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Ken MaiView profile

Research Professor

• High-Performance Circuit Design
• Secure IC Design
• Radiation Hardening
• +4 more

Ken Mai is a Principal Systems Scientist in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.S., M.S., and Ph.D. in Electrical Engineering from Stanford University. His research focuses on high-performance circuit design, secure IC design, radiation hardening, reconfigurable computing, and computer architecture. He has received prestigious awards including the NSF CAREER Award and the George Tallman Ladd Research Award. Education: Ph.D., Electrical Engineering, Stanford University, 2005 M.S., Electrical Engineering, Stanford University, 1997 B.S., Electrical Engineering, Stanford University, 1993 Research Interests: Dr. Mai’s work addresses challenges in nanometer-scale CMOS technology, including interconnect delay, leakage, and soft errors. His projects include secure IC design against hardware attacks, robust memory techniques using digital communications, 100GHz logic via cryogenic cooling, and bio-implantable computing platforms. He collaborates with neurosurgeons at the University of Pittsburgh for medical applications. Key Projects: Secure IC Design: Countermeasures against invasive/non-invasive attacks Robust Memory Design: Error correction codes for resilience 100GHz Logic: Cryogenically cooled CMOS for high-speed applications Bio-Implantable Systems: Low-power, high-density computing for medical devices Awards: NSF CAREER Award George Tallman Ladd Research Award Eta Kappa Nu Excellence in Teaching Award Teaching and Advising: He teaches courses like 18-322 (Digital Circuits), 18-617 (Memory Systems), and advises students including Mudit Bhargava and Mark McCartney. His lab, the VLSI Design Group, develops tools and methodologies linking circuit design to architectural design. Contact: Email: kenmai@ece.cmu.edu Website: Carnegie Mellon VLSI Design Group

Claire AdjimanView profile

Professor

• Process Design
• Molecular Engineering
• Thermodynamics
• +5 more

Claire Adjiman is a Professor of Chemical Engineering at Imperial College London, affiliated with the Faculty of Engineering and the Department of Chemical Engineering. She holds an MEng from Imperial College London and a PhD from Princeton University. Her research focuses on integrating molecular-level decisions into process design, emphasizing multiscale process and molecular/materials design, property prediction, and optimization algorithms. She collaborates extensively with industries such as oil and gas, pharmaceuticals, and agrochemicals, and has licensed thermodynamic modeling software. Adjiman directs the Sargent Centre for Process Systems Engineering and serves as Editor-in-Chief of the RSC-IChemE journal MSDE. Adjiman's work bridges molecular-level decisions with process design, addressing limitations in traditional sequential decision-making. Her methodologies aim to enhance process economics and sustainability by expanding design spaces through computational tools. Key affiliations include the Agri Futures Lab, Centre for Advanced Therapeutics, and the Institute for Molecular Science and Engineering. Her research spans topics like solvent design for pharmaceutical processes, CO 2 capture technologies, and crystal structure prediction. She emphasizes holistic approaches to reduce environmental impact and improve material/energy efficiency. Recent projects include the HiRECORD initiative for scalable CO 2 capture systems and the development of predictive models for drug manufacturing processes. Adjiman's contributions to computational methods, including the SAFT-γ Mie equation of state and optimization algorithms, underpin her work in advancing sustainable industrial processes. Her lab's innovations aim to transform traditional manufacturing practices through data-driven and integrated design strategies.

Tom EllisView profile

Professor

• Synthetic Biology
• Synthetic Genomics
• Engineered Living Materials
• +6 more

Tom Ellis is a Professor of Synthetic Genome Engineering at Imperial College London's Department of Bioengineering, part of the Faculty of Engineering. He leads the Ellis Lab, focusing on synthetic biology and engineered living materials. His research includes developing foundational tools for synthetic genomics, with a focus on yeast and bacterial cellulose-based materials. He has pioneered Engineered Living Materials (ELMs), including self-pigmenting microbial leather and bioengineered textiles. Background: Ellis earned his PhD from the University of Cambridge in 2004, followed by postdoctoral work at Boston University under Jim Collins. He has held academic roles at the University of Cambridge and Imperial College, where he now co-leads synthetic biology education. Research Interests: Synthetic genomics, engineered living materials, genome engineering, DNA sequence function, and bio-based material production. His lab collaborates with industry partners like Modern Synthesis to advance sustainable materials. Awards: Multiple teaching awards, including recognition for supervision of iGEM teams. Lab Affiliations: Ellis Lab, Centre for Synthetic Biology, Synthetic Biology Hub, and Industrial Biotechnology Hub. Active in UK and international projects like the Sc2.0 synthetic yeast consortium. Recent Work: Development of self-dyeing bacterial cellulose textiles (Nature Biotechnology 2025), optogenetic patterning of materials, and modular yeast genome design.

Zubair Abdullah-VetterView profile

Research Fellow

• Machine Learning
• Renewable Energy Engineering
• Solar Cell Technology
• +3 more

Dr. Zubair Abdullah-Vetter is a Research Fellow at the University of New South Wales (UNSW) , affiliated with the College of Engineering and the Photovoltaic and Renewable Energy Engineering department. His work focuses on integrating advanced machine learning techniques with photovoltaic device analysis to enhance solar energy system quality and reliability. PhD in Photovoltaic Engineering Specializes in AI-driven solar cell diagnostics Active in both journal publications and conference presentations Research interests center on machine learning for renewable energy systems , particularly: Deep learning for defect analysis in solar cells Predictive modeling of photovoltaic degradation Accelerated testing protocols using AI Quantum efficiency measurement automation Luminescence image interpretation Time-series analysis of PV performance Recent publications demonstrate expertise in applying neural networks and regression techniques to photovoltaic diagnostics. The work has significant implications for climate change mitigation through improved solar technology efficiency. Scientific recognition includes: BT Imaging Photovoltaic Thesis Prize (2020) Best Poster Award at IEEE PVSC (2022) ACAP Best Student Paper Award (2024) Collaborates with leading researchers in photovoltaic materials and device reliability while contributing to practical applications in Australian solar infrastructure projects.

Michael Xianfeng ChenView profile

Professor

• Biomaterials
• Biomedical Engineering
• Nanomedicine
• +8 more

Prof. Michael Xianfeng Chen is a Personal Chair of Therapeutic Engineering and Director of Industry Engagement at the School of Engineering, University of Edinburgh. He leads the Institute for Bioengineering, focusing on biomaterials, biomedical engineering, and nanomedicine. His research emphasizes drug delivery systems, microneedle technologies, and microfluidics, with significant contributions to vaccine delivery and nanotechnology-based therapies. Education: DPhil in Materials Science, University of Oxford MSc in Chemistry, National University of Singapore Research Interests: Prof. Chen’s work spans advanced drug delivery systems, antibacterial coatings, biodegradable nanomedicine, and cancer therapy. He pioneers technologies like diamond nanoneedle arrays and programmable optical window bonding for microfluidic devices. His inventions have led to patents and industry collaborations, notably with Vaxxas for microneedle vaccine platforms. Grants & Awards: Funding from MRC, EPSRC, Cancer Research UK, and industry partners Listed as a top 2% global scientist (2021–2024) 12 granted patents and 15 patent applications Advising & Outreach: Prof. Chen supervises PhD students and postdocs, offering scholarships through the University of Edinburgh and international programs. He actively engages in scientific community service, reviewing for top journals and serving as an associate editor for IET Nanobiotechnology. Labs & Teams: His research group focuses on bioengineering and nanomedicine, with projects ranging from hydrogel formulations to biosensor development. Collaborations span academia and industry, addressing challenges in drug delivery and medical diagnostics.

Anne AndrewsView profile

Professor

• Neurochemical Sensing
• Biosensor Development
• Neuropsychopharmacology
• +2 more

Professor Anne Andrews holds joint appointments in Chemistry & Biochemistry and Psychiatry & Biobehavioral Sciences at UCLA. She leads research in neurochemical sensing, developing implantable biosensors for real-time neurotransmitter monitoring. Her innovations include aptamer-based field-effect transistors for serotonin/dopamine detection and wearable cortisol trackers. Her laboratory advances flexible electronics for neurological applications, combining nanotechnology with machine learning to optimize neurochemical detection. Recent work establishes serotonin's role in stress response circuitry and examines pharmacological interventions during pregnancy. Honors include NSF's PECASE Award and fellowships in biomedical engineering. She currently advises six doctoral candidates and maintains NIH-funded projects on molecular sensing platforms and neuropharmacology.

Michael BruenigView profile

Professor

• Robotics
• Cybersecurity
• Data Innovation
• +6 more

Professor Michael Bruenig is the Head of School for the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ), a position he has held since 2016, with an interim role as Head of UQ’s Business School from 2019–2021. He previously led the CSIRO’s $140m National Research Flagship on Digital Productivity and co-founded Data61. With a PhD from RWTH Aachen University, his career spans automotive R&D in Germany, Silicon Valley, and Australia. He holds a Master’s and PhD in Science from RWTH Aachen University, Germany. His research focuses on strategic innovation, entrepreneurship, and translating research into industry impact through ventures like UQ Cyber, the National Industry 4.0 Energy Testlab, and the QLD Government AI Hub. He pioneered UQ’s Bachelor of Computer Science, Master of Cyber Security (based on US NICE Framework), and online Master of Business Analytics. His work spans robotics, sensor networks, and terahertz technology, with recent articles addressing lidar-based navigation, terahertz imaging, and cybersecurity. He advises startups and sits on boards, driving commercialization and spin-offs. Key initiatives include UQ Innovate and UQ Ventures, fostering student and faculty entrepreneurship. Labs and teams include collaborations on AI, Industry 4.0, and energy systems. His leadership emphasizes cross-disciplinary projects and curriculum innovation in tech and data fields.

• Biomedical Engineering
• Microfluidics
• Biosensors
• +3 more

A K M Arifuzzman is a Research Fellow at the School of Electrical and Computer Engineering, Georgia Institute of Technology. His research focuses on developing microfluidic and biosensor technologies for high-throughput cell analysis and biomedical diagnostics. He specializes in integrating electronic detection systems with microfluidic devices to enable label-free, real-time cellular phenotyping and mechanophenotyping. Key research themes include: Design of multiplexed impedance sensors for cell stiffness measurement Automated lightless cytometry using immunomagnetic manipulation Electronic antibody microarrays for combinatorial immunophenotyping Development of lab-on-a-chip systems for point-of-care diagnostics His recent work emphasizes high-throughput approaches for immune cell analysis, leukocyte differential counting, and cellular antigen expression profiling. The 2023-2025 publications highlight advancements in microfluidic constrictions, automated microchip systems, and multimodal electronic phenotyping techniques. His sensor innovations address critical challenges in biomedical engineering, particularly in miniaturization, sensitivity, and automation of diagnostic tools. Notable contributions include the creation of label-free electronic detection platforms and adaptive immunomagnetic manipulation systems. His research bridges electrical engineering, microfluidics, and biomedical applications, with particular emphasis on translating lab-scale technologies into practical clinical solutions.

Apurva Ratan MurtyView profile

Assistant Professor

• Visual Intelligence
• Neurodevelopmental Disorders
• fMRI
• +4 more

Apurva Ratan Murty is an Assistant Professor at the School of Psychology, Georgia Institute of Technology. His research focuses on uncovering neural codes and algorithms underlying human vision by integrating biological studies with artificial intelligence models. The Murty Lab employs advanced neuroimaging techniques (fMRI, MEG, EEG) and computational methods (deep learning, generative AI) to explore perceptual development, neurodevelopmental disorders, and invariant object representations. He holds a PhD from the Indian Institute of Science (IISc) and completed postdoctoral research at MIT's McGovern Institute. Education: PhD in Neuroscience, Indian Institute of Science (IISc), Bangalore, India (Adviser: S.P. Arun) Postdoctoral Research: MIT's Center for Brains, Minds, and Machines (Advisers: Nancy Kanwisher, James DiCarlo) Research Interests: The lab investigates how visual information transforms into perception through neural circuits, emphasizing cross-disciplinary approaches to bridge biological and artificial vision systems. Key themes include modeling neurodevelopmental disorders, analyzing fMRI data with AI, and developing biologically constrained computational frameworks. Awards: NIH K99/R00 Pathway to Independence Award Young Systems Scientist Award, National Systems Society of India Institute Medal, Indian Institute of Science Labs & Teams: The Murty Lab actively recruits PhD students, postdocs, and undergraduates. The lab's work is showcased at murtylab.com , emphasizing translational research in vision science and neurotechnology.

Dmitry MarkovView profile

Research Professor

• Microphysiological Systems
• Organ-on-a-Chip Technology
• Microfluidic Bioreactors
• +3 more

Dmitry Markov is a Research Professor of Biomedical Engineering at Vanderbilt University's School of Engineering. His research focuses on developing microphysiological systems and organ-on-a-chip technologies to model tissue microenvironments ex vivo. These systems utilize microfluidic bioreactors for studying disease progression, drug efficacy, and environmental toxin effects. Markov's work integrates engineering principles with biological systems, emphasizing instrumentation for micro-scale measurements and environmental control within bioreactors. Education includes a Ph.D. and M.S. in Electrical Engineering from Texas Tech University, providing foundational expertise in microfluidics and sensor technologies. His interdisciplinary research bridges material science, computational modeling, and clinical applications, with a focus on PDMS-based device design and toxicokinetic analysis. Key research interests include optimizing organ-on-chip systems for personalized medicine, modeling tumor microenvironments, and developing integrated multi-organ platforms. His recent work explores metabolic dysfunction in neurological disorders using organ-on-a-chip models and investigates chemical-partitioning dynamics in biomaterials. Markov has contributed to advancing microfluidic valve and pump technologies, with patents covering rotary valves, capacitive pumps, and stackable bioreactor architectures. His lab develops both hardware innovations and computational models to enhance predictive toxicology and translational biomedical research.

Elizabeth Bartolak-SukiView profile

Academic

• Mechanotransduction pathways
• Respiratory mechanobiology
• Vascular mechanobiology
• +4 more

Elizabeth Bartolak-Suki is a Research Assistant Professor in the Department of Biomedical Engineering at Boston University's College of Engineering. She holds a B.S., M.S. in Basic Medical Sciences, and an M.D. from the Medical School of Szeged, along with a D.Sc. (PhD equivalent) in Molecular Cell Biology from the Medical School of Budapest. Her primary research focuses on mechanotransduction pathways in respiratory and vascular systems, including organelle mechanobiology and protein post-translational modifications. She develops novel live imaging techniques to study cellular responses to mechanical forces in dynamic environments, with applications in vascular tissue engineering and alcohol-related vascular malformations. Education: B.S./M.S. in Basic Medical Sciences, Medical School of Szeged M.D. in General Medicine, Medical School of Szeged D.Sc. in Molecular Cell Biology, Medical School of Budapest Her research explores how mechanical forces from breathing, blood flow, and physiological rhythms regulate cell functions, cytoskeletal organization, and molecular signaling. Techniques include real-time imaging and dynamic mechanical modeling to investigate mitochondrial behavior, extracellular matrix interactions, and disease mechanisms in emphysema and pulmonary fibrosis. Recent work highlights the role of variability in mechanical stimuli for maintaining homeostasis and tissue repair. Publications emphasize mechanobiology applications in lung and vascular systems, with notable contributions to tissue engineering and ventilation strategies. Her studies bridge molecular mechanisms with clinical applications, particularly in optimizing variable ventilation for preterm lambs and mitigating ventilator-induced lung injuries. Dr. Bartolak-Suki’s lab focuses on translational research, combining engineering approaches with biological systems to address unmet clinical needs in respiratory and vascular health. Current projects include developing biomaterials for vascular repair and elucidating mitochondrial responses to mechanical stress in aging and disease.

Gürhan ÖzkayarView profile

Researcher

• Biomedical Engineering
• Microfluidics
• Cancer Research
• +5 more

Gürhan Özkayar is a Researcher in the Department of Chemical Engineering at Delft University of Technology (TU Delft), affiliated with the Faculty of Applied Sciences. His postdoctoral research focuses on developing label-free microfluidic technologies for isolating heterogeneous circulating tumor cells (CTCs) to enhance drug testing accuracy. This work is part of a collaborative ZonMw project led by Pouyan Boukany (TU Delft), involving partners such as Leiden University Medical Center (LUMC) and Erasmus MC. His research interests center on biomedical engineering, microfluidics, and cancer diagnostics. Key areas include CTC isolation, lab-on-a-chip systems, dielectrophoresis, and modular microfluidic architectures for organ-on-a-chip applications. His contributions address challenges in fluid dynamics, nanoparticle manipulation, and biomedical device design. Özkayar’s publications highlight advancements in microfluidic particle separation, piezoelectric micropump optimization, and rare cell enrichment. His work bridges engineering and biomedicine, emphasizing practical solutions for diagnostic and therapeutic applications. Collaborations include projects on multidrug resistance detection in leukemia cells and portable flow control systems. No scientific awards are mentioned. His current projects involve developing scalable, integrated microfluidic systems and improving CTC capture efficiency. He contributes to cross-institutional teams advancing cancer research and precision medicine technologies.

Annie KathuriaView profile

Assistant Professor

• Organoid Tissue Engineering
• Pluripotent Stem Cells
• 3D Tissue Models
• +5 more

Annie Kathuria, PhD is an Assistant Professor in the Department of Biomedical Engineering at Johns Hopkins University, affiliated with the Kavli Neuroscience Discovery Institute. Her research focuses on organoid tissue engineering using pluripotent stem cells to create 3D models of neurological systems, particularly cerebral organoids for studying autism, schizophrenia, Alzheimer's, and other disorders. She leads the Kathuria Lab, which employs multi-modal approaches including electrophysiology and high-throughput imaging to advance drug screening and toxicological analysis. Education: PhD in Neuroscience (King’s College London, 2016), MSc in Clinical Neuroscience (King’s College London, 2012), BSc Double Major in Neuroscience/Genetics (University of Minnesota, 2011). She completed a postdoctoral fellowship at Harvard Medical School in 2019. Research Interests: Development of cerebral, retinal, and visceral organoids; molecular mechanisms of neurodevelopmental disorders; industry partnerships for translational applications in personalized medicine and food safety. Her work bridges stem cell biology, bioengineering, and computational analysis to create clinically relevant models. Recent Highlights: 2023 interview highlighted her vision for integrating organoid systems with machine learning to accelerate drug discovery. Her lab's multi-region brain organoid fusion system (2025) represents a major advancement in modeling complex neural circuits.

Yuling WangView profile

Professor

• Nanotechnology
• Surface-Enhanced Raman Spectroscopy (SERS)
• Cancer Diagnostics
• +3 more

Professor Yuling Wang is an ARC Future Fellow and Professor at Macquarie University's School of Natural Sciences. She leads the Nanosensors@MQ research group and the SERS program for in vitro diagnostics at the MQ Photonics Research Centre and Hearing Research Centre. Her research focuses on plasmonic nanostructures for SERS-based diagnostics, biomarker sensing, and personalized nanomedicine. Educational Background: PhD from Chinese Academy of Sciences (2009), postdoctoral work at Purdue University (2009-2011), Alexander von Humboldt Fellowship at University of Osnabrück (2011-2013), and DFG-funded research at University of Duisburg-Essen (2013-2014). Joined Macquarie University in 2014 as an ARC DECRA Fellow, promoted to Associate Professor (2020) and Professor (2023). Research Interests: Development of SERS nanotags for multiplexed biomarker detection, EV-based liquid biopsy technologies, and nanostructured theranostics for precision oncology. Key projects include cancer-derived EV phenotyping and SERS-microfluidic platforms for clinical translation. Grants & Collaborations: Principal Investigator on 19 projects including MNDRA24 (EV membrane proteome analysis), LE24 (multimodal microscopy), and ACRF Centre for Advanced Cancer Modelling. Active collaborations in Australia and internationally. Award Recognition: ARC College of Experts (2022-2024), Wiley Raman Student Award (2018), and multiple student scholarships. Labs/Teams: Leads the Nanosensors@MQ lab and contributes to ARC Centres of Excellence. Supervises 10 PhD students (principal) and 2 (associate), with notable student achievements in cancer diagnostics research.

Hans-Joachim EgelhaafView profile

Senior Lecturer

• Photovoltaics
• Materials Science
• Energy Technology
• +3 more

PD Dr. Hans-Joachim Egelhaaf is part of the Chair of Materials for Electronics and Energy Technology at Friedrich-Alexander-Universität Erlangen-Nürnberg. He leads the 'Solar Factory of the Future' group, focusing on advancing printed photovoltaic technologies and scalable production processes. His work emphasizes roll-to-roll (R2R) manufacturing, ink formulation using green solvents, and high-efficiency solar module upscaling. He also explores laser ablation patterning, encapsulation techniques, and integration into building-integrated photovoltaics (BIPV). Research interests include optimizing perovskite and organic solar cells, improving outdoor durability, and developing industrially viable processes. His group collaborates on high-throughput platforms and material design for BIPV applications. Recent studies highlight innovations in electrode materials (e.g., silver electrodes via laser printing), process optimization (e.g., gas-quenching for perovskite films), and large-area module efficiency (14.5% certified record). His work bridges laboratory research and industrial scalability, aiming to minimize efficiency losses during upscaling. Key contributions include aerosol-jet-printed encapsulation, CO₂ snow jet cleaning for substrate deburring, and inkjet-printed organic solar cells on 3D objects. His lab emphasizes cross-disciplinary approaches to address challenges in energy alignment, moisture resistance, and mechanical stability.