Smart Nano NI Researchers Group
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Dr Fatemeh Moradiani, Research Fellow, QUB
Fatemeh holds a PhD in electrical engineering with academic expertise in integrated photonic devices, including modulators, lasers, and filters. She has industry experience in LED and Integrated Circuit (IC) packaging, as well as photonics device packaging. Her experimental skills encompass the fabrication of photonic devices using techniques like direct writing lithography and electron beam lithography (EBL), alongside designing and building experimental setups for research and development.
Fatemeh is proficient in software tools such as LabVIEW, Python, MATLAB, and FDTD Lumerical. Currently, her work at Smart Nano focuses on quantum technology, particularly in the fabrication and characterization of single-photon sources, quantum sensing, and integrated photonic-microfluidic chips. Her interests lie in quantum technology and integrated photonics chips. She has recently published on ‘Strip-loaded nanophotonic interfaces for resonant coupling and single-photon routing’ (Snow et al., Front. Phys., 2024), and ‘Tailoring performance through loss engineering in ring-waveguide lasers for enhanced Single-Mode lasing’ (Arvanagh et al., Opt. Laser Technol., 2025).
Mike is an interdisciplinary scientist who works in spectroscopy for various applications. His background in Physics with a BSc and PhD from Queen’s University Belfast – specifically, optics/photonics, plasmonics, and condensed matter physics. More recently, he has been working on machine learning techniques and the development of portable devices to complement his spectroscopy work. Mike’s spectroscopy research is chiefly with Raman and surface enhanced Raman spectroscopy (SERS) but he has also worked in UV-visible, infrared, fluorescence and x-ray fluorescence (XRF).
His current Smart Nano interests are in 3D printing for rapid device prototyping, hyperspectral imaging, the miniaturisation of Raman spectroscopy systems, novel quality control methods for sensor development – specifically nanoimprinted lithography plasmonic sensors. He is passionate about collaboration across the sciences and has been liaising with Queen’s Health Sciences Department in relation to emerging optical methods for breast cancer assessments, of interest to Smart Nano partner company, Cirdan Imaging. He has also been collaborating with colleagues in the School of Chemical Engineering at the University of Birmingham on Raman spectroscopy, and works closely with the Photonic Integration and Advanced Data Storage (PIADS) Centre for Doctoral Training, in conjunction with the University of Glasgow.
Dr Mike Hardy, Research Fellow, QUB
Natan Kuninski, PhD Researcher, QUB.
Natan is a PhD Candidate in the group of Professor Robert M. Bowman, studying all-optical switching (AOS) in synthetic ferrimagnets. Since AOS is not yet well understood, his research focuses on characterising materials to help determine why it might occur. Natan’s primary techniques include broadband ferromagnetic resonance (FMR) to measure dynamic magnetic properties such as Gilbert damping and the gyromagnetic ratio, and vibrating sample magnetometry (VSM) to determine static properties like magnetic saturation (Ms) and coercivity. He is particularly interested in magnetic ferrites with perpendicular magnetic anisotropy (PMA), such as cobalt ferrite, which are promising for AOS applications.
As part of Natan’s work, he has been collaborating with the Smart Nano NI laboratory to 3D print waveguide holders that secures the waveguide between two magnetic poles, enabling precise characterisation of Gilbert damping in the perpendicular direction. The holder must be nonmagnetic for accurate measurements and mechanically stable to support the tightening of coaxial cable connections in a perpendicular direction. Smart Nano NI provides access to a variety of 3D printing materials, allowing optimisation for both structural integrity and a low dielectric constant—essential for FMR experiments that rely on microwave excitation.
By integrating advanced characterisation techniques with custom 3D-printed components, Natan’s research aims to deepen our understanding of AOS and contribute to the development of novel magnetic materials with tuneable properties.
Natan was the recipient of the 2024 John Geddes Physics Prize for best MSci performance at Queen’s University Physics Department.
Yessenia’s research focuses on advancing computational imaging and optical systems, particularly in imaging through complex media. Recently, she has represented Smart Nano NI at the International Thematic School, ‘Waves in Complex Media from Theory to Practice’ organised by la Société Française d’Optique (Les Houches, France), and as a panel member for the Research Synergies and Knowledge Transfer in Science and Technology theme at the First Mexico-UK Interdisciplinary Congress (London).
Throughout her professional career, she has developed extensive knowledge and expertise in optics, imaging through scattering media, Fourier optics, imaging systems, optical devices, and numerical analysis. Her work has been published in prestigious journals, including Optics Letters and Nature Communications. Yessenia is a keen artist and featured as a top cover candidate for the special issue ‘Optics in 2023’ of Optica (formerly OSA). In addition, she won 1st Prize in the 2024 Smart Nano Photography Competition for her photo on multi-coloured polarisation effects in thin films. Yessenia is a STEM Ambassador in both the UK and Mexico.
Dr Yessenia Jauregui-Sánchez, Research Fellow, QUB.
Dr Arthur Lipinski, Research Fellow, QUB.
Arthur gained his BSc in Physics with Astronomy at Dublin City University (DCU). During that time, he completed an internship in a Biomedical Diagnostics Institute (BDI) where I worked on design, manufacture and testing of lab-on-a-chip microfluidic devices. Following this, he attained a PhD from Queen’s University Belfast Physics Department, in the Photonic Integration and Advanced Data Storage (PIADS) Centre for Doctoral Training under Professor Robert M. Bowman, with a thesis, ‘Synthesis, characterisation, and spectral metrology of plasmonic titanium nitride films and nanostructures’.
Arthur’s skills and expertise involve fabricating thin plasmonic films using ultrahigh vacuum (UHV) DC Magnetron Sputtering, alongside the design, fabrication, characterisation and optimisation of plasmonic nanostructures using electron beam lithography (EBL). He has extensive experience in optical and structural characterisation of thin films using ellipsometry, attenuated total reflection (ATR), dark field spectroscopy, scanning electron microscopy (SEM) and x-ray diffraction (XRD). He has designed and constructed optical setups using supercontinuum lasers.
Arthur has recently published on the topic of ‘Synthesis of Plasmonically Active Titanium Nitride Using a Metallic Alloy Buffer Layer Strategy’ (Lipinski et al., ACS Appl. Electron. Mater., 2023).
Briliant’s research focuses on advancing photonic device development and fabrication techniques to enhance light management and sensing capabilities. He is currently pioneering a rapid and scalable approach for integrating freeform micro-lenses onto fibre optics using two-photon polymerisation, with applications spanning optical communication, photonic sensing, micro-imaging probes, and photonic chips. His work plays a crucial role in advancing digital manufacturing and sensing technologies, aligning with the consortium’s mission to translate cutting-edge research into commercially viable solutions.
Previously, he was a researcher at the International Iberian Nanotechnology Laboratory (INL) in Portugal, where he worked on magnetoresistive biosensors for stroke screening and sensor fabrication in a high-tech cleanroom environment. He collaborated with industrial partners on front-end production, gaining expertise in photolithography and wafer-scale device fabrication. He holds a Master’s degree in Industrial Semiconductor Technology from Asia University, Taiwan, where he collaborated with Taiwan Semiconductor Manufacturing Company (TSMC), and a PhD from Chang Gung University, Taiwan, specialising in biosensing photonic devices, which led to two granted patents. With a strong background in both industry and academia, he actively contributes to Smart Nano NI’s efforts in developing scalable and commercially ready nanotechnology solutions.
Briliant recently presented at the 50th International Micro and Nano Engineering Conference (MNE 2024), in Montpellier, France on ‘Direct Fabrication and 3D Alignment of Perpendicular Freeform Micro-Lenses on Fibre Optic Tips’ (Prabowo et al., 2024).
Dr Briliant A. Prabowo, Research Fellow, QUB
Dr Ranjeet Kumar, Research Fellow, QUB.
Ranjeet earned his PhD from the Indian Institute of Technology Delhi in optical trapping, followed by five years teaching at Hindu College, University of Delhi. Since then, he has worked as a postdoctoral researcher in the UK at Imperial College, St. Andrews, and the University of Bath in the areas of non-linear microscopy, light-sheet fluorescence microscopy for drug-screening, development of multispectral fluorescence-based hand-held devices for rapid detection of synthetic cannabinoids, and an endoscope for label-free blood-flow imaging in anastomotic leaks detection for keyhole surgeries. Currently, he is involved in the development of a multispectral imaging device in conjunction with Smart Nano NI partner company, Causeway Sensors Ltd.
He is also interested in on-chip spectroscopy and programmable integrated photonic systems and in his spare time Ranjeet is a keen sportsman and loves nature.
Ranjeet’s work has recently been featured extensively online, for e.g.: University of Bath, ‘Portable device instantly detects illegal drugs with 95% accuracy’. Phys.org (2023) [Online] https://phys.org/news/2023-09-portable-device-instantly-illegal-drugs.html
Arran completed his undergraduate degree in Applied Maths and Physics at Queen’s University Belfast. His MSci thesis was on the energy transfer and thermodynamics of collisions between atoms in an open quantum system and its environment. He began his PhD in November 2024 in the group of Dr Hamidreza Siampour in the Smart Nano Single Photon Laboratory, looking at optimisation of defect centres in hexagonal boron nitride (hBN) through their characterisation. This is done in order to enhance the emission of indistinguishable single photons from photonic devices containing hBN. Outside of academic life, Arran have a keen interest for football and rugby, he is an avid Chelsea and Ulster Rugby fan. He is also a big fan Eurovision Song Contest and even has his own podcast dedicated to all things Eurovision!
Arran Ashfield, PhD Researcher, QUB.
Dr Breandán Hill, Senior R&D Manager, Causeway Sensors Ltd.
Breandán completed his undergraduate in Physics at Trinity College Dublin in 2008 before moving to Queen’s University Belfast to earn a PhD in 2014. He is a founding employee at Causeway Sensors Limited. Breandán’s PhD and research forms a large part of the company’s core intellectual property and products. He leads many of the company’s research and development projects, including design and manufacture of Causeway’s new commercial biosensor, TITAN.
Breandán has 14 years of industrial experience in R&D and product development having worked on a huge range of projects including nanofabrication, optics, modelling, software development, biochemistry, 3D design, manufacturing, and electronics.
In collaboration with Smart Nano NI, Breandán is currently working on several interesting projects, including the development of novel manufacturing solutions using 3D printing and the characterisation of nanostructures using hyperspectral imaging.
Causeway Sensors Ltd. TITAN: Your dedicated tool for real-time, at-line titre analysis https://www.causewaysensors.com/titan
Pooja completed her PhD in South Korea, developing a biosensing platform for preclinical drug screening to detect changes in cardiac electrical and mechanical activities. She hails from a multidisciplinary background, starting with B. Tech in Electronics engineering, M. Tech in energy systems and PhD in mechanical engineering. She is passionate about developing physical biosensors and bioelectronic devices. At Smart Nano, she is currently working on a polymer-based biosensor for toxicity screening. She has published extensively in microelectromechanical sensors (MEMS) for bio-applications, including recently, ‘Cardiotoxicity Assessment through a Polymer‐Based Cantilever Platform: An Integrated Electro‐Mechanical Screening Approach’ (PP Kanade et al., Small, 2024), and ‘Graphene SU-8 Platform for Enhanced Cardiomyocyte Maturation and Intercellular Communication in Cardiac Drug Screening’ (Li et al., ACS Nano, 2024)
Dr Pooja Kanade, Research Fellow, QUB
Ata possesses a strong foundation in the manipulation of electromagnetic waves through the utilisation of metasurfaces (subwavelength structures), with expertise in the design, simulation, and realization of advanced photonic devices. His ongoing research at Smart Nano is focused on the theoretical modelling of multilayer metasurfaces, investigating their potential applications in dynamic beam shaping, optical communication, and sensing technologies. With an extensive experience in high-frequency simulations (CST, and Lumerical), he is playing his role in advanced wavefront control focusing on the development of innovative solutions that integrate fundamental scientific principles with practical applications in the real world.
Dr Ata Ur Rahman Khalid, Research Fellow, QUB.
Dr M M Manjurul Islam, Postdoctoral Research Associate, Ulster University
Manjurul’s research focuses on artificial intelligence, industrial automation, and smart manufacturing, developing AI-driven models to enhance manufacturing efficiency and reliability, especially in semiconductor production. At the Smart Nano NI Consortium, his current research integrates dynamic modelling, machine learning, computer vision, and digital twins to optimize processes and apply advanced AI research. He actively collaborates with Smart Nano NI partner companies, such as Seagate Technology, to address real-world industrial challenges. Recently, he authored a paper titled "Efficient Wafer Defect Pattern Recognition Using Deep Convolutional Neural Networks," presented at the 2023 IEEE Conference on Artificial Intelligence (CAI), USA.
Previously, Manjurul was a Postdoctoral Researcher at the Digital Industry Center, Fondazione Bruno Kessler in Italy, where he focused on diagnostics and prognostics tools development for smart manufacturing systems. He also served as an Assistant Professor at American International University-Bangladesh, teaching and conducting research in AI and machine learning. He holds a PhD from the University of Ulsan, South Korea, where his work on fault diagnosis and prognosis, using signal processing and AI, significantly improved the safety of industrial equipment. He has received several awards, including the Brain Korea 21 research grant, and actively contributes to international research through publications and presentations.
Mohammad Sharifur Rahman, PhD Researcher
Ulster University | AI in Smart Semiconductor Manufacturing
Mohammad Sharifur Rahman is a PhD researcher at Ulster University, specializing in applying artificial intelligence in smart semiconductor manufacturing. His research integrates nanotechnology, Industry 4.0, and digital twin technologies to optimize manufacturing processes, aiming to enhance efficiency, reduce operational costs, and improve production quality. His work advances AI-driven automation in semiconductor fabrication, aligning with the next generation of intelligent manufacturing systems.
With over 16 years of professional experience, Mohammad has led large-scale projects in the telecommunications industry in Southeast Asian countries, including deploying Thailand’s and Bangladesh’s first 4G network, 2G and 3G network in Bhutan and Bangladesh while serving as Head of RF Planning and Optimization at Huawei Technologies. His expertise in network optimization, data analytics, and system automation translates seamlessly into his research on AI-driven process improvements in manufacturing.
Academically, Mohammad holds an MSc in Data Science (Distinction) from Ulster University, an MSc in Computer Science (Highest CGPA, Vice Chancellor’s Award), an MBA in Banking & Finance, and a BSc in Computer Engineering. His interdisciplinary background equips him with a strong foundation in AI, machine learning, and advanced computing.
His research has also significantly contributed to healthcare, including AI-powered models for diabetic retinopathy and Alzheimer’s disease detection. His work has been published in leading AI and machine learning proceedings.
Through his research at Ulster University and Smart Nano NI, Mohammad aims to drive innovation in semiconductor manufacturing by harnessing AI and emerging digital technologies.
Sanjoy is currently pursuing his PhD at Ulster University, with a research focus on equipment condition monitoring and anomaly detection through the identification of irregular behaviour in manufacturing systems. His primary objective is to develop an automated health monitoring framework for bearings, cryogenic pumps, and other steady-state operating equipment within the semiconductor manufacturing process. In addition, his research explores tool and equipment matching opportunities by fingerprinting optimal operating conditions and modelling them against current performance data.
He holds both a master’s and a bachelor’s degree from the University of Rajshahi, Bangladesh. His Master’s research focused on EEG signal processing.
Sanjoy was recently selected to participate in the Doctoral Symposium at the 16th Annual Conference of the PHM Society in Nashville, USA, where he presented his work titled ‘A Two-Step Framework for Predictive Maintenance of Cryogenic Pumps in Semiconductor Manufacturing(2024)’ and awarded sponsorship by the conference.
Sanjoy Kumar Saha, PhD Researcher, University of Ulster
Muhammad Rashid Rasheed is a PhD researcher at Ulster University specialising in Anomaly Detection for Smart Manufacturing, focusing on semiconductor wafer defect identification. His research develops machine learning and computer vision solutions combining supervised and unsupervised approaches to detect microscopic flaws in real-time. Using supervised methods for known defects and unsupervised techniques for novel anomalies, his work enhances quality control in precision manufacturing. In collaboration with Seagate Technology, he implements these systems for industrial manufacturing, improving quality assurance in data storage production. His real-time visual inspection systems integrate deep learning with production automation to reduce defects and optimise efficiency (Rasheed et al., 2024).
Muhammad Rashid holds a master’s degree from Tiangong University's School of Computer Science and Technology, specialising in Machine Learning and Computer Vision.
Muhammad Rashid Rasheed, Ulster University
Yasir Ijaz, PhD Researcher, Ulster University
Yasir Ijaz’s research with Ulster University Research & Innovation and Seagate Technology focuses on developing cutting-edge image analytics solutions to address material handling challenges in industrial environments. His current work with Smart Nano NI involves a rigorous evaluation of object detection methods to accurately assess the physical state of equipment load locks, enhancing the safety and reliability of loading operations. This forward-thinking research aims to replace traditional physical and electronic tool interlocks with a sophisticated, software-defined interlock system.
Yasir brings extensive experience in industrial applications, particularly in the textile sector. During his master's studies, he focused on textile fabric defect detection during the production process—developing computer vision-based approaches to identify anomalies, significantly improving quality control and reducing waste. This work deepened his expertise in deploying image processing techniques within high-speed manufacturing settings and laid a strong foundation for his current research.
He thrives in innovative environments where he can pursue applied research, devise intelligent solutions, and collaborate closely through his dynamic PhD work at Ulster University and with the Smart Nano NI team. Smart Nano NI continues to nurture and expand talent within the photonics sector.