Integrated Nano Computing Lab

At the INC Lab, we develop practical nano-devices for the future of computing. We study the fundamental physics and materials properties of emerging materials, and work to bridge the gap from test structures to practical devices to circuits and systems. This vertical approach includes theoretical and experimental work at the materials, devices, and circuits levels. We seek to understand the materials properties, and then show how they can be designed into devices that do not just stand alone, but can perform useful computing tasks.

We are facing a time when we are reaching the limits of scaling improvements using current technology.  Current transistors waste energy both while switching and when idle, which ends up as wasted heat in our computers. On the other end of the spectrum, we are facing new big-data applications for computing that require large, dense memories that are distributed with logic, and applications like artificial intelligence and neuromorphic computing that require massive parallel computation.

New physics and materials, such as magnetic materials and 2D materials, have the potential for more energy efficient computing.  They also have novel physical properties that can be utilized, such as naturally low-dimensional sizes for ultra-scaled electronics, non-volatility (keeping its state when off), oscillatory dynamics, device-to-device interactions, low to no idle power dissipation, low-temperature fabrication, and in-memory computing possibilities.  This is an exciting time where we have the tools to apply new types of physics and materials to real-world devices, with a strong motivation to do so.

We are also interested in other applications of nanotechnology, such as quantum computing and medicine.


Check out INC Lab’s latest YouTube video, a student presentation by Harrison Jin on Topological materials in magnetic memory.

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Check out INC Lab’s latest YouTube video, a student presentation by David Basford on STT-MRAM for Embedded Applications.

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Check out our latest Youtube video, a student presentation by Matt Dwyer on the Brief History of Magnetic Data Storage!

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Check out this highlight of our recent two papers on magnetic stochastic neurons and WSe2-based ambipolar transistor circuits!

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Check out our latest Youtube video, a student presentation by Odinaka Okeke on Multiferroics Hardware-based Neuromorphic Architectures beyond Crossbar Arrays.!

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We have built ambipolar dual-gate WSe2 thin film transistors and measured them in cascaded logic gates, published in ACS Nano! The lead graduate student on the work is Xintong Li, who recently successfully defended his Ph.D., and it was done in close collaboration with Joseph S. Friedman and Deji Akinwande.

The most exciting parts are 1) the 2D devices are designed so they can be cascaded into circuits, without needing to insert any devices between the 2D gates, and 2) we demonstrate the Vt-drop circuit for the first time, which leverages the ambipolar control to cut in half the number of devices in the circuit compared to traditional FETs.

This project exemplifies my over-arching research objective to leverage the physical behavior of new materials and devices as they are, rather than try to fit them into the mold of other technologies. WSe2 is naturally ambipolar, so it is great to make that useful.

The work is supported by the US National Science Foundation.

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Our latest paper on magnetic devices for neuromorphic computing is now published in Applied Physics Letters! We show that the domain wall-magnetic tunnel junction device can act as a stochastic neuron, which is robust to recognizing noisy images compared to ideal leaky, integrate, and fire neurons. This shows how magnetic devices could be beneficial for noisy, edge computing. The neurons are made on the same chip as magnetic multi-weight synapses, showing both neuromorphic building blocks can be made together.

Thomas Leonard took the data with Harrison Jin and Sam Liu who led the neural network simulations; the research is supported by the National Science Foundation.

Thomas Leonard will give a talk on these results at the Device Research Conference tomorrow!

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Take a look at our recent paper on graphene-based brain-like artificial synapses selected for Neuromorphic Hardware and Computing collection at Nature Communications!

Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing

Check out our most recent YouTube video!

Spectrum News visits INC Lab to discuss graphene synapses

It is good timing that I just visited imec to talk at a spintronic logic workshop, and our recent work with Patrick Xiao and Nicholas Zogbi on using domain wall-magnetic tunnel junctions for parallel matrix multiplication is now published (early access)!

We solve a couple major challenges in using magnetic domain walls and magnetic tunnel junctions for computing by using voltage to increase the device reliability, and device design to allow multiple fanout without change in device footprint. With these changes, we are able to use physics-based simulations to show a fully functioning 8-bit MAC operation, the main computation for deep neural network inference!

It was so much fun to talk about neuromorphic computing on the 100th episode of the “It’s a Material World” podcast! Great for sharing with students and those interested to know more on the topic from a materials science perspective.

I truly appreciate what this podcast is doing to bring more awareness to materials science. A lot of the problems of today can be solved with materials of the future.

YouTube Link

Audio-Only Podcast

Thank you Xuan Hu and Joseph Friedman for leading this review on neuromorphic computing with domain walls and skyrmions.

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Here’s a presentation by Sam Liu of his work on Hardware-Aware Bayesian Variational Inference, presented at the MMM 2022 conference.

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Here’s Dr. Mahshid Alamdar’s presentation of her work on measuring multi-weight artificial synapses made from magnetic materials, presented at MMM-Intermag 2022.

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For a description of our theoretical work on scandium nitride magnetic tunnel junctions, check out our latest YouTube Channel video of Suyogya Karki’s presentation at Trends in Magnetism (TMAG) 2021
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Vivian Rogers, graduate student in the INC Lab, made a great video visualizing her work on spin-dependent transport in scandium nitride magnetic tunnel junctions. Check it out here!
High Magnetoresistance in Symmetry Filtering Scandium Nitride Junctions Using First Principles

Happy holidays! Sharing our work, “Random Bitstream Generation using Voltage-Controlled Magnetic Anisotropy and Spin Orbit Torque Magnetic Tunnel Junctions,” just published in JxCDC. Led by graduate student Sam Liu and postdoctoral researcher , we used physics-based modeling to study and compare different methods for random bitstream generation using magnetic tunnel junctions, and showed their usefulness for generating arbitrary probability distributions and solving np-hard problems. A shoutout to the whole DOE-Coinflips team!

Find it here!

Sharing this one more time – open faculty positions in our wonderful department in a wonderful city.

Link to the faculty positions

Click here to see the post!

Post from Chandra Family Department of Electrical and Computer Engineering (Texas ECE - UT Austin ECE) and an orange graphic of Texas ECE

Our article designing small arrays of magnetic skyrmions as brain-inspired artificial neurons is officially published and edited! This was the brainchild of Priyamvada Jadaun with hard work from Can Cui and Sam Liu, and supported by the National Science Foundation (NSF).

Click here for the link!

PAPER ALERT: Researchers from @utexasece are re-imagining computers to think like the human brain and they’ve made a new device discovery.

They used magnetic materials to engineer nano-devices that behave like synapses in the brain, which connect neurons to each other. The synapses they created can be adjusted by manipulating their geometry, which allows the synapses to be tuned for a variety of potential computing applications. Brain-like, or neuromorphic devices represent a new computing paradigm that can perform complex tasks that the human brain is good at, like image processing, and they learn as they go.

Magnetic materials fit many of the major requirements for brain-like computing because of their ability to switch not just between 0s and 1s but to other levels, and stay that way when they are off. The researchers recently published a similar paper on neuromorphic synapses using biocompatible materials, which are important for medical uses, but not fast enough for next-gen computers. This paper is focused more on devices with the speed and energy to compete with state-of-the-art computing technologies, as we think of how to design computers for AI.

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Meet the team 

@utexasece: Jean Anne Incorvia, Thomas Leonard, Samuel Liu, Mahshid Alamdar, Harrison Jin, Can Cui and Otitoaleke G. Akinola

@SandiaLabs: Christopher Bennett, T. Patrick Xiao, Matthew Marinella

@UTD_ECE: Joseph Friedman

@Applied4Tech: Lin Xue

I look forward to speaking at PUZZLE X 2022 in Barcelona!

PUZZLE X™ is the leading global forum for Frontier & Deep Tech for the Future. It brings together leading figures in industry, science, capital and goverment to discuss how the bleeding-edge technologies in the “Matterverse” can shape the next chapter for cities, citizens, industries, and societies.

Join me Nov 15-17 in Barcelona.

Check out our latest work, led by Sandia National LaboratoriesChristopher H. Bennett and Sam Liu in the INC Lab. We show in simulation that combining a tunable stochastic magnetic tunnel junction with the domain wall-magnetic tunnel junction device creates a very efficient bit cell for Bayesian neural networks, which can do classification tasks with well-calibrated uncertainty estimates.

Bayesian neural networks using magnetic tunnel junction-based probabilistic in-memory computing

So far, the standard computer doesn’t have any thoughts, and algorithms do everything.

Texas ECE researchers including Dmitry Kireev, Jean Anne Incorvia, and Deji Akinwande are hoping to change that.

I am very proud to have our work Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing published today in Advanced Electronic Materials!

Find it here: Shape-Dependent Multi-Weight Magnetic Artificial Synapses for Neuromorphic Computing

We show we an reliably achieve 3-5 stable resistance states in a device with a single domain wall and single magnetic tunnel junction, and show through data-driven neuromorphic simulations that the stability of each resistance state makes it promising for inference, and that the ability to tune the domain wall control with geometry makes it promising for online learning. Many people in our field of spintronics are interested in the domain wall-magnetic tunnel junction as a synapse, and I am hopeful our work makes it more of a reality and points us in the direction of what to prove next. I have talked about this work a lot, and am really happy to see it officially published.

Congratulations to the authors, especially Thomas Leonard and Sam Liu who saw the paper to the finish line! And thank you to the funding agencies, National Science Foundation (NSF) and . Thank you Christopher H. Bennett and team at Sandia for our fruitful collaborations!

The Daily Texan and Austin Statesman covers our work on graphene synapses. Find them with these links:

Austin Statesman

The Daily Texan

I’ve been looking for an opportunity to work on magnetic material-based inductors, and now it’s happening with Alex Hanson and Southwest Research Institute! We will work together on developing large-scale rapid coating deposition technology for synthesizing high-quality and affordable magnetic materials.

UT Austin and SwRI Support Five Collaborative Energy Research Projects

I am so proud of the effort of my graduate student Xintong Li in our just-published paper, All-Electrical Control and Temperature Dependence of the Spin and Valley Hall Effect in Monolayer WSe2 Transistors!

ACS Publications

I worked on spin and valley Hall effect experiments when I was a postdoc, working with Elyse Barré and Tony Heinz. These experiments are so challenging, everything has to go right from the monolayer material transfer, 20+ nanofabrication steps, electrically connecting the devices to the cryostat, cooling down, spatial measurements without drift, maintaining good signal:noise ratio, and more. Xintong did it all through his diligence and smarts and produced a very comprehensive set of results.

We optically and spatially characterize the spin and valley Hall effect in monolayer WSe2 transistors. We show it’s persistence up to 160 Kelvin and robust electrical control, important step towards practical application in devices. The SVHE is one of the only ways to generate a gateable spin current, which if properly harnessed could be very useful in spintronic devices.

Our latest collaborative work with Deji Akinwande has just been published! Check it out here:

We combine graphene and Nafion to create a fully bio-compatible artificial synapse and show it has low update energy, good endurance, and good nonlinearity and symmetry for neural network applications. We show the metaplastic properties of the synapse can allow them to outperform ideal synapses in online learning neuromorphic tasks. Perhaps biological and artificial neural networks will be working in tandem, sooner rather than later!

Big shout-out to the co-first authors Dmitry Kireev and Sam Liu, and co-authors Harrison JinPatrick Xiao, and Christopher H. Bennett. And I want to acknowledge the research sponsors, this project brought together researchers supported by various programs, including the UT Austin NSF MRSECNational Science Foundation (NSF)Sandia National LaboratoriesOffice of Naval Research, and the UT Austin Portugal Program.

Look at these amazing undergraduates who devoted their summers to working in my lab! From left, Maya Borowicz fabricated and took measurements of graphene artificial synapses and neurons; Vivian Rogers modeled neuromorphic functions in radically new materials; Kaywan Taha exfoliated 2D materials and measured them for cancer therapies; Ethan Rivers fabricated heterostructured 2D ambipolar transistors; Naman Parikh imaged magnetic domain walls in neuromorphic devices; Paul W Bessler modeled stochastic computing with magnetic tunnel junctions; and Harrison Jin measured magnetic artificial synapses and modeled their applications for in-memory computing.

Group of students and Professor Jean Anne Incorvia standing in from of the Cockrell School of Engineering. From the left, Maya Borowicz, Vivian Rogers, Ethan Rivers, Naman Parikh, Paul W Bessler, and Harrison Jin.

To catch up on our recent progress on intrinsic lateral inhibition in magnetic neurons, see Can Cui’s talk at ISCAS 2022 here!

Congratulations to Mahshid Alamdar for receiving her Ph.D. from Texas Electrical and Computer Engineering (Texas ECE – UT Austin ECE) as the second graduate of INC Lab! Now she is on to new things at Samsung Austin Semiconductor.

Professor Jean Anne Incorvia and Mahshid Alamdar stand in graduation gowns in front of Cockrell School of Engineering backdrop, with text reading “We are TEXAS ENGINEERING.”

Check out this spotlight on Spintronics and Neuromorphic Computing with professor Incorvia!

“Great to connect to the Advanced Material Future Preparedness Taskforce. If you haven’t heard of them yet, I encourage you to check them out!”

Prof. Incorvia discusses with  and Dmitri Nikonov about the field of nanotechnology for AI and answers some questions about her career path as a woman in engineering!

Listen to the podcast here

On Spotify:
On Soundcloud:
On Apple Podcasts:

Professor Jean Anne Incorvia sitting in a workspace.

Here's to a great research collaboration that has started between INC Lab, David Z. Pan and Samsung Electronics, and we appreciated the visit of Debasis Bera and Choi Yongkwang to our labs!

Professor Jean Anne Incorvia and a research group, including David Z. Pan, Debasis Bera and Choi Yongkwang.

"There is a lot to hear about skyrmions at this year's APS March Meeting. I will present on our group's work with  on Tuesday in G29: Towards Skyrmionics Manipulating Spin Textures (check out the whole session, thank you Avik Ghosh for organizing!) and Andrew Maicke will present on his work with my group at Monday's B54: Skyrmion Based Devices."

Our work was highlighted by APS Press, read more about it here: - Brains Built in the Lab, Octopus Robots, and Knitted Elephants - Brain Jadaun


If anyone missed our 2D materials for biomedical applications workshop, hosted by the UT Austin-Portugal program, you can watch the recorded lectures on Youtube.

Puzzle X is an impressive international effort to converge new materials frontiers with entrepreneurship and venture building. Check out Dr. Incorvia's interview with them to discuss the research going on in the Integrated Nano Computing Lab!

New video is posted on our Youtube channel!

"Sam Liu, Ph.D. Student in the INC Lab, Presents his Work at MMM/Intermag Describing how Domain Wall-Magnetic Tunnel Junctions can be Designed for Accurate Training of Neural Networks"

There is rich physics in new materials and devices that is ready to be used for brain-like advanced computing!

This is the conclusion of our Special Topic on Emerging Hardware for Cognitive Computing that was published in the IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (JxCDC). You can read my reflection and summaries of the papers here:

Congratulations on the impressive work of the authors in this competitive call. And thank you to Azad Naeemi and Ian Young for the opportunity to guest edit this topic.

Proudly representing UT Austin at the International Electron Devices Meeting this week, the premier annual meeting on nanoelectronics! Xiuling Li participated in IEEE committees, Deji Akinwande is one of the two speakers at today’s conference lunch, and I am chairing 3 sessions including helping organize the MRAM forum taking place on Thursday. Come say hi if you are here, and see my student Sam Liu’s poster tomorrow at the MRAM poster session.

Professor Jean Anne Incorvia standing in front of a screen reading “IEDM” with Xiuling Li and Deji Akinwande on the sides of her, throwing “hook’em horns” hand gestures.

INC Lab was featured on page 19 in the Fall 2021 ECE Magazine!

Magazine imagine colored blue and purple which reads “Texas ECE, Create • Transform • Innovate, 6G@UT”

New video is posted on our Youtube channel!

"Patrick August, UT Austin Physics Ph.D. Student, Talks on Nuclear Magnetic Resonance"

We are honored to have our recent publication, on theory of magnetic tunnel junctions using scandium nitride, highlighted as the inside cover for Advanced Theory and Simulations!

Magazine imagine colored green and cyan which reads “Advanced theory and simulations”

New video is posted on our Youtube channel!

"Guy Farmer, UT Austin Physics Ph.D. Student, Talks on Electromagnetic and Electrodynamic Suspensions"

"I joined IEEE as a graduate student 10 years ago just to get a student discount for a conference. Over these 10 years I have been continually impressed with the IEEE organization and the amazing conferences, research chapters, and student groups it enables around the world. I am very proud to be part of IEEE and now a senior member!"

-Prof. Jean Anne Incorvia

New video is posted on our Youtube channel!

"Mengke Liu, UT Austin Physics Ph.D. Student, Talks on Quantum Hall Effect"

"I am here to announce our latest publication on predicting large on/off ratio and unique spin transport properties in scandium nitride (ScN) magnetic tunnel junctions (MTJs)! I am very excited by these results, since so few materials exist to-date that can compete with the "magic" tunnel barrier material magnesium oxide (MgO) that has propelled the field of MTJs. New materials could be so helpful in finding the best applications of MTJ-based devices, especially for neuromorphic computing and artificial intelligence. Congratulations to the authors especially Suyogya Karki and Vivian Rogers."

-Prof. Jean Anne Incorvia

Large Magnetoresistance in Scandium Nitride Magnetic Tunnel Junctions Using First Principles

Sandia Labs News Releases

3 square layers of compacted molecules are stacked, the top and bottom are labeled “Fe” and the middle is labeled “ScN”

New video is posted on our Youtube channel!

"Umar Burney, UT Austin Physics Ph.D. Student, Talks on Magnetocaloric Materials"

At INC Lab we are so excited to be part of this new team, led by Sandia National Laboratories, to bridge neuroscience, algorithms, computer architectures, and probabilistic devices to advance microelectronics! Thank you to the Department of Energy for this opportunity.

What If the Secret to Your Brain’s Elusive Computing Power is Its Randomness?

Sandia Labs News Releases

"Prof. Jean Anne Incorvia of Texas ECE has been named a 2021 Intel® Rising Star. The Rising Star Faculty Award is an invitation-only program to foster innovation and help promote the careers of promising early-career faculty members. This year Intel recognized "10 promising early-career academic researchers who are leading some of the most important technology research of our time."

ECE: Prof. Jean Anne Incorvia Named Intel® Rising Star

Intel® 2021 Rising Star Faculty Award Recognizes 10 Leading Early-Career Professors

New video is posted on our Youtube channel!

"Jackson Hill, UT Austin Physics Ph.D. Student, Talks on Magneto-Optic Kerr Effect (MOKE)"

New video is posted on our Youtube channel!

"Jeffrey Vit, UT Austin Physics Ph.D. Student, Talks on Magnetic Force Microscopy & its Applications"

New video is posted on our Youtube channel!

"Maxwell Nakos, UT Austin Physics Ph.D. Student, Talks on Reservoir Computing with Magnetism"

New video is posted on our Youtube channel!

"Samuel Liu, UT Austin Physics Ph.D. Student, Talks on Magnetic Neuromorphic Computing Devices"

New video is posted on our Youtube channel!

"Blake Broussard, UT Austin Physics Ph.D. Student, Talks on Defect Color Centers"

New video is posted on our Youtube channel!

"Anthony Salazar, UT Austin Physics Ph.D. Student, Gives an Overview on Nuclear Electric Resonance"

New video is posted on our Youtube channel!

"Aparna Jayakumar, UT Austin Physics Ph.D. Student, Talks on Domain Walls and Skyrmions in TmIG"

New video is posted on our Youtube channel!

"Hyunsue Kim, UT Austin Physics Ph.D. Student, Talks on the Basics of Magnetic Topological Insulators"

New video is posted on our Youtube channel!

"Dongseob Kim, UT Austin Physics Ph.D. Student, Talks on the Challenges of 2D Magnets for Device Applications"

New video is posted on our Youtube channel!

"Mahshid Alamdar Speaks at DRC 2021 on Spin Orbit Torque in-Memory and Neuromorphic Computing Devices"

New video is posted on our Youtube channel!

"Alena Nederveld, UT Austin ECE Ph.D. Student, Overviews on Electromagnetic Acoustic Transducers"

New video is posted on our Youtube channel!

"Prof. Incorvia Speaks at SPIE 2020 on Lateral Inhibition in Magnetic Domain Wall Racetrack Arrays"

New video is posted on our Youtube channel!

"Prof. Incorvia Speaks at MMM 2020 on Synapses for Energy-Efficient Neuromorphic Computing."

New video is posted on our Youtube channel!

"Jingyu Cao, UT Austin ECE Ph.D. Student, Gives an Overview on Spin Orbit Torque MRAM"

New video is posted on our Youtube channel!

"Can Cui Speaks at MMM 2020 on Maximized Lateral Inhibition in Paired Magnetic Domain Wall Racetracks"

New video of a student presentation is posted on our Youtube channel!

"Teddy Hsieh, UT Austin ECE Ph.D. Student, Gives an Overview on Embedded STT-MRAM"

Prof. Incorvia gave a talk recently on Designing Magnetic Synapses and Neurons with Application-Specific Functions! Find it here!

New video posted on our Youtube channel!

"Otitoaleke Akinola Speaks at MMM 2020 on Spiking Neural Networks using Magnetism"

New video posted on our Youtube channel!

"Sebastian Miki-Silva, UT Austin ECE Ph.D. Student, Gives an Overview on RAM Types"

New video posted on our Youtube channel!

"Nick Pronin, UT Austin ECE Ph.D. student, gives an overview of spin transfer torque magnetic random access memory"

New video posted on our Youtube channel!

"Can Cui shows our work on lateral inhibition domain wall racetrack arrays for neuromorphic computing"

New video posted on our Youtube channel!

"Andrew Maike, UT Austin ECE Ph.D. student, teaches about computational micromagnetics"

New video posted on our Youtube channel!

"Otitoaleke Akinola from INC Lab speaks at the MRS Spring/Fall Meeting 2020 on Synthesis of Two-Dimensional Metal Carbide Materials"

Our work on the synthesis and characterization of a new 2D material, Cr2C, was published today as an invited featured paper in the Journal of Materials Research! Check it out here. These results open up Cr2C to experimental study, including of its predicted emergent magnetic properties, and develop guidelines for synthesizing new MXene materials. We thank the UT Austin MRSEC center for supporting this research

Check out our first Youtube video on our channel, INC Lab!

"Computing using Magnetism - talk by Prof. Jean Anne Incorvia at the 2021 Microelectronic Reliability and Qualification Workshop (MRQW)"

Check out our published article May 2021 “Irradiation Effects on Perpendicular Anisotropy Spin-Orbit Torque Magnetic Tunnel Junctions” in IEEE Transactions on Nuclear Science!

Ph.D. graduate from INC Lab Otitoaleke Akinola received the UT ECE top achiever award! Congratulations Leke.

Check out a May 2021 article on a trio of papers from our group!

Brain-like Computing Takes a Step Forward with New Discoveries Using Magnetism

Prof. Incorvia gave a talk on implementing advanced biological functions in artificial magnetic neurons and synapses to the Petaspin lecture series. It is available on YouTube.

Prof. Incorvia gave a talk on domain wall-magnetic tunnel junction devices for in-memory and neuromorphic computing to the Online Spintronics Seminar series. Check it out here.

Our work "Domain wall-magnetic tunnel junction spin–orbit torque devices and circuits for in-memory computing" was published today in Applied Physics Letters, as part of the Special Topic on Spin-Orbit Torque (SOT): Materials, Physics and Devices. Calling out the hard work of all the authors, and especially Mahshid Alamdar and Thomas Leonard who share first-authorship.

We have two students with awards to congratulate! Congratulations to Can Cui for receiving the Bruton Graduate Student Fellowship in recognition of her research excellence. And congratulations to Mahshid Alamdar for receiving a 2021 American Physical Society March Meeting Award for excellence in graduate research, give to 7-10 graduate students out of > 10,000 attendees.

Check out the Nov. 2020 issue of the Texas ECE Magazine, with INC Lab featured on p. 15!

Our group's work on lateral inhibition in magnetic neurons, led by graduate student Can Cui, was published in IOP Nanotechnology in 202o. The results have reach broader audiences through the UT Austin Cockrell School Website,, and

Prof. Incorvia answers five questions about computing like the brain in an interview with the Cockrell School of Engineering.

Dr. Incorvia received the 2020 IEEE Magnetics Society Early Career Award, awarded to one person internationally in her field a year. Read more about the award here.

Congratulations to Thomas Leonard for receiving the 2020 NSF Graduate Research Fellowship!

Dr. Incorvia received the National Science Foundation Faculty Early Career Development Program CAREER award, starting March 2020

CAREER Announcement

2018 interview discussing the research going on in the INC Lab

Interview with Dr. Incorvia at the 2019 American Graphene Summit

Our work on designing magnetic devices as synapses with spike-timing-dependent plasticity has been published in Sept. 2019!

Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity

Research Highlights

Magnetic Logic Devices and Circuits

We are researching new device and circuit designs for computation using magnetic materials.

Neuromorphic Computing

We work on designing and building magnetic resistive devices for analog/neuromorphic/bio-inspired computing.

Spintronics using 2D TMD Materials

2D transition metal dichalcogenide (TMD) materials have emerging applications for spintronics. We are studying the spin and valley Hall effect in TMD transistors such as WSe2 and WS2.

Image is divided into thirds by color, top and bottom are blue and are labeled “FM”. The middle, a much thinner layer, is orange and labeled “insulator”

Materials for Magnetic Tunnel Junctions

We are investigating new materials for both the electrodes and tunnel barrier to improve the on/off ratio and functionality of magnetic tunnel junctions.

Black and white image depicting ultra-scaled transistors, reading from top to bottom on the left, “Ag, Cr, Sc, ScOx, BP, SiO2” and on the right, “ScOx ~ 9nm, BP ~ 6.5nm, 5nm”

Ultra-Scaled Transistors using 2D Materials

We are investigating 2D transistors with materials such as TMDs and black phosphorus.

Avada Admin

New Spintronic 2D Materials

We are studying new types of low-dimensional materials with promising applications in spintronics.