and robotic control systems using spiking neural networks. Recent Publications : 2025 firefly algorithm tuning studies; 2024 emotion-integrated cognitive models; 2023 UAV path planning with coronavirus-inspired optimization Awards : No specific honors mentioned Students : Supervising Geethu Joy (PhD Enrolled, 2022-) and Babak Mohajer Ashjaei (PhD Enrolled, 2025-) Labs : Active in Middlesex's AI research group, integrating neuroscience with robotics and NLP

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Xin-She YangView profile

Associate Professor

Middlesex UniversityUnited Kingdom

Xin-She Yang is an Associate Professor in Simulation & Modelling at Middlesex University, London. He holds a DPhil in Applied Mathematics from the University of Oxford and has over 25 years of experience in research and teaching. His academic roles include serving as an Editor-in-Chief, editorial board member for multiple journals, and chair of IEEE CIS Task Force on BIKM (2015-2020). He is a Fellow of the Institute of Mathematics and its Applications (2021), Asian Computational Intelligence Society (2023), and Soft Computing Research Society (2025). Research interests span nature-inspired computing, mathematical modelling, engineering simulation, AI, algorithms, and optimization. Notable achievements include being listed as a top 0.1% scientist in Web of Science since 2016 and receiving multiple Leader Awards in Computer Science (2023–2025). He supervises PhD students in areas like parameter tuning, nature-inspired computing, and optimization. Teaching includes courses on engineering simulation, mathematical optimization, and partial differential equations. He has authored books like Optimization Techniques and Applications with Examples and contributed to Springer's Nature-Inspired Computing and Optimization series. Education: DPhil in Applied Mathematics, University of Oxford (1998) Affiliations: IEEE, IMA, Asian CIS Grants: UKRI Doctoral Training Centres, National Research Councils (Iceland, Ireland, etc.)

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Ali A. MinaiView profile

Professor

University of CincinnatiUnited States

Ali A. Minai is a Professor of Electrical & Computer Engineering at the University of Cincinnati, with a secondary appointment in Computer Science and affiliation in the Neuroscience Graduate Program. He holds a PhD in Electrical Engineering from the University of Virginia (1991) and postdoctoral training in neuroscience. His research spans neural networks, complex systems, computational neuroscience, and text analysis, with a focus on creativity dynamics and brain networks. He has led major grants including an NSF INSPIRE award (2012) and served as President of the International Neural Network Society (2015-16). His work bridges AI, cognitive models, and biological systems. Education: PhD in Electrical Engineering, University of Virginia, 1991 MS in Electrical Engineering, University of Virginia, 1987 Research Interests: His work emphasizes computational models of cognition, neural networks, and social networks. Current projects include analyzing text corpora to study creativity, hippocampal modeling for spatial processing, and applying deep learning to clinical medicine. His models explore how neural systems generate and adapt ideas, with applications to robotics and biomedical research. Grants & Awards: Over $2M in NSF grants, including the INSPIRE award (2012) for creativity studies. Collaborative projects with federal agencies (Air Force, Army) focus on machine learning for verification processes and innovation diffusion. Service & Editorial Work: Served on editorial boards of Neural Networks and IEEE Transactions on Neural Networks , and organized major conferences like IJCNN 2011. Active in professional societies (IEEE, INNS).

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Harold WarehamView profile

Professor

Memorial University of NewfoundlandCanada

Dr. Harold Wareham is a tenured Professor in the Department of Computer Science at Memorial University of Newfoundland (MUN), Faculty of Science. He holds a Ph.D. from the University of Victoria and has been at MUN since 1999, advancing through roles including Assistant Professor, Associate Professor, and Full Professor. His research focuses on computational complexity theory applied to cognitive science, robotics, and computational biology. He has served on numerous academic committees and international conference program committees. Education: B.Sc. (Computer Science) and B.A. (Linguistics/Mathematics) from MUN, followed by an M.Sc. in Computational Biology and a Ph.D. in Parameterized Complexity in Computational Phonology from the University of Victoria. Research Interests Computational complexity of cognitive processes Algorithm design for robotics and swarm control Parameterized complexity in biological systems Machine learning interpretability Recent Work Trends Recent publications emphasize applying complexity theory to AI interpretability (e.g., neural network reverse-engineering) and cognitive science (segmentation processes). His robotics research explores algorithmic foundations for swarm construction tasks. He also investigates computational challenges in software reconfiguration and modularization. Awards 2017 Best Professor Award (MUN CS Graduate Society) Teaching Fellow at Radboud University (2014–) F. A. Aldrich Alumni Graduate Scholarship (1989) Grants & Advising Has supervised numerous courses across undergraduate and graduate levels, including AI topics, computational biology, and theoretical computer science. Active in grant review roles for NSERC and international funding bodies. Served on MUN committees for promotion, tenure, and graduate studies. Labs & Collaborations Associated with the MUN CS Theory Group and the Bio-inspired Robotics (BOTS) Lab. Collaborates internationally on projects like the Dagstuhl Complexity Workshops and cognitive science initiatives.

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Mojtaba AhmadiView profile

Professor

Carleton UniversityCanada

Mojtaba Ahmadi is a Professor in the Department of Mechanical and Aerospace Engineering at Carleton University, cross-appointed within the Faculty of Engineering and Design. He holds a B.Sc. from Sharif University, an M.Sc. from the University of Tehran, and a Ph.D. from McGill University. His research focuses on robotics, mechatronics, and control systems with applications in rehabilitation, aerospace, and biologically inspired systems. Key areas include robotic locomotion, real-time control, and neuromorphic computing. He has contributed to advancements in FPGA-based neural network implementations, memristor circuits, and soft actuators. Dr. Ahmadi has served on technical committees for conferences such as CA2008, ICA2009, and CSME 2008, and organized special sessions on control applications. His work bridges theoretical models with practical hardware solutions, emphasizing interdisciplinary approaches. Publications span topics from spiking neural networks and neuromorphic vision systems to low-resource digital neuron implementations. He actively explores applications in healthcare robotics and energy-efficient computing architectures.

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Peyman MirtaheriView profile

Professor

Michigan Technological UniversityUnited States

Peyman Mirtaheri is a full Professor of Biomedical Engineering at Oslo Metropolitan University's Faculty of Technology, Art and Design, leading the NIRS/optical lab established in 2009. He holds an adjunct professorship at Michigan Technological University's Biomedical Engineering department. His research focuses on developing novel sensor technologies for brain activity detection and applying fNIRS/EEG to study motion and balance in the cerebral cortex. As PI, he oversees major projects like PACER (RCN-funded), MgSafe (Horizon 2020), and Future Running Shoes (IP-N collaboration with Gaitline AS). He teaches medical sensors and actuators in the ACIT master's program and leads the ADEPT research platform integrating health intelligence and brain-inspired technologies across multiple faculties. Education details are not explicitly listed in the provided texts, but his academic roles imply advanced credentials in biomedical engineering. His research spans interdisciplinary domains including neurotechnology, wearable sensors, and clinical applications of brain monitoring. Over 70 publications demonstrate expertise in fNIRS signal processing, neuromorphic computing, and user-centered biomedical design. Professional networks include active Twitter (@PMirtaheri) and LinkedIn profiles. Current projects emphasize translational research and ethical design considerations in neurotechnology. His work bridges engineering, health sciences, and arts through collaborative platforms like ADEPT, addressing both technical innovation and societal impact.

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Fei WangView profile

Professor

University of TennesseeUnited States

Fei Wang is a Professor and Condra Chair of Excellence in Power Electronics at the University of Tennessee, Knoxville (UTK), affiliated with the Tickle College of Engineering and the Min H. Kao Department of Electrical Engineering and Computer Science. He serves as Technical Director of CURENT and holds a joint appointment at Oak Ridge National Lab. His expertise spans power electronics converters, motor drives, wide bandgap devices, and renewable energy systems. Education: B.S. in Electrical Engineering, Xi’an Jiaotong University, 1982 M.S. and Ph.D. in Electrical Engineering, University of Southern California, 1985 and 1990 Research Interests: Focuses on design, modeling, and control of advanced power electronics systems, including grid integration of renewable energy, electric vehicle drivetrains, and wide bandgap semiconductor applications. He has authored over 500 publications and holds 20 patents, with funding exceeding $65M and personal share over $18M. Key Contributions: Developed three-level NPC medium voltage drives at GE Co-founded CURENT and led its technical strategy Recipient of IEEE IAS Gerald Kliman Innovator Award (2018), Dushman Award (1998), and multiple research excellence awards Grants & Advising: Supervised 13 Ph.D. and 8 M.S. students, advised postdocs, and hosted over 35 visiting scholars. Active in IEEE standards development and editorial roles. Labs & Teams: Leads the CURENT Engineering Research Center, focusing on ultra-wide-area power grid resilience through advanced power electronics and system integration.

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Tayfun Efe ErtopView profile

Assistant Professor

University of TennesseeUnited States

Tayfun Efe Ertop is an Assistant Professor in the Department of Mechanical, Aerospace and Biomedical Engineering at the University of Tennessee, Knoxville. He previously held roles including Research Assistant Professor at Vanderbilt University (2023-2024), and Graduate Research Assistant roles at Vanderbilt and Middle East Technical University (2017-2023). His research focuses on soft and continuum robots, surgical robotics, bio-inspired systems, and advanced control methods. Education: PhD in Mechanical Engineering, Vanderbilt University (2023) MS in Mechanical Engineering, Middle East Technical University (2017) BS in Mechanical Engineering, Middle East Technical University (2014) Research Interests: Dr. Ertop develops robotic solutions for minimally invasive surgery, including steerable needles, continuum robots, and bio-inspired actuators. His work emphasizes sensor integration, trajectory control, and material innovation for surgical applications. Recent projects involve phase-changing metallic spines for stiffness modulation and virtual reality frameworks for surgical robot evaluation. Awards: Best Presentation Award at VISE Annual Symposium (2020) Best Paper Finalist at ASME Dynamic Systems Conference (2020) Engineering Graduate Fellowship (Vanderbilt University, 2017-2018) TUBITAK Graduate Fellowship (2014-2017) Advising & Grants: As faculty advisor, he mentors graduate students in surgical robotics and continuum mechanics. His work is supported by grants from IEEE and ASME memberships, with recent funding enabling advancements in thermoelectric manipulators and steerable needle technologies. He collaborates with labs like the MABE Maker Lab and Syndaver Lab for experimental validation. Labs & Teams: Active in the University's robotics and biomedical engineering research groups, contributing to interdisciplinary projects at the Tickle College of Engineering.

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Antonio Rubio SoláView profile

Professor

Polytechnic University of CataloniaSpain

Antonio Rubio Solá is a Full Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the High Performance Integrated Circuits and Systems Design (HIPICS) group. He holds an M.S. in Industrial Engineering (1977) and a Ph.D. in Electronic Engineering (1982), both from UPC. His research focuses on semiconductor technology evolution, integrated circuit design, and memristor-based neuromorphic systems. Key interests include nanoelectronics, energy-efficient computing, and biomimetic circuits. Rubio has contributed to advancements in memristive logic, graphene nanoribbon devices, and fault-tolerant circuit architectures. His work bridges theoretical research and practical implementation, with notable contributions in neuromorphic hardware, in-memory computing, and radiation-hardened electronics. Recent publications emphasize memristor applications in biological systems emulation, stochastic resonance phenomena, and energy-efficient data processing. Rubio actively participates in Spain’s neuromorphic technology initiatives and promotes sustainable microelectronics education through digital tools. Publications are accessible via UPC FenixDoc and the HIPICS e-prints repository. His research is driven by interdisciplinary collaboration, addressing challenges in next-generation computing paradigms and emerging technologies.

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Andrew SingerView profile

Professor

Stony Brook UniversityUnited States

Andrew Singer is the Dean of the College of Engineering and Applied Sciences and a Professor in the Department of Electrical and Computer Engineering at Stony Brook University. Previously, he held roles at the Grainger College of Engineering, University of Illinois Urbana-Champaign, including positions as Associate Dean for Innovation and Entrepreneurship. His research spans signal processing, underwater acoustic communications, biomedical acoustics, and entrepreneurship. He leads projects like the MAGIC Automated Acoustics Laboratory and Augmented Listening Technology, focusing on audio signal enhancement, wearable devices, and underwater communication systems. Research interests include adaptive signal processing, turbo equalization, and biomedical applications of acoustics. Notable contributions include high-data-rate ultrasonic communication through biological tissues and real-time video streaming using acoustic channels. His work integrates machine learning and physical models to address challenges in acoustics, communications, and biomedical engineering. Recent articles explore reliable measurement in unreliable systems, underwater source localization, and bio-inspired signal processing techniques. Awards and recognitions are not explicitly listed but his extensive publications and leadership roles highlight his contributions to the field. Advised students and collaborators span academia and industry, including roles at Apple, Amazon, and defense agencies. Current initiatives include developing mechatronic systems for acoustic research and advancing assistive listening technologies.

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Wilfred van der WielView profile

Professor

University of TwenteNetherlands

Prof. Dr. Ir. Wilfred van der Wiel is a full professor of Nanoelectronics at the University of Twente and director of the BRAINS Center for Brain-Inspired Nano Systems . He also holds a second professorship at the Institute of Physics, Westfälische Wilhelms-Universität Münster and serves as a visiting professor there. His research focuses on unconventional electronics for energy-efficient information processing , pioneering Material Learning at the nanoscale to realize computational functionality and artificial intelligence in designless nanomaterial substrates. Education : MSc and PhD in Applied Physics (cum laude) from Delft University of Technology (1997, 2002). Research : Intersects nanotechnology , physics , computer science , and neuroscience , developing artificial neural networks in materials . Grants & Awards : ERC Starting Grant (2009) World Economic Forum Outstanding Young Scientist Award (2013) EIC Pathfinder HYBRAIN (2022-2027) Take-off Grant (2020) Collaborations : Co-founded spin-off ECsens Initiated intensified collaboration with University of Münster International advisor for WISE-SSS program , Tokyo Institute of Technology

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Mark HumphrysView profile

Assistant Professor

Dublin City UniversityIreland

Dr. Mark Humphrys is an Assistant Professor at Dublin City University's School of Computing within the Faculty of Engineering and Computing. He holds a BSc in Mathematics and Computer Science from University College Dublin, a PhD in Computer Science from the University of Cambridge, and completed postdoctoral work at the University of Edinburgh. His research spans Artificial Intelligence, Reinforcement Learning, JavaScript-based educational platforms, and multi-agent systems. His research focuses on: Action selection methods in autonomous agents Reinforcement learning architectures JavaScript-based AI education platforms (Ancient Brain) Multi-author hybrid AI systems Turing Test implementations Urban mobility and transportation modeling Analysis of his recent publications reveals strong emphasis on: Educational technology innovations using JavaScript frameworks Financial market impacts on labor economics Distributed AI system architectures Urban transportation solutions and predictive modeling Human-computer interaction paradigms He has supervised 4 PhD students to completion and maintains the Ancient Brain coding platform hosting over 11,000 user projects. His work has received 686 citations with an h-index of 11. Dr. Humphrys leads several projects including Ancient Brain (JavaScript coding education), World-Wide-Mind (distributed AI research), and maintains research groups exploring multi-agent systems and transportation analytics.

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Nina FeffermanView profile

Professor

University of TennesseeUnited States

Nina Fefferman is a Professor in the Departments of Ecology and Evolutionary Biology and Mathematics at the University of Tennessee, Knoxville. Her research focuses on applying mathematical modeling to understand complex systems, including epidemiology, evolutionary biology, and conservation. She holds a Ph.D. from Tufts University and is affiliated with the College of Arts and Sciences. Her work bridges theoretical and applied research, addressing challenges in disease dynamics, biosecurity, and social behavior. Current projects include developing models for outbreak detection, understanding the evolution of social systems, and creating tools for wildlife conservation. Fefferman collaborates with interdisciplinary teams to explore topics such as distributed anomaly detection algorithms and the impact of human behavior on disease spread. Fefferman’s research has been supported by grants from NSF, NIH, USDA, and other agencies. She advises multiple graduate students and postdoctoral researchers, fostering a collaborative lab environment. Her lab’s work has been featured in media outlets like The Washington Post, BBC, and TEDx. Key areas of focus include: Epidemiology & Biosecurity: Modeling disease transmission and intervention strategies. Evolutionary Sociobiology: Investigating self-organizing social systems and their resilience to threats. Conservation Biology: Developing tools to mitigate extinction risks and invasive species threats. Bio-Inspired Algorithms: Designing algorithms based on biological principles for cyber-security and anomaly detection. Her publications span high-impact journals such as Philosophical Transactions of the Royal Society, PLoS Neglected Tropical Diseases, and Nature Climate Change. Ongoing efforts include exploring the role of social learning in health behaviors and the integration of human-environment interactions in climate models.

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