Grégoire Ithier is a Senior Lecturer in Physics at the Department of Physics, Royal Holloway, University of London. His research focuses on quantum engineering, decoherence, thermalization, mesoscopic physics, and random matrix theory. He leads the 'TypDyn' project exploring typical dynamics of embedded quantum systems, and co-leads the Leverhulme Trust-funded 'Generation and detection of quantum signals' initiative. His work bridges theoretical and experimental domains, including superconducting circuits and cryogenic microwave engineering. Ithier's research tools include advanced numerical methods (e.g., exact diagonalization) and statistical techniques (e.g., random matrix theory). Key Projects: TypDyn: Studies typical dynamics in embedded quantum systems (2015–present) QSimFP: Quantum simulators for fundamental physics (2020–2024) A new statistical theory of disordered quantum systems (2020–2024) His experimental work involves superconducting qubits, Josephson devices, and nano-superfluidic cavities. Grants include STFC and Leverhulme Trust funding. Recent publications address quantum thermalization, many-body systems, and random Hamiltonian analysis.
James McCann is an Associate Professor at the Carnegie Mellon Robotics Institute, where he leads the Carnegie Mellon Textiles Lab. He has been a faculty member since May 2017 after working at Disney Research Pittsburgh. McCann's academic journey includes a PhD from Carnegie Mellon advised by Nancy Pollard, followed by a postdoc at Adobe Research and a period developing video games. McCann's research focuses on building creative tools that operate in real-time and build user intuition, with particular emphasis on textiles fabrication and machine knitting. His work spans computer-aided fabrication, simulation, graphics, and creative tools development. He has pioneered systems for machine knitting design, including compilers for knitting instructions and tools for automatic conversion of 3D meshes to knitting patterns. His recent publications demonstrate a strong trend toward computational textiles, with significant contributions to knitting semantics, deployable textile structures, and applications of machine knitting in healthcare and robotics. McCann's work bridges computer science, robotics, and textile arts, creating practical systems for once-off manufacturing with industrial knitting machines. McCann actively mentors students, with current PhD candidates working on solid knitting machines, knit calibration, and assistive devices. His teaching portfolio includes courses on Real-Time Graphics, Algorithmic Textiles Design, and Game Programming. He has taught at CMU since 2017, developing innovative courses that blend computer science with physical fabrication. As director of the Textiles Lab, McCann oversees research projects spanning machine knitting, robotic painting, and real-time graphics systems. His lab develops practical tools for creators, emphasizing intuitive interfaces and real-time feedback that lower barriers to advanced fabrication techniques.
Andre Levchenko is the John C. Malone Professor of Biomedical Engineering at Yale University, with secondary appointments in the Department of Neurosurgery and affiliations with the Cancer Signaling Networks, Immunology, and the Yale Program in Neurodevelopment and Regeneration. His research focuses on systems biology, signal transduction, and cell-cell communication, utilizing microfluidics and computational modeling to study cancer progression, stem cell behavior, and neurological disorders. PhD, Columbia University MEng, Moscow Institute of Physics and Technology Levchenko's work explores how cells process dynamic signals to make critical decisions, particularly in glioblastoma migration, organoid development, and cardiovascular tissue engineering. His lab develops innovative microfluidic platforms and mathematical models to dissect multicellular communication and signaling networks. Recent publications highlight his contributions to understanding YAP-driven cancer invasion , NOTCH signaling in angiogenesis , and metabolic regulation of hypoxia responses . He has pioneered methods for organoid modeling and single-cell analysis , advancing precision in biological signaling studies. Scientific Awards : Computational Molecular Biology Post-Doctoral Fellowship (Burroughs Wellcome Fund) National Academies Keck Futures Conference Invitee Distinguished Guest Lecturer, University of Virginia American Asthma Foundation Early Excellence Award Fellow, American Institute for Medical and Biological Engineering Levchenko leads the Levchenko Lab at the Yale Systems Biology Institute, collaborating with institutions like Mayo Clinic and Yale Cancer Center. His research has received recognition in Faculty of 1000 and multiple journal highlights.
Ting Lu is an Associate Professor at the University of Illinois at Urbana-Champaign in the School of Biomedical and Translational Sciences, focusing on microbial synthetic biology and systems biology. Their research bridges biology, engineering, and physics to reprogram cellular functionalities through gene regulatory networks. Ph.D. in Biophysics, University of California at San Diego (2007) B.S. in Physics, Zhejiang University (2002) Ting Lu's work explores microbial ecosystems, synthetic gene circuits, and their applications in biotechnology and medicine. By combining experimental approaches with mathematical modeling, they investigate bacterial communication networks, metabolic pathways, and spatial dynamics in microbial communities. Selected research trends include microbial consortia engineering for bioremediation and bioproduction, complexity reduction in microbiomes, and predictive modeling of synthetic gene networks. Their publications span high-impact journals such as Nature Communications , Nature Chemical Biology , and eLife . Fellow, American Institute for Medical and Biological Engineering (2022) Future Insight Prize (2021) Donald Biggar Willett Faculty Scholar (UIUC) (2020) NIH Maximizing Investigators' Research Award (2019) NSF CAREER Award (2015) AHA National Scientist Development Grant (2012) Ting Lu's lab has received grants from NIH, NSF, ONR, and industry partners. They offer undergraduate research opportunities in synthetic and systems biology, and teach advanced courses such as BIOE 430 - Intro Synthetic Biology and BIOE 432 - Systems Biology .
Gert Cauwenberghs is a Professor of Bioengineering at the University of California San Diego (UCSD), affiliated with the Jacobs School of Engineering. He co-directs the Institute for Neural Computation and holds a visiting professorship at MIT. His research focuses on neuromorphic engineering, energy-efficient neural interfaces, and wearable biosensors. Key contributions include silicon-based adaptive neural circuits, implantable neural recording systems, and in-ear biosensing devices. Education: M.Eng. in Applied Physics (University of Brussels, 1988), M.S. and Ph.D. in Electrical Engineering (Caltech, 1989–1994). Prior roles include Professorships at Johns Hopkins University and Visiting Professor at MIT. Research Interests: Biomedical integrated circuits, neuromorphic computing, brain-machine interfaces, and energy-efficient neural systems. His work bridges neuroengineering and clinical applications, emphasizing adaptive intelligence and low-power designs. Recent Work: Development of femtojoule-efficient neural chips, high-density neural interfaces, and closed-loop wearable systems. Projects include neurobench benchmarking frameworks and RRAM-based neuromorphic hardware. Awards: NSF Career Award (1997), ONR Young Investigator (1999), PECASE (2000), IEEE Distinguished Lecturer (2003–2004). Grants & Labs: Active in NIH and DoD-funded projects, co-directs the UCSD Institute for Neural Computation. Collaborates with industry on neural interface technologies. Labs/Teams: Cauwenberghs Lab at UCSD focuses on integrated neuroengineering systems, including neural recording systems and neuromorphic computing architectures.
Changxi Zheng is an Associate Professor in the Department of Computer Science at Columbia University's School of Engineering and Applied Science (SEAS). He directs Columbia's Computer Graphics Group (C2G2) within the Columbia Vision and Graphics Center (CVGC). After receiving his PhD from Cornell University, he joined the faculty of Computer Science Department at Columbia, where he has established himself as a leading researcher in computer graphics and scientific computing. Dr. Zheng's research spans multiple areas of applied computer science with a particular focus on computer graphics and scientific computing. His work centers around developing numerical models for simulating physical phenomena involving complex motions such as fluids, bubbles, and thin rods, along with their resulting acoustic waves. Leveraging computational insights from these models, he devises methods for improving tangible object creation, enabling novel human-computer interactions, and developing software tools for acoustic and photonic devices. His research has attracted significant public interest and media coverage, including projects like FontCode, AirCode, and Computational Metallophone Design. His recent publications reveal a strong interdisciplinary approach, bridging computer graphics, physics simulation, machine learning, and hardware design. His work demonstrates consistent innovation in computational methods for simulating physical phenomena and applying these techniques to practical problems in 3D printing, acoustic modeling, and interactive systems. The breadth of his research spans from fundamental physics-based simulations to practical applications in industry. Columbia SEAS Dean's Fellow (for advised students) NSF Graduate Research Fellow (for Ruilin Xu) Snap Research Fellow (for Rundi Wu) CKGSB Fellow (for Yun Fei) Adobe Research Fellow (for Gabriel Cirio) Marie Sklodowska-Curie Individual Fellow (for Rundi Wu) Best Paper Award at ACM International Conference on Multimedia (ACMMM), 2019 Dr. Zheng actively mentors a diverse group of students, including current PhD candidates and postdoctoral researchers. His research group has received support from various sources that enable their innovative work in computational graphics and physics-based simulation. He has supervised numerous successful students who have gone on to positions at leading technology companies including Adobe, Tencent, Facebook, and academic institutions. As director of Columbia's Computer Graphics Group (C2G2) within the Columbia Vision and Graphics Center (CVGC), Dr. Zheng leads a vibrant research team focused on advancing the state of the art in computer graphics, physics-based simulation, and their applications. The group maintains strong collaborations with industry partners and academic institutions worldwide, fostering an environment of innovation and practical application of theoretical concepts.
Deborah Fox is Associate Professor in Midwifery at the University of Technology Sydney (UTS), Faculty of Health, and a core member of the Centre for Midwifery, Child and Family Health. She serves as Co-lead of the Maridulu Budyari Gumal SPHERE Maternal and Women's Clinical Theme and Chair of the National Publicly Funded Homebirth Consortium. In 2024, she received the Faculty of Health Dean's Academic Excellence Award for Research (Mid Career Researcher), following her 2021 award as Highest Performing Early Career Researcher from the School of Nursing and Midwifery. Her research focuses on optimizing physiological processes and positive experiences for women with complex pregnancies, with particular emphasis on the mediation of technology in midwifery practice. Current projects include evaluation of non-invasive fetal ECG beltless and wireless fetal monitoring in labor and birth, and examining the social, economic and environmental impacts of telemonitoring and telehealth in pregnancy and postpartum care. Dr. Fox's scholarly work demonstrates consistent focus on technology's role in maternity care, women's experiences of monitoring during labor, and innovative approaches to midwifery practice. Her recent publications show increasing emphasis on digital health solutions, AI applications in women's health, and pandemic impacts on maternal care systems globally. Faculty of Health Dean's Academic Excellence Award for Research (Mid Career Researcher) 2024 Highest Performing Early Career Researcher award from School of Nursing and Midwifery 2021 Editorial Board Member, Women and Birth journal Dr. Fox is actively involved in higher degree research supervision and has developed innovative teaching resources, including an Objective Structured Clinical Examination for perinatal mental healthcare. She is scheduled to spend three months as a Visiting Scholar at the University of Oxford in 2025.
Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.
Supratik Guha is a Professor at the Pritzker School of Molecular Engineering and Senior Advisor to Argonne National Laboratory's Physical Sciences and Engineering directorate. His work bridges industrial R&D with academic and national lab research, focusing on quantum computing , semiconductor materials , and sensor networks for water and soil monitoring. Guha leads Argonne’s quantum information science strategy and serves as Faculty Director for the University of Chicago Center in Delhi. Education: PhD in Materials Science (USC, 1991), BTech in Engineering Physics (IIT Kharagpur, 1985) Research interests span multiple domains: Quantum technologies focusing on erbium-doped oxides for quantum memory and quantum interconnects Sensor networks for soil and water quality monitoring using cyberphysical systems Nanofabrication techniques including controlled spalling for heterogeneous material integration Advanced memory technologies exploring ferroelectric and optically addressable memory at atomic scales Scientific awards include: Election to National Academy of Engineering (2015) APS Prize for Industrial Applications of Physics (2015) Vannevar Bush Faculty Fellow (2018) Fellow of Materials Research Society and American Physical Society IBM Corporate Award (2013) Advising notable students like Manish Kumar Singh (co-founder memQ ), Cheng Ji (now at Intel), and Vamsi Nittala (now at Micron Technology). His group contributes to major DOE , NSF , and USDA funded projects including: Q-NEXT - DOE National Quantum Information Center AIFARMS - NSF/USDA AI for Agriculture Institute Thoreau Project - Geospatial sensor networks Labs and teams operate across University of Chicago and Argonne National Lab , with facilities for molecular beam epitaxy , nanofabrication , and optical/electrical characterization . The group has spawned startups like memQ (quantum networking) and K1 Semiconductors (wide-bandgap material transfer).
Alanson Sample is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan (since 2018), leading the Interactive Sensing and Computing Lab. His research focuses on Human-Computer Interaction, Cyber-Physical Systems, and wireless technology innovations. He holds a PhD in Electrical Engineering from the University of Washington (2011), with prior postdoctoral work there developing implantable medical devices. Before academia, Sample held senior roles at Disney Research (2013-2018) as Executive Lab Director and Principal Research Scientist, leading teams in Robotics, AI, Computer Vision, and HCI. Earlier, he worked at Intel Labs (2008-2013) on energy harvesting for wearables and IoT. Key research themes include wireless power systems, embedded sensing, and privacy-aware technologies. Over 150+ publications span topics like magnetic sensing (MagDesk), acoustic gesture recognition (HandSAW), and privacy-preserving activity tracking (PrivacyMic). His work bridges academic and industry innovation, particularly in scalable interactive systems and medical technology. Notable projects include the Quasistatic Cavity Resonance wireless charging system, RFID-based sensing platforms (WISP), and wearable health monitoring devices. His lab develops hardware-software co-design frameworks for energy-efficient embedded systems. Current research emphasizes medical applications, smart infrastructure, and ubiquitous computing interfaces.
David Lindlbauer is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University, where he leads the Augmented Perception Lab and co-directs the CMU Extended Reality Technology Center. His research bridges human perception, extended reality (AR/VR), and computational interaction techniques, focusing on developing systems that dynamically adapt interface elements based on environmental context, user cognition, and task requirements. He completed his PhD at TU Berlin under Prof. Marc Alexa and held a postdoctoral position at ETH Zurich's Advanced Interactive Technologies lab. His work has been published extensively at top venues including ACM CHI, UIST, and IEEE VR, with research themes spanning gaze tracking, spatial audio optimization, haptic feedback, and multimodal notification systems. Media outlets like MIT Technology Review and Fast Company Design have featured his innovations. Dr. Lindlbauer has received prestigious grants from Meta, NSF, and ETH Zurich, and serves on program committees for CHI, UIST, and ISMAR. He has been recognized with Best Paper awards at ISS 2023 and CHI 2016, and his lab develops tools like MineXR for personalized XR interfaces and RealityReplay for temporal change visualization in mixed reality environments.
Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award
Prof. dr. ir. C.H. (Caspar) van der Wal is a Full Professor in Physics of Quantum Devices at the Faculty of Science and Engineering , University of Groningen. His research focuses on spintronic and quantum information functionalities using electron/nuclear spins in semiconductor devices, combining quantum optical and electron transport methods. PhD in Quantum Transport (Delft University of Technology, 2001) Postdoc in Quantum Optics at Harvard University (2001-2003) Scientific Director of Zernike Institute for Advanced Materials (2016-2022) Research keywords include Quantum Optics , Spintronics , Quantum Information , and Semiconductor Physics . Recent work explores 2D/3D semiconductor heterostructures , spin defects in SiC , and transition metal dichalcogenides . His scientific contributions have earned him the NWO-Vidi Grant (2005) , ERC Starting Grant (2011) , and multiple teaching awards. Publications since 2001 span topics like quantum superpositions in superconducting circuits, spin relaxation in quantum dots, and telecom-ready spin centers in silicon carbide. Grants : NWO-Vidi (2005), ERC Starting Grant (2011) Leadership : Scientific Director, Zernike Institute (2016-2022) Teaching : Teacher of the Year (2015), Education Prize (2012) Current affiliations include the Physics of Nanodevices group at the Zernike Institute for Advanced Materials. Collaborations span institutions like MIT, Harvard, and AMOLF.
Ankit Saxena serves as Assistant Professor in the Department of Mechanical Engineering at the University of Wyoming since 2024, focusing on innovative applications of additive manufacturing in structural engineering and materials science. His work bridges theoretical design with practical implementations in energy, aerospace, and robotics systems. Education: Ph.D. in Mechanical Engineering, Penn State University (2024) M.S. in Mechanical Engineering, Penn State University (2020) B.S. in Mechanical and Automotive Engineering, Delhi Technological University (2016) Dr. Saxena's research centers on developing adaptive stiffness structures , meta-materials , and functionally graded systems through advanced additive manufacturing techniques. His work specifically targets energy applications (nuclear, wind, hydrogen, oil/gas) and aerospace challenges, with emphasis on structural health monitoring and vibration damping. The SUMMIT Lab under his direction creates multi-functional materials enabling shape morphing and self-strengthening properties for next-generation engineering solutions. His publication record (2020-2024) reveals a consistent trajectory toward multi-physics meta-material design , with dominant themes in TPMS lattice optimization, fluid-structure interaction systems, and medical robotics applications. Key methodological contributions include novel fluid accumulator integration, laser powder bed fusion parameterization, and non-pneumatic tire architectures. Scientific Recognition: ASME Graduate Teaching Fellow (2022-2024) Harold F. Martin Graduate Assistant Outstanding Teaching Assistant Award (Penn State, 2023) Dr. Saxena teaches core materials courses (ME 3450: Properties of Materials; ME 4150: Mechanical Behavior of Materials) while expanding his research group through active recruitment of PhD candidates for 2026. His teaching philosophy emphasizes practical applications of theoretical concepts, recognized through multiple Penn State teaching fellowships. The SUMMIT Lab operates at the intersection of Wyoming's energy priorities and cutting-edge manufacturing research, maintaining strategic focus on renewable energy infrastructure and aerospace applications through metal additive manufacturing innovations.
Sumeet Kumar Gupta is an Associate Professor in the Department of Electrical and Computer Engineering at Purdue University. His academic career spans from his current role to a prior Assistant Professorship at Pennsylvania State University (2014-2017) and an engineering position at Qualcomm Inc. (2012-2014). He holds a PhD in Electrical and Computer Engineering from Purdue University (2012), an M.S. from the same institution (2008), and a B.Tech in Electrical Engineering from IIT Delhi (2006). B.Tech, Electrical Engineering, IIT Delhi (2006) M.S., Electrical and Computer Engineering, Purdue University (2008) PhD, Electrical and Computer Engineering, Purdue University (2012) Dr. Gupta's research focuses on neuromorphic computing, low power variation-aware VLSI design in emerging nanotechnologies, device-circuit co-design, and nano-scale device modeling/simulations. His work addresses challenges in ferroelectric materials, crossbar arrays for deep neural networks, and energy-efficient AI hardware. Recent publications (2025-2024) highlight trends in: Ferroelectric HfO2/HZO thin films Compute-in-memory architectures Variability/stochasticity analysis Machine learning for device optimization Interconnect resistance/temperature effects AI hardware fault tolerance Scientific Awards & Recognitions: DARPA Young Faculty Award (2016) Early Career Professorship, Penn State (2014) 6th TSMC Outstanding Student Research Bronze Award (2012) Magoon Award (Purdue) Outstanding Teaching Assistant Award (Purdue, 2007) Intel PhD Fellowship (2009) His professional journey includes academic appointments at Purdue University (2020-present, Associate Professor) and Pennsylvania State University (2014-2017, Assistant Professor) after industry experience at Qualcomm Inc. (2012-2014). He maintains IEEE and EDS membership while publishing over 100 refereed works.
