Mikhail Shalaginov

Excited to lead this effort on AI for Wireless Chip Design, as one of the three anticipated awardees of the $30 million dollar inaugural proposal call from National Semiconductor Technology Center (Natcast.org), established through the US Chips and Science Act by the Biden-Harris administration. AI-enabled RFIC design started as a small effort from our group (nearly unfunded) about four years ago. Without any prior work, we went through quite a bit of sweat, tears, and failed ideas, before we demonstrated (in 2022) the first examples of how AI can discover new architectures for wireless chips, and allow rapid designs on demand. This has now evolved into a substantial effort across academia, industry and government. Expectedly, a highly multi-disciplinary effort--immensely proud of my students, who had to learn multiple areas from complex chip design to electromagnetics to AI, and build the foundations from scratch. Congrats to Emir Ali Karahan, Zheng Liu, Jonathan Zhou, and all the members of the group. Excited to partner with Hossein Hashemi, Ioannis Savidis, Xuan 'Silvia' Zhang, Mengdi Wang, Raytheon, Cadence Design Systems, and Keysight Technologies. https://lnkd.in/eZFfnyPY #AI #RFIC Princeton University, Princeton Engineering, Princeton ECE, Princeton Research

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Read our most recent, invited paper, entittled "Experimental Investigation of a Recurrent Optical Spectrum Slicing Receiver for Intensity Modulation/Direct Detection systems using Programmable Photonics" in Journal of Lightwave Technology. The paper experimentally shows the equalization of 64 Gb/s (32 Gbaud PAM-4) signals using a photonic accelerator enabled by recurrent optical spectrum slicing in programmable photonics. By equalizing even 80 km of 64 Gb/s PAM-4 transmission in C-band, we prove that our idea can offer an appealing, low-power consumption, solution in highly dispersive channels. Kudos to Kostas Sozos, Francesco Da Ros, Metodi Yankov, George Sarantoglou, Stavros Deligiannidis and Charis Mesaritakis, Ph.D and to PROMETHEUS Horizon Europe project, Villum Fonden OPTIC-AI and #NOOKHFRI projects. #programmablephotonics #neuromorphiccomputing #photonicaccelerators #opticaltransmission https://lnkd.in/dT-8_wHs

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https://lnkd.in/ethDyF98 Anis Rahman Chief Technology Officer, President Applied Research & Photonics, Inc. Harrisburg, PA, United States Silicon carbide (SiC) is an important semiconductor for high temperature and high voltage applications such as in electric vehicles. The SiC boule is grown by seeded sublimation deposition process where the primary ingredients viz. carbon (C) and silicon (Si) are sublimated at very high temperature. Eddy and Gaskill [1] indicated that the variations in the atomic ratio of Si to C in the vapor phase that arise from feedstock granularity is difficult to minimize during growth. It is also difficult to avoid impurities arising from both in the SiC feedstock and in the graphite-insulation used in the growth reactor. Additionally, radial, and axial thermal profiles in the reactor and boule may cause polycrystallinity, grain boundary formation, and other defects in the lattice, which may lead to macro- and micro-domain formation. Because the understanding of materials’ properties at the extreme growth temperature of ~2200°C is incomplete, the boule growth modeling efforts are based on extrapolated parameters. Thus, an accurate experimental quantification is very important. The evolution of domain walls in single crystalline SiC is therefore very difficult to eliminate, and they stay put in the boule. This paper investigates SiC substrates and epitaxial SiC wafers via cameraless T-ray imaging route. T-ray images reveal significant features that were not seen before. “Dendrimer dipole excitation (DDE)” T-ray source was used that generates wider terahertz bandwidth (0.1 THz to ~30 THz) and generate >200 milliwatts of CW power without requiring a femto-second pulsed laser. An instrument system, the T-ray nanoscanning and 3D imager (TN3DI), has been designed around the DDE T-ray source that was used for the present investigations. Here the wafer was directly mounted on the nanoscanner and the whole wafer was scanned for imaging. T-ray images (see Fig. 1) have revealed some patterns in the SiC wafers of the present investigation that were unseen previously. Optical images and T-ray images were compared side-by-side that shows that the T-ray exhibits higher sensitivity and clearer images thus reveals internal intricate pattern not visible by the optical and X-ray technique. Here, we propose that the unique patterns observed from the T-ray images are due to some kind of domain formation in the boule that has remained in the wafers even after slicing and polishing. This hypothesis is further strengthened via T-ray micrograph of different wafers that exhibit many micro-domains on the epi layer of a 100 mm SiC wafer. Thus, the T-ray images have revealed some intricate patterns for the first time that are present in the SiC wafers. Details of the principle and experimental will be presented.

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You can make workflows and their data FAIR with Sim2Ls.

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MODULAR SCALABLE Silicon Photonics GUARANTEED: INSIDE OpenLight WITH Adam Carter. We get many questions from young photonics companies trying to scale up production to serve new markets and increase their turnover. And that’s where Optica can help. We have access to the leading CEOs and CTOs in over 600 photonics businesses who have a wealth of experience and are willing to share their advice with others. NEW INTERVIEW SERIES In this long-form interview series hosted on our YouTube channel, we explore the business strategies being developed by industry leaders. I’m joined at the questioner's table by Michael Hochberg, an authority in the Silicon Photonics industry. https://lnkd.in/d9TPJexs For this edition, we sat down with Dr Adam Carter, the CEO at OpenLight. Formed as a joint venture between Juniper Networks and Synopsys Inc, the company has a proven ability to integrate lasers, optical amplifiers, DFBs, EA-modulators, and photodetectors on a single chip. They grant their customers access to a comprehensive library of photonics components that are heterogeneously integrated on the PASIC. OpenLight’s approach removes the need to source and package separate lasers on silicon photonics chips and improves device performance. In our interview, Adam explains that their approach will be key to producing next-generation, pluggable transceivers for datacenters and AI/ML applications. We discuss their partnership with Optica corporate member Jabil. This move is to meet the needs of the global Silicon Photonics market, which, according to some reports, is expected to grow in value to around US$8.3 billion by 2030. Earlier this year, they also announced strategic partnerships with Optica members like VLC Photonics (Hitachi Group), an end-to-end integrated photonics services firm, now part of the Hitachi group. VLC Photonics now offers design and test services using the OpenLight process design kit (PDK). The collaboration increases the number of designs that OpenLight can support at any one time on the Tower Semiconductor PH18DA process. We also spotted a similar agreement with Optica corporate member Spark Photonics in the US. Who is Adam? Dr Adam Carter has more than 25 years of experience at large and small companies. He is perhaps best known for being chief commercial officer at Foxconn Interconnect Technology (FIT), Cisco, and, earlier, at Oclaro at the time of its acquisition by Lumentum. Originally from the UK, we started by asking Adam to sketch what it was like when the Telecom Bubble burst at the start of this Millennium. I hope you enjoy this conversation. Feedback encouraged.

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📢 New Paper Alert: Bridging molecular modeling and experimental insights for conductive metal-organic framework (MOF) supercapacitors. Our latest work introduces a multi-scale circuit model that links molecular dynamics with experimental data. By accounting for crystallinity, crystal shape, and porosity, the model provides a comprehensive approach to understanding and predicting the electrochemical performance of conductive MOF supercapacitors ⚡. 🌍 Why it matters: Advancing the design of MOF-based energy storage systems is key to achieving higher efficiency, better scalability, and sustainability in next-generation supercapacitors. This work offers new perspectives for both theoretical modeling and practical implementation. A big thank you to the brilliant team behind this work: Liang Niu, Zhou Liu, Ding Yu, Ming Chen, and Guang Feng 🙌. And here's the link to our paper 👇👇👇👇 https://lnkd.in/e_4ZHxii #MOF #Supercapacitors #EnergyStorage #Modelling #Electrochemistry

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This is what I love doing: reading about new and exciting research that's pushing the bar forward. In this case, let's break the paradigm holding back transistor power! New physics, new potential. 2D materials in TFETs offer a potential future for rewriting the rule book when it comes to efficiency. https://lnkd.in/eC5f42AY

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In our new JCP paper, we propose a novel IBM that suppresses the non-physical pressure jump in the traditional continuous forcing IBM: One-side diffuse-interface immersed boundary method for compressible flows https://lnkd.in/geKu7jYA

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🌟 New Research Alert 🌟 We are excited to share this cutting-edge paper published in APL Photonics! 📄 Title: Ultra-high precision comb-locked terahertz frequency-domain spectroscopy of whispering-gallery modes 🔍 Highlights: • Demonstrates a novel frequency-domain terahertz spectrometer based on a comb-locked frequency synthesizer • Provides absolute frequency calibration with outstanding stability and repeatability • Achieves kilohertz-level frequency resolution in ultra-high precision spectroscopy of whispering-gallery-mode resonators For anyone interested in the latest advancements in terahertz spectroscopy, this is a must-read! Check out the full paper here: Read the article https://zurl.co/V2bO 👈 #Photonics #TerahertzSpectroscopy #FrequencyComb #Research

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I will give a talk at the IEEE San Francisco Bay Area (SFBA) Nanotechnology council on 8/22 in Sunnyvale, CA. See you soon there. https://lnkd.in/g65N-g-n 2D Materials: Innovations for Future IC Applications Prof Jeongwon Park, U Nevada Reno In-Person Meeting. Register: Here Thurs Aug 22 11:30am: Networking & Pizza Noon-1PM: Seminar; followed by Lab Tour Cost: $4 to $6 Location: Covalent Metrology, 923 Thompson Place, Sunnyvale Note this is a change from our previous venue For more info on Covalent - scroll down This talk will introduce various technologies based on 2D materials and discuss possible applications. In addition, traditional silicon-based devices and nanotechnology-enabled high-performance devices will be discussed. Read More: Current Prospects and Challenges in Negative-Capacitance Field-Effect Transistors Dr. Jeongwon Park joined the Department of Electrical and Biomedical Engineering at the University of Nevada, Reno, NV, USA, as an Associate Professor in July 2019. Prior to that, he was an Associate Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, Canada (2016-2021, currently Adjunct Professor) and a scientist at SLAC National Accelerator Laboratory, Stanford University, USA (2014 -2016). For six years (2008-2014), he served as a senior technologist to support the corporate chief technology officer (CTO) and business units at Applied Materials, USA. In addition, he has been a guest researcher at the Lawrence Berkeley National Laboratories (2005-2008), an adjunct professor in the Department of Electrical Engineering at Santa Clara University (2009-2016), and a visiting scholar in the Department of Electrical Engineering at Stanford University, CA, USA (2013-2014). He received his Ph.D. (2008) in materials science and engineering from the University of California, San Diego, USA. He is a senior member of IEEE and the National Academy of Inventors. Covalent Metrology is a disruptive analytical services laboratory and digital platform based in Sunnyvale, California. Its mission is to empower technological innovation with superior data and insights. Covalent makes it easier and more affordable to access the metrology data necessary for strategic decision-making: facilitating faster research, development, and production of advanced materials and devices. It is dramatically changing the materials characterization service landscape with the combination of its modern data platform, world-class analysts and top-notch customer service, state-of-the-art analysis instrumentation, and strategic partnerships. Covalent now has over 500 customers in 30+ industries. Learn more at: https://lnkd.in/gtRnsW_P.

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BRISTOL Optica QUANTUM SUMMIT REVIEW: I am back home, time to wrap up our coverage of the 3rd Optica Quantum Industry Summit. While most discussions were behind closed doors, it’s clear last week was packed with practical insights, strategic shifts, and a few surprises. For the first time, the summit was focused on the needs of end users from Airbus, Cisco, Qubit Pharmaceuticals and NVIDIA among others. Here are my top highlights: Number 1. Companies are opening up to partnerships. A great example is PsiQuantum. Historically, it has focused on fault-tolerant quantum computing, and it has been seen by the community as a closed and secret company, but now things have changed. At the summit, they were actively looking for partners and they’re now licensing components through GlobalFoundries to accelerate innovation. With their expansion into technologies like SiN and BTO, along with new facilities near Brisbane airport and the UK, they have become the flagship for the industry to follow. Another example is ORCA Computing’s collaboration with ID Quantique. They’re integrating cutting-edge single-photon detectors into the PT-2 system for quantum-enhanced AI. I was personally impressed with Pixel Photonics, they developed a superconducting nanowire single-photon detector compatible with silicon photonics. Now they are actively seeking a foundry partner to scale their SNSPD building blocks—mirroring GlobalFoundries’ support for PsiQuantum’s wafer-level production. 2. QKD is facing hurdles. Quantum Key Distribution is under scrutiny. U.S. and international cybersecurity agencies still hesitate to trust QKD for classified communications. But companies from all over the world see the UK and EU as testbeds to prove the resilience of QKD technology. BT is driving early adoption. However, in their view, miniaturization will be critical. This explains the surge in interest around Photonic Integrated Circuits (PICs) from companies like LuxQuanta, Qunnect, and KETS Quantum Security, with support from players like Cornerstone and Light Trace Photonics. 3. Quantum chips need hybrid integration. For Photonic Quantum Computing to succeed, we need broad wavelengths, accurate detectors and stable modulation. We need hybrid integration of different PIC platforms. At the summit, we saw the rise of LIGENTEC, LioniX International and QuiX Quantum: With their low-loss silicon nitride platforms. ALUVIA: with their aluminum oxide platform offering a wide wavelength range, crucial for ion-based quantum systems (as companies like Oxford Ionics demand). And Quantum Computing, Inc. Their thin-film lithium niobate offers unmatched stability for ultra-precise modulation. 4. Investors are cautious. While quantum is still exciting, having the right business plan and early revenue streams is becoming essential. Do not miss the 4th edition, when we return to Bristol, on November 10th and 11th 2025, and we will have a big surprise for you. Look where we are going for dinner.

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📖 Our latest work: when nonlinear optics "emulates" the properties of quantum optics. Research at the intersection of these two fields. https://lnkd.in/efhkWBJR #quantumoptics #physics #quantumentanglement #quantum #Nonlinear_optics #NonlinearOptics #QuantumPhotonics #QuantumSensors #QuantumTechnology #QuantumSensing

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The third of our several #2Dsemiconductor strain papers this year came out last Friday. Lauren Hoang (co-advised with Andrew Mannix) led this study, and found that Ni contacts impart strain to monolayer WS2, improving its electron mobility and contact resistance. Many groups use Ni contacts, which seems to have reasonably low contact resistance despite its non-ideal work function. The built-in strain appears to play an important role in this! This is related to earlier work led by Marc Jaikissoon, who found similar effects with Ni-capped Au contacts to MoS2 (see https://lnkd.in/gQ9KZB4j). The size of the contacts and the annealing history (i.e. thermal budget) also matter! All these things are very relevant for the fate of #2Dmaterials in electronics, because controlling strain at the nanoscale is something that the silicon industry already knows how to do. Lauren's work is out in Nano Letters: https://lnkd.in/gs28-aFH

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a groundbreaking achievement in collaboration with Sandia National Laboratories successfully demonstrating training of a 1 trillion parameter AI model on a single CS-3 system. Trillion parameter models represent the state of the art in today’s LLMs, requiring thousands of GPUs and dozens of hardware experts to perform. By leveraging Cerebras’ Wafer Scale Cluster technology, researchers at Sandia were able to initiate training on a single AI accelerator – a one-of-a-kind achievement for frontier model development. Cerebras Systems #ai #hpc

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A functional quantum computer needs both classical and quantum parts working together. VLSI needs to find ways to integrate these on a single chip while considering low temp and error correction.

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This article titled "A Comparative Analysis of Hybridized Genetic Algorithm in Predictive Models of Breast Cancer Tumors" published in IEEE Access https://lnkd.in/g9SHTQSz proposes several high-performing predictive models using hybridized genetic algorithm, based on other learning models, while taking into consideration the placement order of the feature selection algorithms in the hybridized models. The Wisconsin Breast Cancer dataset was used as the test bench, while filter, wrapper and embedded feature selection algorithms were used in the proposed hybridized models. The performances of proposed hybridized models were compared with those of the individual learning models, considered in this work. 

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Our game changing inference performance will enable new applications

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This Special Topic in APL Photonics on Brillouin Scattering and Optomechanics is building momentum - check out the content so far https://lnkd.in/gK5rJWkT

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