About

Dipak Ghosal is a Professor and the Bucher Family Chair in the Department of Computer Science at UC Davis. His research focuses on high-speed networks, wireless and sensor networks, transportation-based cyber-physical systems, network security, and performance evaluation of computer and communication systems. He is particularly interested in all problems related to networking, with his research group concentrating on control and security issues in computer, sensor, and wireless networks, as well as next-generation intelligent traffic systems. His work includes investigating new congestion control algorithms in high-speed networks, especially in private and dedicated wide-area networks, and developing machine learning-based network routing and scheduling algorithms for data transfers that require guarantees such as deadlines. Additionally, he is involved in designing, implementing, and deploying wireless sensor networks to optimize data fidelity and energy usage in harsh environments, as well as optimizing traffic signal control through machine learning. His research also addresses identifying threats and vulnerabilities in next-generation intelligent traffic systems with connected and autonomous vehicles (CAVs), and co-optimizing performance and fairness in 5G wireless networks. Ghosal serves as chair of the Graduate Group of Computer Science (GGCS) and is a member of the ECE Graduate Program at UC Davis.

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Engineering
• Distributed computing
• Telecommunications
• Mathematical optimization
• Mathematics
• Automotive engineering
• Operating system
• Geography
• Transport engineering
• Computer network
• Real-time computing

Selected publications

• Achieving Deterministic and Reliable Large-Scale Data Transfers in a Scientific Network

  2025-10-06

  articleSenior author

  Modern scientific workflows are data-intensive, geographically distributed, and time-sensitive, demanding reliable, low-latency data transfers across high-performance networks. While current solutions, such as ESnet’s OSCARS, offer static bandwidth reservation, they lack the fine-grained, deterministic guarantees essential for emerging real-time applications. To address this gap, we explore the applicability of Cyclic Queuing and Forwarding (CQF), a deterministic scheduling mechanism traditionally designed for Local Area Networks (LANs), to the unique challenges of Wide Area Networks (WANs). We propose a novel architecture that integrates CQF with multi-path routing to enhance reliability and evaluate it through a comparative simulation against OSCARS on a realistic ESnet topology, considering both time-triggered and event-triggered flows. Our results demonstrate that with proper parameter tuning, CQF can achieve a performance comparable to that of OSCARS in terms of latency, acceptance rate, and network utilization. As one of the first efforts to adapt CQF for WAN-scale scientific workflows, this study highlights its potential to enable deterministic communication for high-volume, long-distance scientific networks.

  PublisherDOI

• A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD

  Frontiers in Psychiatry · 2025-02-12 · 4 citations

  articleOpen access

  Background: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children and adolescents characterized by persistent patterns of hyperactivity, impulsivity, and inattentiveness. ADHD persists for many into adulthood. While irritability is not a diagnostic symptom of ADHD, temper outbursts and irritable moods are common in individuals with ADHD. However, research on the association between irritability and ADHD symptoms in adolescents and young adults remains limited. Method: Prior research has used linear regression models to examine longitudinal relations between ADHD and irritability symptoms. This method may be impacted by the potential presence of highly colinear variables. We utilized a hierarchical clustering technique to mitigate these collinearity issues and implemented a non-parametric machine learning (ML) model to predict the significance of symptom relations over time. Our data included adolescents (N=148, 54% ADHD) and young adults (N=124, 42% ADHD) diagnosed with ADHD and neurotypical (NT) individuals, evaluated in a longitudinal study. Results: Results from the linear regression analysis indicate a significant association between irritability at time-point 1 (T1) and hyperactive-impulsive symptoms at time-point 2 (T2) in adolescent females (β=0.26, p-value < 0.001), and inattentiveness at T1 with irritability at T2 in young adult females (β=0.49, p-value < 0.05). Using a non-parametric-based approach, employing the Random Forest (RF) method, we found that among both adolescents and young adults, irritability in adolescent females significantly contributes to predicting impulsive symptoms in subsequent years, achieving a performance rate of 86%. Conclusion: Our results corroborate and extend prior findings, allowing for an in-depth examination of longitudinal relations between irritability and ADHD symptoms, namely hyperactivity, impulsivity, and inattentiveness, and the unique association between irritability and ADHD symptoms in females.

  PublisherOA PDFDOI

• A Study of a Deterministic Networking Framework for Latency Critical Large Scientific Data Transfers

  2024-11-17 · 1 citations

  articleOpen accessSenior author

  Scientific workflows often involve large data transfers, which increasingly require completion-time guarantees. To support these time-sensitive flows, the Energy Science Network (ESnet) has implemented on-demand circuits with packet priority, allowing the circuit to be utilized by other traffic when the deadline-sensitive flow is inactive. In this paper, we explore a deterministic networking framework designed to support large scientific data transfers with completion guarantees. We consider an ideal network where all nodes are time-synchronized and utilize Cyclic Queueing and Forwarding (CQF) to achieve reliable low-latency data transfers. Specifically, the CQF cycle time is configured to ensure that all data transfers between neighboring nodes are completed within the cycle time. The number of packets transferable between two neighboring nodes depends on the cycle time, propagation delay, and link bandwidth. We conduct simulations to compare the performance of the deterministic networking framework with two circuit-based schemes: one utilizing fixed bandwidth allocation for all requests and another employing dynamic bandwidth reservation, which adjusts the allocated bandwidth based on the available bandwidth along the path. Our results show that the deterministic network architecture achieves performance comparable to the dynamic bandwidth reservation scheme. We believe that a more optimized version of the time-sensitive networking protocol, exploiting multi-path routing, could offer better completion guarantees than traditional network reservation options, while enhancing the overall network bandwidth utilization.

  PublisherOA PDFDOI

• CourseAssist: Pedagogically Appropriate AI Tutor for Computer Science Education

  2024-12-02 · 14 citations

  articleSenior author
  PublisherDOI

• A Simulation Study of Quantum Clock Synchronization Using Teleportation

  2024-07-01 · 1 citations

  articleOpen access

  An important requirement in implementing distributed computing and sensing application is the synchronization of clocks at various locations. The Internet relies on the Network Time Protocol (NTP), which synchronizes clocks with accuracy in the order of milliseconds. More recently an ensemble of atomic clocks is used for navigation based on GPS. These clocks are highly accurate and provide time with very low uncertainty. Even so, many physics experiments such as distributed LIGO-based systems may require more accurate clock synchronization that is achievable using quantum entanglement. This requires the deployment of a network of quantum clocks synchronized by exploiting entangled atomic clock qubits. In this paper, we carry out a simulation study of synchronizing a network of quantum clocks interconnected by a fiber plant that supports the ESnet; the latter is used to support the classical communication needed for teleportation. We consider an existing protocol for synchro-nizing the atomic clock qubits that relies on the GHZ states. To assess the performance of the protocol we developed a discrete-event simulation of the network using IBM Qiskit framework for underlying quantum gate operations and measurements. The simulation results shed light on the resources required in terms of the number entangled qubits and the time needed to achieve the synchronization of different number of nodes in ESnet.

  PublisherOA PDFDOI

• Counterfactual Analysis: A Case Study on Impact of External Events on Building Energy Consumption

  2023-12-15 · 2 citations

  articleOpen access

  Energy consumption in buildings accounts for a significant portion of the global energy use. Consequently, understanding building energy use is important. Data over the past decade show that the energy intensity (Joules/sqft) of commercial buildings has decreased. While some of the improvements (decrease in energy use) are easily measurable such as the use of more energy efficient lighting, impact of other modifications such as changes to the operation of the HVAC system or changes in the usage pattern of the building potentially due to external events are difficult to quantify. Simply comparing energy consumption prior and post change is not accurate as energy use is impacted by many factors including external weather conditions. In this paper, we present a case study to quantify the impact of external events on the energy consumption of a medium-sized office building. We adopt an approach based on counterfactual analysis. Towards this end, we first build two models based on Linear Regression and k-Nearest Neighbors to predict the daily energy use given different input features related to the weather. We determine the statistical features of the weather that are most predictive of energy use. We then use the models to determine a counterfactual baseline and thereby to accurately estimate the impact of the events. The results of the counterfactual analysis provide new insights on the impact of the events on energy consumption. The update to the building cooling system resulted in more energy savings than direct yearly comparison reveals. On the other hand, the tests of a MPC-based controller for the HVAC system saved less energy than determined by the direct yearly comparison. Finally, the results show that there no gains in terms of energy savings due to remote work during the COVID-19 pandemic. An increase in airflow setting in the HVAC system corroborates this finding and further validates the underlying model and the counterfactual analyses.

  PublisherOA PDFDOI

• A Road Network Simplification Algorithm that Preserves Topological Properties

  Research Square · 2022-08-31

  preprintOpen access

  Abstract A road network can be represented as a weighted directed graph with the nodes being the traffic intersections, the edges being the road segments, and the weights being some attribute of a road segment. Such a representation enables researchers to analyze road networks in consistent and automatable ways from the perspectives of graph theory. For example, analysis of the graph along with the traffic demand pattern can identify critical road segments based on centrality measures. However, due to the complexity of real-world road networks and the computationally expensive algorithms, it is challenging to extend the such methods to a large-scale road network. In this paper, we present a simple yet efficient network simplification framework based on graph theory that sub-samples and simplifies the graph while preserving key topological characteristics in the original network. Our method iteratively identifies and removes network elements that do not contribute to transportation functionality, such as self-loops, dead-ends, and interstitial nodes that lies on the same road line. We applied this method to three small cities with distinct street patterns and one large city, and showed that topological characteristics in the original networks are preserved by comparing two distinct kinds of centrality distributions in the original and simplified networks.

  PublisherOA PDFDOI

• TempMesh – A Flexible Wireless Sensor Network for Monitoring River Temperatures

  ACM Transactions on Sensor Networks · 2022-12-08 · 5 citations

  articleOpen accessSenior author

  For a Chinook salmon restoration project in the lower Yuba River in California, we designed and deployed a wireless sensor network to monitor river temperatures at micro-habitat scales. The study required that temperatures be measured along a 3 km study reach, across the channel, and into off-channel areas. To capture diel and seasonal fluctuations, sensors were sampled quarter-hourly for the full duration of the six-month juvenile salmon winter residency. This sampling duration required that nodes minimize power-use. We adopted event-based software on MSP430 micro-controllers with 433 MHz radio and minimized the networking duty-cycle. To address link failures, we included network storage. As the network lacked real-time clocks, data were timestamped at the destination. This, coupled with the storage, yielded timestamp inaccuracies, which we re-aligned using a novel algorithm. We collected over six months of temperature data from 35 sensors across seven nodes. Of the packets collected, we identified 21% as being incorrectly timestamped and were able to re-align 41% of these incorrectly timestamped packets. We collected temperature data through major floods, and the network uploaded data until the flood destroyed the sensors. The network met an important need in ecological sampling with ultra-low power (multi-year battery life) and low-throughput.

  PublisherOA PDFDOI

• TCP Davis: A Low Latency First Congestion Control Algorithm

  2022-10-01 · 1 citations

  articleSenior author

  The choice of feedback mechanism between delay and packet loss has long been a point of contention in TCP congestion control. This has partly been resolved, as it has become increasingly evident that delay based methods are needed to facilitate modern interactive web applications. However, what has not been resolved is what control should be used, with the two candidates being the congestion window and the pacing rate. BBR is a new delay based congestion control algorithm that uses a pacing rate as its primary control and the congestion window as a secondary control. We propose that a congestion window first algorithm might give more desirable performance characteristics in situations where latency must be minimized even at the expense of some loss in throughput. To evaluate this hypothesis we introduce a new congestion control algorithm called TCP Davis, which is a congestion window first algorithm that adopts BBR's approach of maximizing delivery rate while minimizing latency. In this paper, we discuss the key features of this algorithm, discuss the differences and similarity to BBR, and present results based on a real implementation.

  PublisherDOI

• A road network simplification algorithm that preserves topological properties

  Applied Network Science · 2022-12-01 · 21 citations

  articleOpen access

  Abstract A road network can be represented as a weighted directed graph with the nodes being the traffic intersections, the edges being the road segments, and the weights being some attribute of a road segment. Such a representation enables researchers to analyze road networks in consistent and automatable ways from the perspectives of graph theory. For example, analysis of the graph along with the traffic demand pattern can identify critical road segments based on centrality measures. However, due to the complexity of real-world road networks and the computationally expensive algorithms, it is challenging to extend the such methods to a large-scale road network. In this paper, we present a simple yet efficient network simplification framework based on graph theory that sub-samples and simplifies the graph while preserving key topological characteristics in the original network. Our method iteratively identifies and removes network elements that do not contribute to transportation functionality, such as self-loops, dead-ends, and interstitial nodes that lies on the same road line. We applied this method to three small cities with distinct street patterns and one large city, and showed that topological characteristics in the original networks are preserved by comparing two distinct kinds of centrality distributions in the original and simplified networks.

  PublisherOA PDFDOI

Recent grants

• NeTS: Small: Addressing End-system Bottlenecks in High-speed Networks

  NSF · $515k · 2015–2019

• DC: Small: Scaling the Performance of Network Security Applications Using Massively Parallel Processing Array (MPPA) Architectures

  NSF · $391k · 2010–2015

• CSR:Small:Estimating the End-system Network I/O Bottleneck Rate to Optimize Transport Layer Performance

  NSF · $411k · 2009–2013

Frequent coauthors

• Biswanath Mukherjee

  Soochow University

  43 shared

• Chen‐Nee Chuah

  31 shared

• Michael Zhang

  University of California, Davis

  20 shared

• Nathan Hanford

  Lawrence Livermore National Laboratory

  18 shared

• Brian Tierney

  16 shared

• Matthew Farrens

  University of California, Davis

  15 shared

• Eric Pouyoul

  Lawrence Berkeley National Laboratory

  14 shared

• Satish K. Tripathi

  14 shared

Labs

• EducationPI

Education

• Research Associate

  University of Maryland Institute of Advanced Computer Studies (UMIACS)

  1990

• PhD, Computer Science

  University of Louisiana at Lafayette

  1988

• MSc (Research), School of Computer Science and Automation

  Indian Institute of Science

  1985

• BTech, Electrical Engineering

  Indian Institute of Technology Kanpur

  1983

Awards & honors

• IEEE Award for Research in Optical Networks (2025)
• Education Award for Student-Designed Customizable AI Platfor…
• Prem Chand Jain Family Presidential Chair for Innovation and…