Overview of our Research
Our lab studies the physics and engineering of advanced electronic systems, with primary research in microelectronic packaging, stochastic computing architectures, and electrical circuits and imaging sensors such as single-photon avalanche diodes (SPADs). We develop new device concepts and integration strategies that bridge physical hardware and computation, aiming to improve performance, scalability, and energy efficiency across diverse platforms. Our methods and technologies find broad application in photonics, physics, chemistry, and biology, where electronic and optical systems increasingly intersect. Ultimately, our goal is to combine these diverse fields to create truly cutting-edge engineering solutions that push the boundaries of modern technology.
Primary Research Areas
Packaging
Our group explores the interaction between self-assembling polymer membranes and proteins. We perform polymer synthesis and characterization, physical-chemical and protein-inversion studies. Our goal is to design and develop novel polymers for bio-sensing applications.
Circuits
1) Ultra-low power mixed-signal circuit design for biosensors and 2) High-performance mixed-signal for control and stabilization of photonic ICs. We specialize in PLLs, DLLs, low-noise analog front-end amplifiers, sigma-delta ADCs, and novel signal control loops.
Bio Applications
Our lab develops electronic and nanoscale systems that interface directly with biological environments through advanced circuit design. Using electrowetting-on-dielectric (EWOD) platforms, we control microfluidic droplets for lab-on-chip assays; single-photon avalanche diodes (SPADs) enable circuit-level detection of faint optical signals in bioimaging; and neural probes integrate electronic, optical, and electrophysiological sensing for studying brain activity. Together, these circuit-driven technologies form the foundation for next-generation bioelectronic systems in diagnostics and neuroscience.
Probabilistic Computing
Our lab explores stochastic computing architectures that harness randomness for efficient problem solving. By implementing Ising and Potts model-based hardware, we emulate probabilistic physical systems to tackle computationally intensive optimization problems such as the travelling salesman problem. These systems leverage noise and device variability to perform low-power, parallel search over large solution spaces. Through circuit-level design, we aim to build scalable stochastic processors that merge physical modeling with computation for next-generation intelligent hardware.
Current Projects
Through Silicon Vias and Redistribution layers
Digital Microfluidics/EWOD
Stochastic Computing
SPAD Sensors
Publications
A Mo, Z Nelson, L Theogarajan
2025 IEEE 75th Electronic Components and Technology Conference (ECTC), 2237-2242
Andrew Netherton, Mario Dumont, Zachary Nelson, Jahyun Koo, Jinesh Jhonsa, Alice Mo, David McCarthy, Skylar Deckoff-Jones, Yun Gao, Noah Pestana, Jordan Goldstein, Ren-Jye Shiue, Christopher Poulton, MJ Kennedy, Mark Harrington, Bozhang Dong, Jock Bovington, Michael Frankel, Luke Theogarajan, Michael Watts, Daniel Blumenthal, John E Bowers
Photonics Research, A69-A86
William Whitehead, Wonsik Oh, Luke Theogarajan
IEEE journal on exploratory solid-state computational devices and circuits
Jahyun Koo, Luke Theogarajan
2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS)
Zachary Nelson, Alice Mo, Luke Theogarajan
2024 IEEE 74th Electronic Components and Technology Conference (ECTC)
Andrew Netherton, Mario Dumont, Zachary Nelson, Jinesh Jhonsa, Alice Mo, Jahyun Koo, David McCarthy, Noah Pestana, Skylar Deckoff-Jones, Christopher Poulton, Michael Frankel, Jock Bovington, Luke Theogarajan, John Bowers
2024 IEEE International Solid-State Circuits Conference (ISSCC)
William Whitehead, Zachary Nelson, Kerem Y Camsari, Luke Theogarajan
Nature Electronics
Shuvro Chowdhury, Andrea Grimaldi, Navid Anjum Aadit, Shaila Niazi, Masoud Mohseni, Shun Kanai, Hideo Ohno, Shunsuke Fukami, Luke Theogarajan, Giovanni Finocchio, Supriyo Datta, Kerem Y Camsari
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Navid Anjum Aadit, Andrea Grimaldi, Mario Carpentieri, Luke Theogarajan, John M Martinis, Giovanni Finocchio, Kerem Y Camsari
Nature Electronics
Our Team
Luke Theogarajan
Principal Investigator
Luke Theogarajan is currently a Professor at the University of California, Santa Barbara in Electrical and Computer Engineering. He received his Ph.D. degree in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology in 2007. His research interests include combining the processing power of electronics with the versatility of synthetic chemistry to develop neural prosthetic devices, integrating CMOS circuits with nanoscale sensors to develop novel biosensors and developing simple synthetic mimics of biological function to gain a deeper physical understanding of biological phenomena. Before starting his Ph.D, he worked for intel for 5 years where he was part of the Pentium 4 design team. He has published both in the field of electrical engineering and polymer chemistry and holds 4 patents. Professor Theogarajan is also a 2010 NIH New Innovator Award recipient and a 2011 NSF Career Award recipient. He has been awarded the Northrupp Grumman Excellence in teaching award in 2011 and the outstanding faculty member in EE for the years 2009, 2010, 2011, 2012, 2013, and 2017.
Ph.D. Students
Zachary Nelson
Chip to Wafer Packaging for Opto-Electronic Integration
Ph.D. Candidate, Year 5
Wonsik Oh
CMOS image sensors, biometric image sensors, and X-ray detectors, analog/mixed-signal integrated circuits and optical devices
Ph.D. Candidate, Year 4
Jinesh Jhonsa
combinatorial optimization problems and FPGA-based signal processing for advanced communication systems
Ph.D Candidate Year 5
Undergraduate Students
Alumni
Alumni
Mitra Saedi (Ph.D. 2021) → Semtech
Prajakta Kulkarni (PostDoc 2020)
Aaron Blustone (Ph.D. 2018) → HRL
Chin-Hsuan Chen (Ph.D. 2017) → Apple
Justin Rofeh (Ph.D. 2017) → Laxmi Therapeutic
Avantika Sodhi (Ph.D. 2017) → Qualcomm
Melika Payvand (Ph.D. 2017) → Prof @ University of Zurich
Danielle Morton (Ph.D. 2016) → Apple
Shahab Mortezaei (PostDoc 2015) → Atomwise
Matthew Pevarnik (PostDoc 2015) → Prof @ Regent University
Weibin Cui (PostDoc 2015)
Sukru Yemenucioglu (Ph.D. 2015) → Apple
Ellie Corigliano (PostDoc 2013) → Merck
Micheal Isaacman (Ph.D. 2013) → PHD Biosciences
Luis Chen (Ph.D. 2012) → Qualcomm
Kaveh Milaninia (PostDoc 2012) → Planobo
Mohamed Elzeftwani (Ph.D. 2012) → Cadence
Ashfaque Uddin (Ph.D. 2012) → Intel
Naraso Borjigin (PostDoc 2010) → Huntsman
Saeed Mirzaeian (Ph.D. 2010) → Qualcomm
Le Wang (Ph.D. 2010) → Apple
Eric Hsieh (M.S. 2024) → Amazon
Alex Nguyen-Le (M.S. 2020) → Ph.D. @ University of Pennsylvania
Sarah Grundeen (M.S 2019) → Northrop Grumman
Sean McCotter (M.S. 2019) → Senseeker
Akshar Jain (M.S. 2017)
Rebecca Martin (R.A)
Star Li (M.S. 2012) → Intel
Aaron Peng (B.S. 2021) → Ph.D. @ University of Chicago
Michell Chiu (B.S. 2019) → Ph.D. @ University of Chicago
Antonio Labaro (B.S. 2019)
Ryan Kaveh (B.S. 2017) → Ph.D. @ UC Berkeley
Wyatt Rodgers (B.S. 2014)
Kathryn Barron
Bassel Ihsan (B.S. 2012)
Laurel Hopkins (B.S. 2012) → Ph.D. @ Oregon State University
Taishi Kato (B.S. 2012) → M.S. @ UC Los Angeles
Krisna Bhargava (B.S. 2010)
Niloufar Pourian (B.S. 2010)
Justin Chang (B.S. 2010)