About

Dennis Lee is an Assistant Professor in the Department of Materials Science and Chemical Engineering at Stony Brook University. His research interests are centered around developing innovative materials processing strategies for synthesizing and characterizing multifunctional composite materials. He aims to tailor the properties of these materials through surface/interface modifications and defect engineering to gain a comprehensive understanding of structure-activity-processing relationships. His group utilizes vapor-phase processes, including atomic layer deposition/molecular layer deposition and post-synthetic vapor treatment, as well as wet chemical methods such as sol-gel and solvothermal/hydrothermal synthesis. These techniques are employed to fabricate targeted porous material-based hybrid systems. The hybrid systems developed by his research group find applications in various areas, including toxic chemical detoxification, membrane gas separation, and materials patterning, with a focus on energy and environmental sustainability and global health applications.

Research topics

• Computer Science
• Programming language
• Operating system
• Physics
• Environmental science
• Theoretical computer science
• Embedded system

Selected publications

• Reconfigurable machine tending with collaborative robots: leveraging ISO 21919 for enhancing flexibility and safety

  International Journal of Computer Integrated Manufacturing · 2025-04-28 · 1 citations

  article
  PublisherDOI

• Implantable Galvanic-Coupled Body Channel Communication Transceiver with Serpentine-Interconnection Electrode Pair for Post-Operative Monitoring of Joint Replacement

  2025-05-25

  article

  This paper presents a galvanic-coupled body channel communication (GC-BCC) transceiver (TRX) system with serpentine-interconnection electrodes for applications in joint replacement surgeries, such as total knee replacement (TKR). The proposed system consists of a GC-BCC transmitter (TX) implanted inside the body and an external receiver (RX). Implanted devices with high stiffness may cause tissue damage or compromise long-term stability due to the inherent curvature and elasticity of the human body. Given these characteristics of the human body, implantable devices should feature flexible and stretchable structures that conform to the body’s contours and minimize such risks. To address this requirement, we propose a serpentine-interconnection electrode pair, which provides mechanical compliance and can replace the conventional straight-interconnection interface. This interconnection enables reliable signal transmission in the MHz band, demonstrating its suitability for both implantable TX and external RX in medical applications. The GC-BCC TX and RX are fabricated using 0.18 µm BCD and 0.18 µm CMOS processes, respectively, achieving a data rate of 20 Mb/s with a bit error rate (BER) of less than 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup>. The TX and RX chips consume an active area of 3.2 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and 2.5 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and consume a power of 675 µW and 4.32 mW, respectively. The performance of the proposed system is validated through ex-vivo experiments using 10-mm thick porcine tissue.

  PublisherDOI

• Is Reuse All You Need? A Systematic Comparison of Regular Expression Composition Strategies

  ArXiv.org · 2025-03-26

  preprintOpen access

  Composing regexes is a common but challenging engineering activity. Software engineers struggle with regex complexity, leading to defects, performance issues, and security vulnerabilities. Researchers have proposed tools to synthesize regexes automatically, and recent advances in LLMs have also shown promise in generating regexes. Meanwhile, developers commonly reuse existing regexes from codebases and internet sources. No work to date has compared these various regex composition strategies, leaving software engineers unaware about which to use and researchers uncertain about open problems. We address this gap through a systematic evaluation of regex reuse, formal synthesis, and LLM-based generation strategies. We curate a novel dataset of 901,516 regexes mined from open-source software projects and internet sources (RegexReuseDB), accompanied by a set of 55,448 regex composition tasks defined by a target regex and its corresponding positive and negative string pairs (RegexCompBench). To address the absence of an automated regex reuse formulation, we design and implement reuse-by-example, the first programming by example approach that leverages RegexReuseDB. Our evaluation then benchmarks reuse-by-example, formal synthesizers, and LLMs on many aspects of interest to software engineers, including accuracy, maintainability, computational efficiency, and result diversity. Although all three approaches solve most composition tasks accurately, only reuse-by-example and LLMs excel over the range of metrics we applied, and reuse-by-example in particular offers engineers the variance in candidates that they say they find helpful. Ceteris paribus, prefer the cheaper solution--for regex composition, perhaps reuse is all you need. Our findings provide insights for developers selecting regex composition strategies and inform the design of tools to improve regex reliability in software systems.

  PublisherOA PDFDOI

• A 16-QAM-Based Multi-Node BCC System with Bias-Electrode-Free Multi-Channel ExG Readout ICs

  2025-06-08

  article1st authorCorresponding

  We present a system for multi-node body channel communication (BCC) integrated with multi-channel ExG readout ICs. By utilizing time-multiplexing for BCC communication and ExG measurement, the system minimizes interference between the BCC signal and the ExG readout IC, enabling the measurement of EEG, which requires ultra-low noise, along with EOG, EMG, and ECG signals. Moreover, eliminating the bias electrode increases BCC signal amplitude by 60%, allowing 16-QAM communication at 8Mbps even under time-multiplexing operation. To guarantee the robustness of communication, the system adaptively switches to OOK modulation in cases of significant body channel loss. Additionally, the system employs a multi-channel least-mean-square (LMS) filter and a DC servo loop (DSL) to effectively address channel mismatches and differential artifacts.

  PublisherDOI

• A 100-Mb/s Current-to-Current Galvanic-Coupling-Communication TX/RX Achieving 0.94-pJ/b TX Energy Efficiency for Neural Implant Systems

  2025-09-08

  article

  This work presents a novel galvanic-couplingcommunication (GCC) method, ITX-IRX GCC, which transmits and receives current to achieve high channel gain over a wide frequency bandwidth and high energy efficiency. In-vitro measurement using porcine tissue confirms reliable communication, achieving a bit-error rate lower than 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−6</sup> through <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$10-\text{mm}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$15-\text{mm}$</tex> tissue layers with a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$3-\text{cm}$</tex> electrode pitch. Fabricated using a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$65-\text{nm}$</tex> CMOS process, the IC achieves a TX energy efficiency of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$0.94 \text{pJ} / \mathrm{b}$</tex> at a data rate of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$100 \text{Mb} / \mathrm{s}$</tex>, making it highly suitable for uplink communication in implantable systems.

  PublisherDOI

• HALO: Loop-aware Bootstrapping Management for Fully Homomorphic Encryption

  2025-02-06

  articleOpen access

  Thanks to the computation ability on encrypted data, fully homomorphic encryption (FHE) is an attractive solution for privacy-preserving computation. Despite its advantages, FHE suffers from limited applicability in small programs because repeated FHE multiplications deplete the level of a ciphertext, which is finite. Bootstrapping reinitializes the level, thus allowing support for larger programs. However, its high computational overhead and the risk of level underflow require sophisticated bootstrapping placement, thereby increasing the programming burden. Although a recently proposed compiler automatizes the bootstrapping placement, its applicability is still limited due to lack of loop support.

  PublisherDOI

• Performance-aware Scale Analysis with Reserve for Homomorphic Encryption

  2024-04-17 · 8 citations

  article

  Thanks to the computation ability on encrypted data and the efficient fixed-point execution, the RNS-CKKS fully homo-morphic encryption (FHE) scheme is a promising solution for privacy-preserving machine learning services. However, writing an efficient RNS-CKKS program is challenging due to its manual scale management requirement. Each cipher-text has a scale value with its maximum scale capacity. Since each RNS-CKKS multiplication increases the scale, programmers should properly rescale a ciphertext by reducing the scale and capacity together. Existing compilers reduce the programming burden by automatically analyzing and managing the scales of ciphertexts, but they either conservatively rescale ciphertexts and thus give up further optimization opportunities, or require time-consuming scale management space exploration.

  PublisherDOI

• Verifiable Sustainability in Data Centers

  IEEE Security & Privacy · 2024-03-18 · 4 citations

  article

  The current techniques and tools for collecting, aggregating, and reporting verifiable sustainability data are vulnerable to cyberattacks and misuse, requiring new security and privacy-preserving solutions. This article outlines security challenges and research directions for addressing these requirements.

  PublisherDOI

• A Multi-Node Body-Channel-Communication System Using Adaptive Gain Control with ExG Readout ICs for Moving VR Users

  2024-11-18 · 1 citations

  article1st authorCorresponding

  Virtual reality (VR) and extended reality (XR) technologies have been utilized to enhance realism in gaming, exercise, military training, and other applications beyond spatial constraints. Besides visual advancements, it is crucial to monitor the movements of each arm and leg in real time for practical human motion analysis. However, connecting the modules on each limb using wires limits the user’s movement and causes user inconvenience, and wireless connection suffers from high power consumption, which hinders the development of wearable and long-lasting solutions. By employing body-channel communication (BCC), we can achieve user’s free and comfortable movement, high energy efficiency, and low cost, all at the same time. It also enables real-time, wireless acquisition of electromyography (EMG) signals from all the arms and legs, as well as electrocardiogram (ECG) signals, without the constraints of wires.

  PublisherDOI

• Privacy Set: Privacy-Authority-Aware Compiler for Homomorphic Encryption on Edge-Cloud System

  IEEE Internet of Things Journal · 2024-08-02 · 4 citations

  article

  Fully homomorphic encryption (FHE) offers a promising solution for privacy-preserving cloud computing by allowing cloud servers to compute on encrypted data without decryption. However, its applicability is limited by the programming burden of ciphertext management and considerable operational latency. Recently proposed FHE compilers automate ciphertext management, but they transform all data into ciphertexts without filtering private data, thus unnecessarily increasing FHE ciphertexts and the overall latency. This work introduces a new privacy-authority type, called privacy-set (PSet), that allows programmers to annotate authorized devices for each unit of private data. Moreover, this work proposes a new privacy authority-aware compiler that automatically transforms a PSet-annotated plain program into an FHE-enabled edge-cloud cooperative program with operation authority- and latency-aware partitioning. This work evaluates the PSet compiler with six machine learning and deep learning applications, and demonstrates that the PSet compiler performs 4.92 times faster than the existing FHE compilers that do not support edge-cloud partitioning.

  PublisherDOI

Recent grants

• CSR: Small: Repurposing Spatial Memory Safety Support in Commodity Processors for Temporal Memory Safety, Other Program Analyses, Hardware-Accelerated Data Structures, and More

  NSF · $516k · 2018–2020

• CSR: Small: Repurposing Spatial Memory Safety Support in Commodity Processors for Temporal Memory Safety, Other Program Analyses, Hardware-Accelerated Data Structures, and More

  NSF · $347k · 2020–2022

Frequent coauthors

• Changhee Jung

  Purdue University System

  25 shared

• James C. Davis

  18 shared

• Francisco Servant

  Universidad de Málaga

  12 shared

• Satish Narayanasamy

  University of Michigan–Ann Arbor

  12 shared

• Peter M. Chen

  University of Michigan–Ann Arbor

  10 shared

• Tong Zhang

  South China University of Technology

  10 shared

• Jason Flinn

  Meta (Israel)

  10 shared

• Keon-Jun Park

  Gachon University

  9 shared

Education

• Ph.D., Computer Science and Engineering

  University of Michigan

  2013

• M.S., Computer Science and Engineering

  University of Michigan

  2009

• B.S., Electrical Engineering

  Seoul National University

  2004