About

Amit Lal is a professor in the School of Electrical and Computer Engineering at Cornell University, with additional affiliations in Biomedical Engineering, Applied Engineering Physics, and Mechanical and Aerospace Engineering. He obtained his Bachelor of Science in Electrical Engineering from Caltech in 1990 and his Ph.D. in Electrical Engineering from the University of California, Berkeley, where he conducted doctoral research at the Berkeley Sensors and Actuators Center focusing on ultrasonic MEMS. Prior to his current position, he worked at the University of Wisconsin-Madison as an assistant professor. Prof. Lal has made significant contributions to the field of microsystem engineering, holding more than 30 patents and publishing over 190 research papers. His research interests include developing integrated microsystems using micro and nanoscale fabrication techniques, with current focus areas such as gigahertz ultrasonic chip-scale communications, sensing, and computation; near-zero power sensors for long-lifetime IoT; ultrasonic inertial sensors based on surface acoustic waves; long-term stable sensors utilizing lasers locked to optical transitions of alkali metals; bulk PZT sensors and actuators; and chip-scale manipulation of electron and ion beams. He directs the SonicMEMS Laboratory, which explores diverse topics aimed at transforming technological capabilities. Prof. Lal has served as a Program Manager at DARPA, managing multiple programs in navigation, low-energy computation, bio-robotics, and atomic microsystems, and has received numerous awards including the NSF CAREER award, the Whitaker Foundation Award, the Department of Defense Exceptional Service Award, and a Best Program Manager Award. His work has been recognized through best paper awards at IEEE conferences. He is actively involved in various professional service roles, including technical program committees and journal reviews, and is a member of several research centers and consortia.

Research topics

• Computer Science
• Physics
• Acoustics
• Artificial Intelligence
• Materials science
• Optics
• Condensed matter physics
• Remote sensing
• Optoelectronics
• Ecology
• Telecommunications
• Computer vision
• Chemistry
• Biology
• Electrical engineering
• Environmental science
• Algorithm
• Geology
• Nanotechnology
• Computer graphics (images)
• Agronomy

Selected publications

• Early Detection of Botrytis Cinerea Growth via GHz Ultrasonic Imaging of Agar Depletion

  2025-09-15

  articleSenior author

  Botrytis Cinerea is a destructive fungal pathogen responsible for significant agricultural losses worldwide. In this paper, we demonstrate a GHz ultrasonic imaging method to detect early fungal growth by monitoring nutrient agar depletion. A sessile droplet drying model was developed to establish baseline evaporation dynamics, which were validated experimentally. Using a custom-built portable 1.85 GHz ultrasonic imager provided by Geegah Inc., we correlated return voltage signals with agar thickness, allowing quantification of Botrytis-induced agar depletion. Control droplets exhibited predictable drying and stabilization, while inoculated samples displayed accelerated agar reduction and demonstratable thickness variation in comparison to control experiments. These results suggest that GHz ultrasonic imaging offers potential for a rapid, portable, easy to use platform for on-site pathogen detection, enabling earlier intervention compared to traditional methods.

  PublisherDOI

• A Compact High Frequency In-Air Ultrasound Assisted Disc Levitator: Simulations

  2025-09-15

  articleSenior author

  We demonstrate the feasibility of a compact, high-frequency (>1 MHz) in-air levitator capable of supporting heavy masses (>100 mg) with enhanced trap stiffness and robust shock tolerance. Theoretical analysis highlights the benefits of operating at high frequency for increasing radiation force and acoustic spring constant. Finite element modeling is employed to determine an optimal architecture, examining the influence of transducer activation schemes, disc insertion, and slit geometries on the resulting trap field.

  PublisherDOI

• Process-Aware Digital Twins by Deep Learning for DUV Photolithography and Plasma Etch

  IEEE Transactions on Semiconductor Manufacturing · 2025-06-23 · 1 citations

  article

  Computer representations of the structure, context, and behavior of physical systems are critical components of computational system optimization. Traditionally, such optimization is done by iterative physical experiments, which can be expensive both in time and resources. In this paper, these computer representations, called digital twins, are developed primarily using SEM images and equipment process parameters. HyperPix2Pix, the proposed methodology of the digital twins, is a deep neural network that uses SEM images of the input structure together with equipment process parameters to predict the output SEM images. We demonstrate HyperPix2Pix on a DUV photolithography stepper and plasma etcher. HyperPix2Pix predicts output images that closely match the experimental output images and have very similar critical dimensions. Compared to previous work, HyperPix2Pix includes the effects of process parameters through multimodal learning, elucidating the role of different parameters in nanofabrication processes and their effects on critical dimensions of the resulting structures.

  PublisherDOI

• Process-Aware Digital Twins for Nanofabrication Processes

  2025-05-05 · 1 citations

  article
  PublisherDOI

• GHz Ultrasound for Quantitative Oocyte Mechanobiology

  2025-06-29

  article

  This paper presents a quantitative characterization method for oocyte mechanobiology that is performed using an AlN piezoMEMS GHz ultrasound transducer array. This is the first demonstration of a GHz ultrasound imaging array (128×128) with high spatial resolution (50×50 μm/pixel) being used for quantitative characterization of a single oocyte cell with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\sim 80\mu \mathrm{m}$</tex> diameter, which provides a pathway to an accurate assessment of mechanical properties for the oocyte selection process in assistive reproductive technologies (ART) [1]. Our ultrasound pulse-echo reflectometry measurements performed at ~1.8GHz using this array showed that we can detect the acoustic impedance changes between 1.89±0.23 MRayl and 1.61±0.28 MRayl depending on the presence and condition of zona pellucida (ZP) to make inferences about oocyte health.

  PublisherDOI

• Rapid Sensing of Extrusion Based Printed Ink Properties Using Ghz Ultrasonic Imager

  2025-06-29

  articleSenior author

  Printed electronics enable future MEMS and electronic systems to create flexible, customizable microsystems using a wide variety of materials. Extrusion-based printing is cost-effective but suffers from ink aging, causing linewidth variations that impact performance. Environmental factors, remote operation, and viscos

  PublisherDOI

• Towards GHz Ultrasound Enabled Noninvasive Hydrogel Metrology for Mechanobiology

  2024-01-21 · 1 citations

  article

  This paper presents a noninvasive method for the measurement of transient mechanical properties for hydrogel swelling using a CMOS-integrated piezo MEMS ultrasound imager operating at <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∼</inf> 1.8 GHz. The noninvasive measurement and tuning of hydrogel stiffness is crucial for creating cell culture environments with different mechanical properties to study the mechanical interactions between cells and the surrounding matrix [1]. We present a novel method for real-time and noninvasive measurement of hydrogel swelling using GHz ultrasound reflectometry. We measured five samples from seven different batches with water contents varying from zero (dry) to 1000 μL water per 100 mg of hydrogel—the ultrasound-based measured bulk modulus of hydrogel samples (~1-4.5 GPa) verified by micro indentation showing closely matching trends.

  PublisherDOI

• Combining gas vesicle acoustic contrast agents with field-deployable GHz frequency ultrasonic chips to detect gene expression in sentinel microorganisms

  2024-09-22

  articleSenior author

  Continuous multi-modal measurements of the physical, chemical, and biological properties of soil are key to the advancement of agriculture, farming, and the study of the soil microbiome. Here, we demonstrate that the Geegah GHz imaging platform can detect changes in the acoustic impedance of bacterial colonies due to the presence of gas vesicle contrast agents. We couple the production of these contrast agents to an external nutrient stimulus, further highlighting that the imager may be used to sense gene expression changes in living organisms. This proof-of-concept experiment unlocks future avenues to measure biological properties of soil by coupling the natural sensing capabilities of soil microorganisms with the Geegah GHz imaging platform by way of gas vesicle genetic circuits.

  PublisherDOI

• Sonic Fourier Transform Imaging Using GHz Ultrasonic Transducer Array

  2024-01-21 · 2 citations

  articleSenior author

  The Fourier transform is one of the most widely used mathematical tools for numerical solutions and understanding signals and images. In the digital domain, the 2D fast Fourier transform (FFT), which has a computational complexity of O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> logN <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), is often used. The compute time can be a bottleneck for many real-time edge applications that require Fourier computation at high frame rates. A solution is to use an ultrasonic hardware accelerator that can compute Fourier transform and convolution at a drastically higher speed and lower power, achieving O(N) complexity [1] – [5]. Presented in this work is the first experimental demonstration of the Sonic Fourier Transform (SonicFT) measurement using a piezoelectric MEMS framework. AlN transducers were used as transmitters to simulate different images being input into an ultrasonic hardware accelerator. The transmitted ultrasonic wavefronts were imaged electronically, using a GHz ultrasonic imager operating at 1.85 GHz, consisting of a 130nm CMOS-integrated 128 by 128 array of 50x50μm AlN transducers. The images obtained are consistent with the expected Fourier transforms, demonstrating an ultracompact Fourier transform capability.

  PublisherDOI

• Ferroelectric AlBN films by molecular beam epitaxy

  Applied Physics Letters · 2024-08-12 · 15 citations

  articleOpen access

  We report the properties of molecular beam epitaxy deposited AlBN thin films on a recently developed epitaxial nitride metal electrode, Nb2N. While a control AlN thin film exhibits standard capacitive behavior, distinct ferroelectric switching is observed in the AlBN films with increasing Boron mole fraction. The measured remnant polarization Pr∼15μC/cm2 and coercive field Ec∼ 1.45 MV/cm in these films are smaller than those recently reported on films deposited by sputtering, due to incomplete wake-up, limited by current leakage. Because AlBN preserves the ultrawide energy bandgap of AlN compared to other nitride hi-K dielectrics and ferroelectrics, and it can be epitaxially integrated with GaN and AlN semiconductors, its development will enable several opportunities for unique electronic, photonic, and memory devices.

  PublisherOA PDFDOI

Recent grants

• Self-Powered Ultra High Vacuum Technology for Harsh Environment Wireless Sensors

  NSF · $330k · 2011–2017

• EAGER: Long Term Reliable Neural Recordings and Neuro Modulation Using GHz to THz Ultrasonics

  NSF · $150k · 2017–2021

Frequent coauthors

• Benyamin Davaji

  Boston University

  79 shared

• Jaibir Sharma

  Institute of Microelectronics

  57 shared

• Ved Gund

  Cornell University

  54 shared

• Justin Kuo

  Cornell University

  53 shared

• Serhan Ardanuç

  Cornell University

  50 shared

• Eldwin J. Ng

  Institute of Microelectronics

  38 shared

• Rajesh Duggirala

  Intel (United Kingdom)

  27 shared

• Srinivas Merugu

  Agency for Science, Technology and Research

  27 shared

Labs

• Cornell SonicMEMS LabPI

Education

• Ph.D.

  University of California Berkeley

  1996

• BSEE

  California Institute of Technology

  1990

Awards & honors

• NSF CAREER Award
• Whitaker Foundation Award
• Department of Defense Exceptional Service Award
• Best Program Manager Award