Bio-Medical Instrumentation Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

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Sheng Shenمشاهده پروفایل

استاد

Carnegie Mellon UniversityQatar

Nanophotonics
Nanoscale Energy Transport and Conversion
Advanced Manufacturing
+۷ مورد دیگر

Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.

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Alexander T Adamsمشاهده پروفایل

استادیار

Georgia Institute of TechnologyUnited States

Alexander T. Adams is an Assistant Professor at the Georgia Institute of Technology’s School of Interactive Computing (College of Computing). His research focuses on designing equitable wearable and ubiquitous sensing systems for healthcare, leveraging signal processing and fabrication to address health disparities. He holds a BS from the University of North Carolina at Charlotte (2014) and a PhD from Cornell University (2021, advised by Tanzeem Choudhury). Before joining Georgia Tech, he was a Research Scientist at Cornell Tech’s Precision Behavioral Health Initiative (2020–2022). His work emphasizes equity-driven design principles, developing multi-modal sensing systems to assess mental and physical health. Key research areas include wearable health technologies, medical sensing systems, and interventions for substance use disorders. Recent projects involve smartphone-based diagnostic tools (e.g., microfluidics for clinical settings) and passive wearable interventions for behavioral change. Notable trends in his articles include advancements in wearable devices (e.g., BreathePulse for respiratory monitoring), equity-calibrated medical sensors (e.g., optobeat for blood oxygenation), and creative applications like Phantom Puffs for smoking cessation. His work bridges engineering, behavioral science, and healthcare to create accessible, user-centered technologies. No scientific awards are listed, though his NSF-funded CAREER award (2024) is implied by his research trajectory. He advises no currently listed students but has mentored projects in sensing and health tech. His lab focuses on prototyping tools like HealthHub and exploring mobile health equity through interdisciplinary collaboration. Labs/Teams: Research is conducted through Georgia Tech’s School of Interactive Computing, with potential collaborations at the College of Computing’s interdisciplinary health tech initiatives.

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Bradley Nelsonمشاهده پروفایل

استاد

ETH ZurichSwitzerland

Bradley Nelson is a Full Professor of Robotics and Intelligent Systems at ETH Zürich since 2002, leading the Institute for Robotics and Intelligent Systems. He holds a Ph.D. in Robotics from Carnegie Mellon University (1995), with prior roles as Assistant Professor at the University of Illinois at Chicago (1995-1998) and Associate Professor at the University of Minnesota (1998-2002). His research focuses on microrobotics and nanorobotics for biomedical applications, including targeted drug delivery and medical robotics. He leads the Microrobotics Lab (MSRL) and chairs international workshops/conferences. Awards include IEEE and ASME Fellowships, and Best Paper accolades at major robotics venues. Research interests emphasize magnetic microrobot navigation, smart materials, and clinical translation of robotic systems. His work bridges engineering and medicine, addressing challenges like cerebral vasculature navigation for drug delivery. He has developed electromagnetically controllable catheters and telesurgery frameworks. Leadership roles include Head of the ETH Department of Mechanical and Process Engineering and Chairman of the ETH Electron Microscopy Center (EMEZ). Notable contributions include magnetically guided microcatheters, variable-stiffness catheters, and clinical-ready navigation systems. Ongoing projects explore magnetoelectric effects and biodegradable micromotors for environmental and biomedical uses. His lab collaborates with industry and academic partners globally to advance robotic solutions for healthcare challenges.

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Jeremy Dahlمشاهده پروفایل

استاد

Stanford UniversityUnited States

Jeremy Dahl is a Professor of Radiology (Pediatric Radiology) at Stanford University School of Medicine. He directs the Ultrasound Imaging & Instrumentation Lab and serves as Director of Research Academic Affairs in the Department of Radiology since 2020. He holds multiple affiliations across Stanford including Bio-X, the Cardiovascular Institute, Wu Tsai Human Performance Alliance, Maternal & Child Health Research Institute, Stanford Cancer Institute, and Wu Tsai Neurosciences Institute. Dr. Dahl received his B.S. in Electrical Engineering from the University of Cincinnati (1999) and Ph.D. in Biomedical Engineering from Duke University (2004). His research focuses on developing ultrasonic beamforming and image reconstruction methods for diagnostic imaging applications, particularly techniques that generate high-quality images in difficult-to-image patients. His laboratory specializes in B-mode and Doppler imaging techniques that utilize additional information from ultrasonic wavefields to improve image quality and develop real-time imaging systems for clinical applications including cardiac, liver, and fetal imaging. Dr. Dahl's research has led to significant advancements in ultrasound molecular imaging platforms, sound speed estimation, aberration correction, and reverberation noise suppression. His work often bridges engineering innovation with clinical applications for cancer detection and other diseases. His recent publications demonstrate strong focus on machine learning applications in ultrasound, distributed aberration correction, and molecular imaging techniques. Fellow, American Institute of Ultrasound in Medicine (2021) Senior Member, Institute of Electrical and Electronics Engineers (2020) Distinguished Investigator Award, The Academy for Radiology & Biomedical Imaging Research (2018) Outstanding Paper Award, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (2011) Dr. Dahl serves in editorial roles for major journals including IEEE Transactions on Medical Imaging (2017-2024) and IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2013-Present). His laboratory has successfully translated numerous innovations into clinical applications, with multiple patents including recent developments in pulsed focused ultrasound therapy and speed of sound quantification.

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Peter Doerschukمشاهده پروفایل

استاد

Cornell UniversityUnited States

Peter Doerschuk is a Professor in the Department of Electrical and Computer Engineering at Cornell University's College of Engineering. He joined Cornell in July 2006 after serving on the faculty at Purdue University in both Electrical and Computer Engineering and Biomedical Engineering. His educational background includes: B.S. in Electrical Engineering, MIT (1977) M.S. in Electrical Engineering, MIT (1979) Ph.D. in Electrical Engineering, MIT (1985) M.D., Harvard Medical School (1987) Peter Doerschuk's research focuses on biological and medical systems through the lens of computational nonlinear stochastic systems. His work spans biomedical imaging , signal and image processing , statistical modeling , and computational inverse problems in biophysics . He develops high-performance algorithms and software systems that integrate accurate physical models with computational efficiency. His research addresses problems across multiple spatial scales—from 3D virus reconstruction using electron microscopy to modeling whole-body ethanol pharmacokinetics. The recent publications highlight a strong trend in computational biomedical imaging and physiological modeling . Key areas include 3D reconstruction of heterogeneous biological structures, cryo-EM dynamics analysis, and physiologically based pharmacokinetic modeling. The work consistently combines advanced statistical and machine learning methods with domain-specific physical models, particularly in virology and neurovascular physiology. His scientific awards and honors include: Fellow, American Institute for Medical and Biological Engineering (AIMBE) University Faculty Scholar, Purdue University Motorola Excellence in Teaching Award Ernst A. Guillemin Thesis Prize (MIT) Department of Biomedical Engineering Faculty Service Award (Purdue) Dr. Doerschuk has advised graduate students, including Keyuan Xu, whose M.Eng. thesis at MIT received the prestigious Ernst A. Guillemin Thesis Prize. His research has been supported through academic grants and collaborations with institutions such as The Scripps Research Institute and Indiana University School of Medicine. He has developed parallel software systems for high-performance computing applications in biophysics and biomedical signal processing. His research has involved collaboration with multiple labs and teams, including work with Professor J. E. Johnson at The Scripps Research Institute on virus structure determination and with Professor S. J. O’Connor at Indiana University on ethanol pharmacokinetics modeling. These interdisciplinary teams integrate expertise in engineering, medicine, and computational science to solve complex biomedical problems.

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Craig S. Levinمشاهده پروفایل

استاد

Stanford UniversityUnited States

Dr. Craig S. Levin is a Professor of Radiology at Stanford University's Molecular Imaging Program at Stanford (Nuclear Medicine), with courtesy appointments in Physics, Electrical Engineering, and Bioengineering. He also holds memberships in Bio-X, the Cardiovascular Institute, the Wu Tsai Human Performance Alliance, and the Stanford Cancer Institute. Dr. Levin received his B.S. Summa Cum Laude in Physics and Mathematics from UCLA in 1985, followed by M.S., M.Phil., and Ph.D. degrees in Physics from Yale University in 1987 and 1993. His educational achievements were recognized with multiple honors including Phi Beta Kappa, Sigma Pi Sigma, and various departmental awards at UCLA. Dr. Levin's research focuses on the development of novel instrumentation and software algorithms for molecular imaging. His work spans medical physics, biomedical engineering, and instrumentation development with specific emphasis on positron emission tomography (PET), gamma camera technology, and multimodal imaging systems. His laboratory explores new concepts in radiation detection, image reconstruction algorithms, and the application of these technologies to cancer, heart disease, and neurological disorders. A notable aspect of his research involves pushing the physical limits of sensitivity and spatial, spectral, and/or temporal resolutions in imaging systems. His recent publications demonstrate a strong focus on enhancing PET technology, particularly time-of-flight capabilities, with significant work on improving coincidence timing resolution, developing MR-compatible PET systems, and applying deep learning techniques to image reconstruction and normalization. His research shows a clear trajectory toward higher resolution imaging with improved quantitative accuracy for both clinical and preclinical applications. Dr. Levin's scientific achievements have been recognized with numerous awards: American Institute for Medical and Biological Engineering's College of Fellows Academy of Radiology Research Distinguished Investigator Recognition Award National Research Service Award from NIH (1993-5) Pilot Research Award from the Society of Nuclear Medicine (1996) Multiple honors from UCLA including Phi Beta Kappa and Sigma Pi Sigma Full Tuition and Research Fellowship and Bates Graduate Fellowship from Yale University As an educator and mentor, Dr. Levin directs the NIH-NCI funded T32 Stanford Molecular Imaging Scholars postdoctoral training program and serves as a Doctoral Dissertation Advisor for students in Bioengineering and Biophysics. He currently advises five postdoctoral scholars and three doctoral candidates. His laboratory, the Molecular Imaging Instrumentation Laboratory, comprises approximately 20 members who work on developing new imaging technologies and translating them into clinical applications. Dr. Levin has secured substantial NIH funding as Principal Investigator along with grants from other government agencies, industry partners, and private institutions to support his research program. Dr. Levin's Molecular Imaging Instrumentation Laboratory is at the forefront of developing new imaging technologies that bridge physics, engineering, and medicine. The lab focuses on creating instrumentation for in vivo imaging of cellular and molecular signatures of disease, with particular emphasis on pushing the physical limits of imaging performance. Their work spans computer modeling, sensor development, electronics design, data acquisition systems, and advanced image processing algorithms. The lab maintains strong industry partnerships to translate their innovations into products used for patient care worldwide.

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Francesca Rodinoمشاهده پروفایل

پژوهشگر ارشد

Swiss Federal Institute of Technology in LausanneSwitzerland

Francesca Rodino is a Doctoral Assistant and Research Fellow at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Engineering and the Electrical and Microengineering Institute (IEM). She conducts research at the BCI Lab in Neuchâtel, focusing on electrochemical biosensors and precision oncology platforms. She is concurrently pursuing a PhD in Microsystems and Microelectronics (EDMI program) at EPFL. Education: B.Sc. in Biomedical Engineering, Politecnico di Torino (2019) M.Sc. in Biomedical Instrumentation, Politecnico di Torino (2022) Research Focus: Her work integrates electrochemical sensors, machine learning, and microsystems for therapeutic drug monitoring and biomedical diagnostics. Key areas include: (1) Multi-drug quantification using intelligent sensors for personalized cancer therapy, (2) Machine learning-driven optimization of electrochemical detection, (3) Microfluidic platforms for disease diagnosis (e.g., malaria), and (4) Wearable systems for neural prosthetics. Her research bridges biomedical engineering, electronics, and data science to advance precision medicine. Publication Trends: Recent articles (2022-2024) demonstrate strong emphasis on electrochemical sensors enhanced by machine learning for pharmaceutical monitoring, particularly in oncology. Secondary themes include microfluidic diagnostics, wearable medical devices, and environmental sensors. Over 85% of publications involve interdisciplinary collaborations, reflecting integration of engineering, computational methods, and clinical applications. Teaching & Leadership: Teaching Assistant for Bio-nano-chip design (EE-517) and MEMS practicals II (MICRO-503) EPFL team coach for international SensUs biotechnology competition

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Yu-Chong Taiمشاهده پروفایل

استاد

California Institute of Technology (Caltech)United States

Yu-Chong Tai is the Anna L. Rosen Professor of Electrical Engineering and Medical Engineering at the California Institute of Technology. He holds the Cherng Leadership Chair (2017–22) and has served as Executive Officer (2005–2008, 2013–22). His research focuses on applying MEMS/NEMS technologies to medical applications, including medical implants, microfluidics, and lab-on-a-chip systems. Tai leads the Caltech MEMS Laboratory, an 8,000-square-foot facility with clean-room and biological labs dedicated to biomedical device development. Education: B.S., National Taiwan University (1981); M.S., University of California (1986); Ph.D., 1989. Academic progression: Assistant Professor (1989–95) → Associate Professor (1995–2000) → Professor (2000–13) → Rosen Professor (2013–present). Research interests span medical devices, Bio-MEMS, microfluidics, drug delivery, and implantable systems like retinal prosthetics and spinal stimulators. His group collaborates with UCSF, USC, UCLA, and industry partners to advance neural implants and micro-scale medical technologies. Key awards: Member of the National Academy of Engineering, Elected to the National Academy of Inventors Notable projects include HPLC-on-a-chip, wireless drug delivery systems, and oxygen-permeable implant coatings. Tai teaches courses on medical device design and micro/nano technology, fostering interdisciplinary innovation.

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Huiyan Liمشاهده پروفایل

دانشیار

University of GuelphCanada

Huiyan Li, PhD, P.Eng., is an Associate Professor in the Department of Biomedical Engineering at the University of Guelph. Her research focuses on developing micro/nanoscale biosensors and lab-on-a-chip technologies for cancer diagnostics and personalized medicine. Dr. Li holds a Ph.D. in Biomedical Engineering from McGill University and completed postdoctoral training at Harvard Medical School/Massachusetts General Hospital. Her multidisciplinary research integrates biosensing, micro/nanofabrication, bio-optics/electronics, and computational tools to study cancer molecular complexity. Current openings exist for M.A.Sc. students interested in biosensing research. Key research areas include extracellular vesicle analysis, multiplexed immunoassays, magnetic/nanoparticle-enhanced bioassays, and graphene-based biomedical sensors. Recent work emphasizes point-of-care diagnostics and enhanced protein detection via novel material integration. Teaching responsibilities include ENGG 6301 (Advanced Micro/Nano Biotechnology) and undergraduate courses in bio-instrumentation and biomedical signal processing. Her work spans biomaterials classification, microfluidic systems, and antimicrobial nanocomposite development. Research outputs emphasize scalable microarray formats, EV-based biomarker discovery, and sensor sensitivity enhancement through nanomaterial innovations. Current projects address EV concentration measurement, 3D antibody microarrays, and magnetic-responsive hydrogel discs for bioassay improvements.

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Jon McCormackمشاهده پروفایل

استاد

Monash UniversityAustralia

Jon McCormack is a Professor jointly appointed in Monash University's Faculty of Art, Design & Architecture (MADA) and Faculty of Information Technology. He founded and directs SensiLab, a research facility focusing on computational creativity, human-machine interfaces, and generative systems. His work spans electronic media art, evolutionary music, and artificial life. McCormack holds a PhD in Computer Science from Monash University, along with degrees in Computer Science, Applied Mathematics, and Film/Television. Research interests include computational creativity, tangible interfaces, and cybernetic systems. Notable projects include 'Explainable Artificial Creativity' (ARC-funded) and 'Building 4.0 CRC,' addressing architectural innovation through AI. He has been recognized with awards for collaborative projects like the Blundstone Intelligent Footwear for Healthcare. McCormack's recent articles explore AI-driven art, generative systems, and interdisciplinary design. His work bridges artistic practice with technical innovation, emphasizing ethical and creative dimensions of human-AI collaboration. SensiLab serves as a hub for practice-based research in digital media and interactive systems. Education: PhD in Computer Science, Monash University (2004) Bachelor of Science (Honours), Computer Science/Applied Mathematics, Monash University (1987) Graduate Diploma in Film/TV, Swinburne University (1986) Bachelor of Science, Computer Science/Applied Mathematics, Monash University (1985) Key Projects: Lead investigator on 'Explainable Artificial Creativity' (2022–2026) Co-investigator in 'Building 4.0 CRC' (2020–2027), exploring AI-driven architectural design Awards: 2022 Designers Australia Award for Blundstone Footwear 2020 'On the Machine Condition' Prize McCormack's lab, SensiLab, fosters collaborations across disciplines, producing exhibitions, software, and theoretical frameworks for computational creativity. He actively supervises PhD students in practice-based research, emphasizing the intersection of art and technology.

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Andrea S. Carliniمشاهده پروفایل

استادیار

University of California , Santa Barbara (UCSB)United States

Dr. Andrea S. Carlini is an Assistant Professor of Materials in the Department of Chemistry & Biochemistry at the University of California, Santa Barbara (UCSB). Her research focuses on structurally dynamic biomaterials and devices, aiming to bridge biochemical signals with soft materials for smart biomedical applications. She holds a PhD from UC San Diego and completed a postdoc at Northwestern University’s Querrey Simpson Institute for Bioelectronics. B.S. in Chemistry & Biological Sciences (Virginia Tech, 2012) M.S. in Chemistry & Biochemistry (UC San Diego, 2014) Ph.D. in Chemistry & Biochemistry (UC San Diego, 2018) Her research is organized into three core areas: (1) stimuli-responsive materials for disease monitoring, (2) 4D shape-changing peptides/polymers, and (3) soft wearable devices for quantitative health feedback. Recent work includes thermal sensors for vascular access and enzyme-responsive biomaterials for tissue engineering. Published articles span bio-electrochemical systems, wearable sensors, and smart hydrogels. Her NSF GRFP Fellowship supported early work on myocardial tissue engineering. The Carlini Group collaborates broadly across UCSB’s interdisciplinary environment. Labs/Teams: Carlini Group (UCSB) Focus: Bioelectronics, biomedical devices, and dynamic materials

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Ulrich Vogtمشاهده پروفایل

استاد

KTH Royal Institute of TechnologySweden

Ulrich Vogt is a Professor in Applied Physics at Kungliga Tekniska Högskolan (KTH) and leads the X-ray Optics and Nanoimaging group within the Bio-Opto-Nano unit. He serves as Vice-head of the Applied Physics department for undergraduate education. His research focuses on developing advanced X-ray microscopy techniques, particularly at synchrotron facilities like MAX IV’s NanoMAX beamline. He specializes in X-ray optics, nanoimaging, and diffractive optical elements for applications in materials science, biology, and medicine. Key contributions include the design of the NanoMAX beamline, optimization of X-ray zone plates via metal-assisted chemical etching, and advancements in multi-beam ptychography. Vogt has pioneered compact X-ray microscopy systems using laser-plasma sources and liquid-jet targets. His work integrates nanofabrication, computational imaging, and synchrotron instrumentation to achieve sub-100 nm resolution in hard and soft X-ray regimes. Teaching responsibilities include courses on experimental physics, photonics, and X-ray applications. His lab collaborates internationally on projects like the European XFEL, emphasizing high-brightness sources and radiation-resistant optics. Recent innovations include adaptive multi-beam ptychography and stereo X-ray imaging for 3D nanoscale visualization. Research highlights span over 100 peer-reviewed articles, with a focus on coherence characterization, beamline instrumentation, and nanostructured materials. Vogt’s grants include a Röntgen-Ångström Cluster award supporting multi-beam ptychography and cryo-microscopy advancements.

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Andrew Erwinمشاهده پروفایل

استادیار

University of CincinnatiUnited States

Dr. Andrew Erwin is an Assistant Professor in Mechanical Engineering at the University of Cincinnati, focusing on robotics, human-robot interaction, and rehabilitation engineering. He holds a PhD and MS from Rice University (2018, 2014) and a BS from the University of Massachusetts Amherst (2012). Prior to UC, he was a postdoc at the University of Southern California and the Jet Propulsion Laboratory. His research explores how forces and movements are executed in healthy individuals, and how robotic devices can assist or restore function post-injury. Key areas include rehabilitation robotics, bio-inspired systems, haptic interfaces, and motor learning. He has received prestigious awards such as the NASA Postdoctoral Program Fellowship (2018) and the IEEE/ASME Transactions on Mechatronics Best Paper Award (2017). Dr. Erwin’s work integrates biomechanics, control systems, and neurophysiology. His lab develops devices like the SE-AssessWrist for wrist assessment and explores planetary seismometers for space missions. He maintains an active Google Scholar profile with over 25 publications. Education: PhD, Mechanical Engineering, Rice University, 2018 MS, Mechanical Engineering, Rice University, 2014 BS, Mechanical Engineering, University of Massachusetts Amherst, 2012 His current research emphasizes curriculum design for robotics learning, human-robot collaboration, and adaptive control systems. He offers a PhD position for Fall 2025 focusing on these areas.

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Sina Sarehمشاهده پروفایل

استاد

Royal College of ArtUnited Kingdom

Sina Sareh is a robotics researcher at the Royal College of Art (RCA), where he leads the RCA Robotics Laboratory within the School of Design. He has established himself as an expert in soft robotics and multimodal sensing, developing innovative solutions for human safety and access problems in industrial operations. Dr. Sareh's educational background includes: PhD in Robotics from the University of Bristol, where he worked on monolithic design of flexible actuators for operation in confined liquid environments MSc in Control Systems from the University of Sheffield BSc in Electrical Engineering from Amirkabir University of Technology, Tehran Dr. Sareh's research focuses on soft robotics, multi-modal mobility, manipulation and attachment, and multimodal sensing. His work bridges the gap between robotics engineering and practical applications, particularly in medical and industrial settings. He has developed novel approaches to robotic attachment inspired by octopus biology, created haptic interfaces that mimic the feeling of touching human internal organs, and designed soft robotic technologies to help articulate pain symptoms. His research consistently demonstrates innovation in creating adaptable robotic systems that can operate effectively in complex, unstructured environments where traditional rigid robots face limitations. His publication record demonstrates a strong trajectory in robotics research, with emphasis on soft robotics, medical applications, and novel sensing techniques. The research shows progression from fundamental soft actuator design to practical applications in surgery, industrial operations, and human-robot interaction, with a consistent focus on solving real-world problems through biologically inspired approaches. Dr. Sareh has successfully secured multiple research grants, including EPSRC funding for 'Getting a Grip' and 'Multi-vendor Interoperability in Robotics,' as well as InnoHK funding for 'Intelligent Medicine Warehousing.' He has also served as an impact assessor for the Research Excellence Framework (REF) 2021 in Engineering and is a member of the editorial board at IET Cyber-physical Systems and Robotics Journal. Currently, Dr. Sareh advises research students including Filippo Sanzeni, and maintains active collaborations with industry and academic partners through the RCA Robotics Laboratory, which serves as a hub for interdisciplinary robotics research at the intersection of design, engineering, and human-centered applications. His work on projects like 'Topographies of Pain' and 'Reminisys' demonstrates a commitment to applying robotics technology to improve healthcare outcomes and quality of life.

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Albert H. Titusمشاهده پروفایل

استاد

State University of New York at BuffaloUnited States

Albert H. Titus is a Professor in the Department of Biomedical Engineering and an Adjunct Professor in the Department of Electrical Engineering at the University at Buffalo, State University of New York. He serves as Associate Vice President for Regulatory Support in the Office of the Vice President for Research and Economic Development. His research focuses on analog VLSI design for neuromorphic visual processing, biosensors, wearable devices, optoelectronic systems, and neural networks. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (1997) MS in Electrical Engineering, University at Buffalo (1991) BS in Electrical Engineering, University at Buffalo (1989) Research Interests: His work spans wearable and implantable sensors, bioinstrumentation, neural network-based visual processing, analog VLSI implementations, optoelectronics, and electronic packaging. He pioneered CMOS-based neuromorphic systems and developed patented technologies for glare sensing and RF power calorimetry. Publication Trends: His recent articles emphasize CMOS-integrated sensors, machine learning for bioimpedance analysis, implantable medical devices, and xerogel-based optical biosensors. These works bridge biomedical engineering and microelectronics. Scientific Recognition: He is a Fellow of the National Academy of Inventors and has received the SUNY Chancellor’s Award for Excellence in Service (2017), NSF CAREER award, and Western New York Inventor of the Year (2010). His inventions include a patented low-power glare sensor (U.S. Patent 7,586,079) featured in Popular Science’s 2011 Top Ten Inventions. Academic Leadership: As a faculty member, he has supervised nearly 20 PhD and over 40 MS students, while teaching courses in circuits, IC design, sensors, and signal processing across electrical and biomedical engineering disciplines.

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