Xiaolong Liu is an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University and a member of the STEM CORE program. He previously held a Research Scientist position at Johns Hopkins University, affiliated with the Department of Mechanical Engineering and the Laboratory of Computational Sensing and Robotics (LCSR). His research spans soft robotics, medical robotics, computer-assisted surgery, and surgical innovation. Grants: National Science Foundation (NSF), National Institute of Health (NIH), American Heart Association (AHA), Maryland Technology Development Corporation (TEDCO) Research Areas: Soft robotics, medical devices, surgical automation, and robotics He has published over 40 peer-reviewed papers in IEEE, ASME, and BMES journals and conferences, and his work has been recognized with awards such as the Maryland Innovation Initiative Award and Best Paper Runner-up Award in Robotics. Dr. Liu has also contributed to NSF panels, conference committees, and editorial boards in robotics and automation.
Christopher G. Brinton is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, where he leads the ION research lab. He is affiliated with the Department of Electrical and Computer Engineering in the College of Engineering at Purdue University's West Lafayette campus. Dr. Brinton received his PhD from Princeton University, where he was previously the Associate Director of the EDGE Lab and a Lecturer of Electrical Engineering. His research focuses on the intersection of networking, communications, and machine learning, with particular emphasis on Fog computing systems, the Internet of Things (IoT), NextG Wireless, and social learning networks. His research integrates foundational techniques including convex and non-convex optimization, machine learning, and signal processing to address challenges in networked intelligent systems. The ION lab under his leadership develops both theoretical frameworks and practical implementations for next-generation networking solutions, with strong industry collaborations including Qualcomm, Nokia, Intel, Cisco, Dell, and Ericsson. Recent publications reveal a strong trend toward federated learning, decentralized algorithms, and edge intelligence, with significant contributions to model partitioning, communication-efficient learning, and robust network architectures. His work increasingly bridges traditional communication theory with modern machine learning techniques to solve emerging challenges in distributed networked systems. NSF CAREER Award ONR Young Investigator Program (YIP) Award DARPA Young Faculty Award (YFA) AFOSR Young Investigator Program (YIP) Award Intel Rising Star Faculty Award (RSA) Dr. Brinton teaches several courses including ECE 647: Performance Modeling of Computer Communication Networks, ECE 301: Signals and Systems, and ECE 547: Introduction to Computer Communication Networks. He has co-authored the book 'The Power of Networks: Six Principles That Connect Our Lives' and taught three Massive Open Online Courses (MOOCs) with over 400,000 cumulative students. While not currently actively recruiting students, he remains open to connecting with highly motivated individuals. Dr. Brinton leads the ION (Intelligent Optimization and Networking) research lab, which focuses on creating theoretical foundations and practical implementations for next-generation networked systems. The lab has recently published significant work on 6G taxonomy in collaboration with major industry partners and continues to push boundaries in distributed learning and network optimization.
Guojun Chen is an Assistant Professor at the Department of Biomedical Engineering and a member of the Rosalind & Morris Goodman Cancer Institute (GCI) at McGill University . His research focuses on engineering intelligent biomaterials for precision medicine , with emphasis on non-viral genome editing , cold atmospheric plasma (CAP) therapy , and biomaterials-mediated immunotherapy . The lab operates in a multidisciplinary environment , integrating principles from materials science , chemistry , biology , and health sciences . Education : Ph.D. from University of Wisconsin-Madison (2017), Postdoc at UCLA (2020) Research Themes : Genome Editing Delivery : Designing non-viral vectors for efficient CRISPR/Cas9 delivery in vivo. CAP-mediated Immunotherapy : Developing portable cold plasma devices to synergize with immune checkpoint blockade and study CAP’s immunological mechanisms. Biomaterials-based Immunotherapy : Reprogramming tumor microenvironments using bioresponsive materials to enhance immune responses. Publication Trends : Recent work spans responsive nanomaterials , genomic editing systems , and plasma oncology , with a focus on cancer immunotherapy , diabetes diagnostics , and bioinspired medical devices . Scientific Awards : Canada Research Chair (2024, 2025) McGill's President's Prize for Emerging Researchers (2025) FRQS Chercheurs-boursiers (2022) Chinese Association for Biomaterials Young Investigator Award (2022) NSERC Discovery Grant (2021) Advising & Grants : Supervises 14 current graduate and undergraduate students. Secured $5M+ in funding from CIHR , NSERC , CCS , and CFI , including multi-institutional collaborations with Dr. Morag Park , Dr. Réjean Lapointe , and Dr. Ian Watson .
Dr. Gushu Li is an Assistant Professor at the University of Pennsylvania's School of Engineering and Applied Science, affiliated with the Computer and Information Science Department (primary) and Electrical and Systems Engineering Department (secondary). He leads the Penn Quantum System Lab, focusing on quantum computing software-hardware co-design. University: University of Pennsylvania School: School of Engineering and Applied Science Department: Computer and Information Science Academic Rank: Assistant Professor His research spans quantum compilers, programming languages, algorithm optimization, computer architecture, and electronic design automation. He develops techniques for quantum error correction verification, qubit mapping, and hybrid quantum-classical systems, with work integrated into IBM's Qiskit and Quantinuum's TKET frameworks. The 15 most recent publications highlight advancements in quantum simulation , bosonic quantum computing , fermion-to-qubit mapping , and NISQ-era architectures . Key methodologies include symbolic Hamiltonian compilation, adaptive tree structures, and runtime assertions for quantum program testing. 2024: NSF CAREER Award, NVIDIA Academic Grant Program Award, Intel Rising Star Faculty Award 2021-2022: QISE-NET Triplet Fellow, ACM SIGPLAN Distinguished Paper Award, multiple travel grants 2015-2017: Fellowships from UCSB, UChicago, and DAC Dr. Li advises four PhD students and actively recruits candidates with FPGA/digital design skills for 2025. His lab emphasizes interdisciplinary backgrounds to tackle quantum system challenges.
Sunil K. Agrawal is a Professor of Mechanical Engineering and Professor of Rehabilitation and Regenerative Medicine at Columbia University, where he directs a highly interdisciplinary rehabilitation robotics program bridging the School of Engineering and Applied Sciences and the College of Physicians and Surgeons. His research focuses on developing robotic systems to restore and enhance human mobility for individuals with neurological disorders, pediatric conditions, and age-related decline. Education: PhD in Mechanical Engineering, Stanford University, 1990 MS in Mechanical Engineering, Ohio State University, 1986 BS in Mechanical Engineering, Indian Institute of Technology (IIT) Kanpur, 1984 Research Focus: Dr. Agrawal’s work centers on rehabilitation robotics , where he integrates dynamic systems, control theory, and optimization to create robotic devices that assist in gait training, balance improvement, and functional movement restoration. His studies span stroke, Parkinson’s disease, cerebral palsy, vestibular disorders, and spinal cord injury, using devices like the Tethered Pelvic Assist Device (TPAD) and robotic exoskeletons. Scientific Honors: Machine Design Award, ASME (2016) Robotics and Mechanisms Award, ASME (2016) Fellow, American Institute of Medical and Biological Engineering (AIMBE) (2016) Fellow, American Society of Mechanical Engineers (ASME) (2004) Alexander von Humboldt Foundation U.S. Senior Scientist Award (2007) Friedrich Wilhelm Bessel Research Award (2002) Presidential Faculty Fellow Award, The White House (1994) Research Collaborations & Funding: Dr. Agrawal collaborates with faculty across Neurology, Rehabilitation Medicine, Pediatric Orthopedics, Otolaryngology, Geriatrics, and Psychiatry. His work is supported by the National Science Foundation, National Institutes of Health, and the Spinal Cord Injury Research Board. Laboratory & Outreach: He leads an active research group focused on translational robotic systems, with ongoing clinical trials for stroke, Parkinson’s, cerebral palsy, and elderly fall prevention. His lab develops novel robotic braces, exoskeletons, and VR-integrated training platforms.
Ryan P. Huang is an Associate Professor in the Computer Science & Engineering department at the University of Michigan, College of Engineering, where he leads the Order Lab. Previously, he was an Assistant Professor at Johns Hopkins CS department from 2017 to 2022. His research focuses on computer systems, particularly operating systems and distributed systems, with emphasis on reliability, efficiency, and defensibility across cloud data centers and mobile devices. Dr. Huang's research interests center on pushing the boundaries of cloud systems availability and observability. His work addresses critical challenges such as gray failures and partial failures in distributed systems, developing principled techniques for failure detection and localization. His research spans multiple thrusts including Panorama for enhanced observability, Watchdog for runtime checking, OmegaGen for partial failure localization, and Narya for predictive failure mitigation. He also investigates energy-efficient mobile systems and system misconfiguration prevention. His recent publications demonstrate a strong trend toward addressing silent failures in distributed systems, with multiple papers accepted to top-tier conferences including SOSP and OSDI in 2025. His work bridges theoretical principles with practical system implementations, focusing on real-world challenges in cloud infrastructure and distributed computing environments. NSF CAREER award recipient Multiple Best Paper Awards (OmegaGen, Argus, LeaseOS) CRA Outstanding Undergraduate Researcher Award honorable mentions for advisees Dennis Ritchie doctoral dissertation award honorable mention Dr. Huang actively mentors PhD students including Yuzhuo Jing, Wanning He, Yuxuan Jiang, and others. His lab has produced graduates who have gone on to faculty positions at institutions like University of Virginia and Boston University. He serves on program committees for major systems conferences including SOSP, OSDI, and NSDI, contributing significantly to the academic community. The Order Lab maintains active research collaborations and regularly publishes in top-tier venues, with multiple papers accepted to SOSP and OSDI in 2025.
Nicola Nicolici is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on methods and algorithms for the design of digital integrated circuits and systems, with significant contributions in manufacturing test, post-silicon validation and debug. His work has expanded to include embedded systems, low-energy computing, and custom hardware-accelerated computing systems. Professor Nicolici's research interests span multiple areas of digital system design and validation. His early work focused on manufacturing test methodologies and power-aware testing strategies for integrated circuits. More recently, he has made significant contributions to post-silicon validation techniques, including constrained-random stimuli generation, trace signal selection, and bit-flip detection. His research has evolved to address emerging challenges in embedded computing systems, low-energy design, and specialized hardware acceleration for various applications including deep neural networks and signal processing. His recent publications reveal a strong trend toward hardware acceleration for specialized computing tasks. The research spans matrix multiplication algorithms (Strassen and Karatsuba), memory system optimization (DDR5 calibration), FPGA-based radar processing, and neural network acceleration. His work consistently bridges theoretical algorithm development with practical hardware implementation considerations, particularly focusing on precision analysis, fault tolerance, and energy efficiency. The research demonstrates a clear progression from traditional digital circuit testing to more complex system-level validation and acceleration techniques. Professor Nicolici has been actively involved in teaching courses related to system-on-chip design and test, digital systems, and embedded systems. His teaching portfolio includes advanced courses such as System-on-Chip (SOC) Design and Test and Digital Systems Design , reflecting his expertise in the field. While specific grant information isn't detailed in the provided text, his extensive publication record suggests ongoing research funding support. His research has contributed significantly to the fields of digital circuit testing, post-silicon validation, and hardware acceleration. The work has practical applications in semiconductor manufacturing, embedded systems design, and specialized computing architectures. His recent focus on neural network acceleration and memory system optimization reflects the evolving landscape of computer architecture research.
Dr Bela Bonita Chatterjee is a Senior Lecturer in Law at Lancaster University School of Law , with a focus on teaching and scholarship since 2020. Her work bridges cyberlaw , artificial intelligence , robotics , and gender/sexuality in legal contexts. She has received multiple teaching accolades, including the 2023 Blue Plaque Award and the 2018 FASS Dean’s Senior Teaching Award . Dr Chatterjee’s research interrogates the interdisciplinary intersections of law and technology , particularly cybercrime , AI and criminal law , and widening participation in legal education . Her recent scholarship explores robotics in criminal law and business attire/fashion as legal subjects. 2025 : 'The Speakeasy' conference paper 2023 : Invited discussant on child sex dolls/robots 2022 : Workshops on assessment design and audio-visual feedback 2020 : Decolonizing the curriculum and digital teaching practices 2019 : Robotics in family law, child protection, and Lex Robotica 2018 : Robotics and sexual violence Scientific Awards: 2023 Blue Plaque Award 2022 Highly Commended Award 2018 FASS Dean’s Senior Teaching Award 2006 Sir Alistair Pilkington Prize Nominee/Shortlisted for HEA NTFS and OUP Law Teacher of the Year Awards Dr Chatterjee has supervised and examined numerous PhD and LLM dissertations , served on editorial boards of journals like Frontiers of Legal Research , and co-organized conferences such as the British Association for Canadian Studies Legal Studies Group Annual Conference . She contributes to committees including the CREST Security Research Ethics Committee and EPSRC Fellowship Advisory Board .
Hasti Seifi is an Affiliated Associate Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in Human-Centred Computing. Her research focuses on haptics, augmented reality, and human-robot interaction. Institution: University of Copenhagen Department: Department of Computer Science Section: Human-Centred Computing Research interests include: Designing innovative haptic feedback systems Exploring tactile experiences in augmented reality Developing human-robot interaction frameworks Creating generative models for haptic design Investigating social touch technologies Advancing mid-air and ultrasound haptic interfaces Recent publications demonstrate a strong focus on: Generative haptic modeling for AR/XR systems Human-robot interaction dynamics Text input in extended reality environments Visual-haptic multisensory integration Ultrasound mid-air haptic design tools Social touch technologies
Jeffrey L. Krichmar is a Professor in the Department of Cognitive Sciences and Department of Computer Science at the University of California, Irvine. His academic journey includes a B.S. in Computer Science from the University of Massachusetts Amherst (1983), an M.S. in Computer Science from The George Washington University (1991), and a Ph.D. in Computational Sciences and Informatics from George Mason University (1997). Prior to UCI, he served as Assistant Professor at George Mason University (1997-1999) and Senior Fellow at The Neurosciences Institute (1999-2007). University of California, Irvine (2007-present) George Mason University (1997-1999) The Neurosciences Institute (1999-2007) His research focuses on neurorobotics , exploring how embodied cognition and biologically plausible neural models can enhance robotic systems. Key areas include spiking neural networks , neuromodulation , path planning , and interactive tactile robots for therapeutic applications. His work bridges neuroscience , robotics , and cognitive science , with applications in autonomous vehicles , neuroprosthetics , and AI explainability . Recent publications emphasize spiking neural networks for navigation , neuromodulated attention , and neuromorphic hardware integration. The development of CARLsim, a GPU-accelerated spiking neural network simulator now in version 6.0, represents a major technical contribution. His team's work on socially assistive robots like CARL-SJR targets therapeutic applications for autism and ADHD. Scientific Awards IJCNN 2020 Best Paper Award Finalist for Best Student Paper at IJCNN 2018 Best Paper Award at IEEE IJCNN 2009 Grants include National Science Foundation funding for neural models of decision-making (2009). His lab (Cognitive Anteater Robotics Laboratory) develops systems that use large-scale brain simulations for autonomous behavior , with applications in adaptive robotics , sensorimotor learning , and neuroethology . Current projects explore neuromodulatory influences on attention systems and cognitive flexibility .
Audrey Bowden is an Associate Professor at Vanderbilt University in both the Department of Biomedical Engineering and Department of Electrical and Computer Engineering . She is also the Dorothy J Wingfield Phillips Chancellor Faculty Fellow . Education: PhD in Biomedical Engineering (2007) from Duke University BSE in Electrical Engineering (2001) from Princeton University Research Interests: Bowden's work focuses on biomedical optics and point-of-care diagnostics , with a strong emphasis on addressing healthcare disparities through low-cost technologies. Key areas include: Biomedical Imaging Biophotonics Image Processing Machine Learning in Medical Imaging Optical Coherence Tomography (OCT) Functional Near-Infrared Spectroscopy (fNIRS) Publication Trends: Recent work combines machine learning with endoscopic imaging to differentiate cancer from inflammation, develops low-cost OCT systems for smartphones, and improves fNIRS accessibility for diverse patient populations. Her lab also focuses on 3D reconstruction algorithms for urological applications and specular reflection removal in endoscopic videos. Lab & Clinical Collaborations: The Bowden Biomedical Optics Laboratory (BBOL) collaborates with clinical departments including urology , dermatology , otolaryngology , and women's health . The lab integrates optics , microfluidics , and computer science to create hardware/software tools for resource-constrained environments.
DE BONIS MICHELE is a Professor at San Raffaele Vita-Salute University , where he serves as the Director of the Cardiothoracic Surgery School. He is also the Chief of the Advanced and Research Cardiothoracic Surgery Unit at Ospedale San Raffaele , actively contributing to clinical and academic advancements in cardiovascular surgery since 2017. Research Interests : His work focuses on complex cardiac surgical techniques, including mitral and tricuspid valve repair, transcatheter interventions, and management of complications like pseudoaneurysms and thrombotic events. His recent publications highlight innovations in cardioplegia delivery, CT imaging for endocarditis, and outcomes of surgical and transcatheter approaches. Scientific Awards and Leadership : He has received notable awards such as the Premio "Eccellenze Lucane" (2018), Premio Nazionale Ciociaria (2005), and Premio di Medicina "Prof. Potito Petrone" (1995). He has held key roles in international societies, including President of the European Society of Cardiology's Cardiovascular Surgery Working Group (2014-2016) and Scientific Director of ESC/EACTS guidelines task forces. Teaching and Editorial Contributions : He supervises internships in surgery and cardiovascular diseases for the 6-year Master's Degree in Medicine and Surgery. He also serves as Editor-in-Chief and editorial board member for the International Journal of Cardiology .
Garreth Tigwell is an Assistant Professor in the School of Information at RIT, co-directing the CAIR Lab with Dr. Kristen Shinohara. His research focuses on accessibility in digital design, particularly for disabled users, addressing challenges faced by novice and expert creators. His work spans topics like accessible prototyping tools, cultural considerations in design, and inclusive mixed reality interfaces. Education: BSc in Psychology, University of Dundee, 2012 MSc (Distinction) in User Experience Engineering, University of Dundee, 2014 PhD in Human-Computer Interaction (HCI), University of Dundee, 2019 Research Interests: Designing accessible digital systems for blind, deaf, and low-vision users Adaptable user interfaces for mixed reality and textured surfaces Cultural dimensions in accessibility pedagogy Authentication methods for visually impaired users Articles Trends: Recent work emphasizes AR/VR accessibility, cultural design frameworks, and haptic authentication. His studies often involve collaborations with global researchers and industry partners. Awards: Best Paper (MobileHCI 2022) CHI Honorable Mention (2023, 2024) NSF-funded research projects Advising & Grants: Active in mentoring graduate students and securing grants. His lab focuses on born-accessible AI tools and inclusive design education. Teaches courses like HCI Research Methods and Future Interactions. Labs/Teams: Co-leads the CAIR Lab, which develops technologies to bridge accessibility gaps in digital design and prototyping.
Dr. Joanna Deaton Bertram is an Assistant Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University’s Pratt School of Engineering. She concurrently holds an Assistant Professor appointment in Surgery, underscoring her interdisciplinary commitment to advancing medical robotics. Dr. Bertram leads a research laboratory devoted to the design, modeling, and control of robotic systems for surgical and interventional applications, working closely with Duke’s clinical and engineering communities. Education Ph.D. in Robotics, Georgia Institute of Technology, 2024 M.S. in Mechanical Engineering, Georgia Institute of Technology, 2024 B.S. in Biomedical Engineering, Georgia Institute of Technology, 2018 Research Interests Dr. Bertram’s research program is centered on medical robotics , with particular emphasis on continuum robotics and image-guided interventions . Her work integrates novel mechanical design with advanced control algorithms and smart materials to create robotic systems capable of navigating complex anatomical pathways. A hallmark of her approach is the incorporation of real-time fiber-optic shape and force sensing (using Fiber Bragg Grating technology) to provide surgeons with unprecedented feedback during procedures. Application domains include steerable needles for brachytherapy , robotic guidewires for endovascular surgery , and pediatric neuroendoscopy . Publication Themes Across more than fifteen peer-reviewed articles, Dr. Bertram has systematically advanced the state of the art in surgical robotics , fiber-optic sensing , and robotic system modeling . Her 2024 tutorial on Nitinol and Tungsten tendon attachment techniques provides practical guidance for building highly articulated continuum robots, while her 2023 series on the COAST guidewire robot demonstrates model-based design and simultaneous shape/force sensing for large-deflection medical devices. Earlier work explored 3D-printed patient-specific robotic tools and carbon-nanotube flexible sensors, illustrating a trajectory from fundamental sensor research to full robotic system integration. Scientific Recognition & Collaboration Although no major external awards are explicitly listed, Dr. Bertram’s publications in top-tier venues such as IEEE Robotics and Automation Letters , IEEE Transactions on Medical Robotics and Bionics , and IEEE/ASME Transactions on Mechatronics attest to strong peer recognition. She actively invites motivated graduate students, post-docs, and research staff to join her lab, fostering an open and interdisciplinary environment. Advising & Grants Dr. Bertram’s lab is presently recruiting trainees at all levels. While specific funded grants are not enumerated, her dual departmental appointments and extensive publication record suggest active federal or foundation support. Prospective students and collaborators are encouraged to contact her directly at joanna.d.bertram@duke.edu . Laboratory & Teams Dr. Bertram directs a laboratory within Duke University’s Pratt School of Engineering that collaborates closely with clinicians in the School of Medicine. The group focuses on rapid prototyping of medical devices, in-vitro and ex-vivo validation, and translation of robotic technologies to the operating room.
Gianmarco Pinton is an Associate Professor in the Department of Biomedical Engineering at the University of North Carolina at Chapel Hill. His research focuses on nonlinear ultrasound and mechanical wave propagation, with applications to medical imaging and therapy. He specializes in traumatic brain injury, shear shock waves, and ultrasound therapy. Ph.D., M.S., and B.S.E. in Biomedical Engineering/Physics from Duke University His lab develops physics and simulation tools for nonlinear wave propagation, aiming to create advanced diagnostic ultrasound methods. Key areas include traumatic brain injury, transcranial imaging, and therapeutic ultrasound. His recent work explores super-resolution imaging, brain motor circuits, and Alzheimer's disease vascular mapping using ultrasound. Article trends highlight innovations in transcranial ultrasound, super-resolution techniques, lung imaging, and neuromodulation. His publications address image degradation, contrast agents, and shear wave dynamics in neurological contexts.
