30 innovations from Bar-Ilan University, available for licensing, co-investment, or spin-out through BIRAD.
Lior Klein
A method, a non-transitory computer readable medium and a system for compensating for an electromagnetic interference induced deviation of an electron beam. The method may include obtaining measurement information about a magnetic field within an electron beam tool, the measurement information is generated by at least one planar Hall Effect magnetic sensor that is located within the electron beam tool; wherein the at least one planar Hall Effect magnetic sensor comprises at least one magnetometer integrated with at least one magnetic flux concentrator; estimating the electromagnetic interference induced deviation of the electron beam, the estimating is based on the magnetic field; and setting a trajectory of the electron beam to compensate for the electromagnetic interference induced deviation of the electron beam.
Shor Joseph
The demand for computational performance continues to rise exponentially, while power and thermal budgets impose strict limitations on integrated circuits (ICs). Modern processors employ multiple power domains, each requiring accurate current sensing for efficient power management. Existing current sensing techniques—such as shunt, Hall-effect, and fluxgate sensors—are either too large, too power-hungry, or too slow for integration at the scale of tens or hundreds of domains within a single chip. Digital ring-oscillator (RO) sensors have been explored, but they exhibit strong non-linearity, temperature, and supply dependence, which severely limit their accuracy. This research proposes a fundamentally new approach: a differential current-controlled oscillator (CCO) amplifier, which directly converts differential current or voltage into a frequency domain signal. Unlike conventional amplifiers, the CCO itself acts as both amplifier and analog-to-frequency converter, providing a highly compact, low-power, and fast solution suitable for power-gate current sensing in advanced processors. The proposed sensor targets an accuracy better than 0.2%, conversion time below 2 μs, power consumption under 20 μW, and area smaller than 0.01 mm², yet with performance significantly surpassing existing state of-the-art designs. Novel circuit techniques are introduced for non-linearity correction, temperature compensation, and common-mode rejection, including bias trimming, replica oscillators, and chopper stabilization. Preliminary simulations of a 65nm implementation demonstrate excellent linearity, 60 dB dynamic range, and temperature- and supply-induced variation below 0.02% when using replica compensation. This project will establish a new class of analog amplifiers based on differential CCOs, enabling fine-grained, energy-efficient current sensing for multi-domain processors, GPUs, and AI accelerators. The outcomes are expected to impact both industrial and academic fields by providing a compact, low-cost, low power sensing solution for power-management architectures and extending its use to applications such as biomedical monitoring, smart-grid systems, and energy-harvesting circuits.
Tischler Yaakov Raphael
We previously introduced a method and device for significantly enhancing the resolution of Raman spectroscopy measurements by using angle tuning of a Fabry-Perot (F-P) etalon in the beam path of a standard grating-based dispersive Raman spectrometer. Building on this innovation, we propose a novel configuration where Raman filters are placed after the F-P etalon. This configuration allows the F-P etalon to interact with both the coherent laser line and the excited Raman signal, enabling simultaneous measurement of the laser's spectral peak position and linewidth along with the stimulated Raman peak. By leveraging this dual measurement, we achieve simultaneous super-spectral-resolution of the Raman peak and the laser's spectral position, leading to an enhanced-resolution and determination of the absolute Raman peak shift, with both the laser and Raman peaks being super-resolved simultaneously. The method relies on computationally reconstructing the peak positions and linewidths of both the laser excitation and Raman scattering by comparing their angle-dependent intensity spectra to a physical model. The reconstruction provides ultra-high resolution for the linewidths and positions of both laser and Raman peaks in the same measurement, which can be achieved either by using a wide-enough range dispersive grating or by separately measuring the reflected or scattered laser signal with a photodetector. When analyzing a substance with a known Raman spectrum, this dual-measurement approach enables highly precise scattering spectroscopy using much more compact instrumentation. By combining the angle-dependent spectra from the Fabry-Perot etalon with a physical model, this method offers a streamlined and cost-effective solution for high-resolution spectral analysis, making it particularly advantageous for applications requiring compact and efficient setups. When analyzing a substance with a known single Raman peak, this dual-measurement approach enables highly precise scattering spectroscopy using just a pair of photodetectors, effectively eliminating the need for a full spectrometer. By combining the angle-dependent spectra from the Fabry-Perot etalon with a physical model, this method offers a streamlined and cost-effective solution for high-resolution spectral analysis, making it particularly advantageous for applications requiring super-compact and efficient setups.
Leshem Amir
// Technical problem of prior art OR any particular problem that the invention solves. // mandatory Autonomous driving, intelligent transportation systems, and smart cities are key industries that can be integrated with technologies of the Fourth Industrial Revolution, such as artificial intelligence, smart mobility, big data, and the Internet of Things (IoT). The introduction of autonomous vehicles can make more efficient use of roads by improving traffic management through interactions between vehicles and between vehicles and smart road infrastructure. Additionally, smart cities based on intelligent transportation systems are an important industry that can influence not only the automotive sector but also various fields such as urban development and logistics. The next-generation transportation system must efficiently and safely control a large number of entities, such as autonomous vehicles and traffic lights, operating on the roads. Existing traffic management systems utilize linear programming or multi-agent pathfinding techniques. Multi-agent pathfinding defines the traffic control problem as a graph and seeks optimal solutions through graph search algorithms. However, these traditional approaches do not account for the dynamic and real-time changes in traffic conditions and face limitations due to the high computational complexity required when dealing with large-scale traffic systems. To improve traffic congestion and prevent accidents, key technologies are needed that can process vast amounts of traffic data from vehicles and infrastructure quickly while adapting to real-time traffic environments. This study aims to define the traffic control problem using game theory, such as congestion games or Markov games, and develop scalable algorithms with low computational complexity based on deep multi-agent reinforcement learning. The goal is to develop core technologies that enable the implementation of an efficient transportation system. This research team is forming a Korea-Israel joint research group to develop core technologies for transportation systems in smart cities, based on the collaboration between the Korean team, which specializes in deep reinforcement learning, and the Israeli team, which has expertise in Markov games. Through international exchange and joint research between Korea and Israel, the team aims to lead the development of the key technologies for the next-generation intelligent transportation system proposed in this study and to foster the continuous advancement of future research. // Technical solution proposed by the invention // mandatory Composition of the Invention 1. A practical model-free algorithm based on the theoretical analysis of max-min optimization in multi-objective reinforcement learning. 2. A game theory-based modification to improve the sample and memory efficiency of the model-free max-min multi-objective reinforcement learning algorithm. Key Points to Emphasize 1. The algorithm is designed based on rigorous theoretical analysis and proof, which demonstrates better performance compared to existing heuristic algorithms. 2. Experimental results support that the algorithm can positively contribute to the design of efficient traffic systems. 3. A new methodology is proposed to significantly reduce the computational load and memory usage of the algorithm, thereby improving its efficiency. // mandatory The multi-objective reinforcement learning algorithm developed in this study can be extended beyond smart city traffic optimization to address problems in resource allocation in communication networks and in multi-agent systems. Such additional research will enhance the algorithm's versatility and contribute to maximizing its performance across various application domains. In communication networks, efficient resource allocation among various users and devices is a critical challenge. By utilizing this algorithm, resources can be dynamically optimized according to network traffic patterns, significantly improving both the efficiency and stability of the network. This approach can provide an innovative solution, particularly for resource management in high-speed communication networks such as 5G. In multi-agent systems, the collaboration between agents and the efficient use of resources are crucial. This algorithm can help address the "lazy agent" problem, where some agents use resources inefficiently in multi-agent environments. By resolving this issue, the algorithm enhances overall resource utilization across the system and enables balanced resource distribution among agents. This extension broadens the applicability across various industries and plays a key role in maximizing the performance of AI and autonomous systems.
Desiatov Boris
he invention relates to a hybrid optical phased array (OPA) platform combining thin-film lithium niobate (TFLN) photonic circuits with three-dimensional polymer end-fire antennas fabricated using two-photon polymerization. The architecture enables compact, broadband, and high-speed optical beam steering by integrating electro-optic phase control with elevated 3D antenna arrays. The technology is suitable for applications including LiDAR, free-space optical communication, and adaptive photonic systems.
Lior Klein
Planar Hall effect sensors capable of measuring multiple components of the magnetic field
Shor Joseph
This circuit measures internal transistor parameters.
Amikam Levy
The invention provides a method for designing and implementing frequency-domain filter functions in quantum systems through dynamically invariant control fields. Unlike traditional dynamical decoupling methods, which derive spectral properties post hoc from time-domain sequences, this method analytically constructs time-dependent Hamiltonians that realize arbitrary spectral responses, including multi-band and phase-sensitive profiles. The approach utilizes the formalism of dynamical invariants to ensure exact state evolution and robustness to drive-amplitude errors. Experimental implementation on nitrogen-vacancy (NV) centers in diamond demonstrates enhanced coherence preservation and signal selectivity beyond conventional control protocols.
Fridman Mordechai
The present invention relates to optical and quantum sensing systems that utilize synthetic temporal gauge fields to perform ultrafast and noise-resilient measurements. More specifically, the invention describes an interferometric sensing architecture in which an external signal is converted into a gauge-invariant temporal phase, analogous to a temporal Aharonov–Bohm (AB) effect, and is subsequently measured through interferometric or correlation-based detection. In the disclosed system, correlated optical modes are generated using a parametric process, such as four-wave mixing or parametric amplification, forming a temporal interferometric structure. The optical modes propagate through a dispersive or time-lens-based section, in which a time-dependent modulation is applied. This modulation produces a synthetic temporal gauge potential that induces a relative phase shift between the correlated modes. The accumulated phase depends on the temporal profile of the modulation and constitutes a gauge-invariant quantity analogous to the Aharonov–Bohm phase in conventional electromagnetic systems. After the gauge-induced phase is acquired, the optical modes are recombined in a second parametric or interferometric stage. The output signal depends on the accumulated gauge phase and is detected using intensity, interferometric, or correlation-based measurements. Because the sensed quantity is a gauge-invariant phase, the system exhibits reduced sensitivity to local perturbations, amplitude noise, and certain environmental fluctuations, thereby enabling more robust and accurate measurements. The invention enables sensing of a wide variety of external signals, including but not limited to: ultrafast phase or delay variations, time-dependent electrical or optical modulation signals, radio-frequency or microwave waveforms, dynamic optical path variations. The sensing mechanism is fundamentally different from conventional phase or amplitude modulation techniques, as the measured signal is encoded in a synthetic gauge phase rather than in a local field interaction. This approach allows ultrafast operation, compatibility with both classical and quantum optical regimes, and the possibility of enhanced sensitivity through parametric or correlation-based readout. The disclosed architecture may be implemented using temporal SU(1,1) interferometers, time-lens systems, dispersive optical elements, electro-optic modulators, or other time-dependent phase modulation devices. The system can operate with classical optical fields, single photons, or entangled photon pairs, and may be configured for various sensing, metrology, and signal-processing applications.
Teman Adam
This invention proposes a scalable and variation-aware algorithm for skew balancing of digital circuits. The skew balancing has two main objectives: the application of clockless wave-propagated pipelining (CWPP) and the reduction of dynamic glitch power. The algorithm achieves the balancing of the maximum and minimum delays through all internal gates of a combanatorial block by iteratively applying delays to the faster paths, while overcoming variation by using a skew balanced strobe signal for output capture.
Shuki Wolfus
The invention is an electromagnetic active protection system, designed to neutralize kinetic energy penetrators (such as armor-piercing rods) before they strike a vehicle's main armor. The system consists of an array of charged conductive plates; when a projectile traverses the array, it physically bridges the gap between electrodes, acting as a closing switch to trigger a rapid, high-current electrical pulse. This discharge exploits the "skin effect" to concentrate intense heat specifically at the projectile's tip, softening it significantly, while simultaneously generating an asymmetric Lorentz force that induces a yaw (tilt) angle. The combination of tip softening, shear stresses from differential thermal expansion, and mechanical tumbling causes the projectile to fracture or shatter upon impact, drastically reducing its penetration capability.
Fridman Mordechai
We suggest a spectrometer based on temporal optics. The spectrometer will enable spectral measurement of ultrafast signals and CW signals. Our spectrometer will provide the spectrum of single-shot input signals even when they have a high repetition rate.
