2026 ACECNJ Fall Conference

Thank you to our Breakfast Sponsor:
Parsons!

ACECNJ President Joe Fiordaliso and new Executive Director Taryn Boland will address attendees and answer your questions about the state of the Council and the future of ACECNJ.

Thank you to our Coffee Break Sponsor:
LAN Associates!

Artificial intelligence (AI) and machine learning (ML) are transforming traffic safety analysis by enabling faster, more scalable, and data-driven insights that extend beyond traditional crash-based approaches. In this case study, a New Jersey urban community explored how AI-powered analysis of near-miss events, instances where collisions were narrowly avoided, could supplement conventional safety evaluations in support of the City’s Vision Zero initiative and Complete Streets goals. Unlike crash data, which typically informs reactive improvements after incidents occur, machine learning-driven near-miss analytics provide a proactive lens by detecting patterns in frequent, high-risk interactions and identifying emerging hazards before crashes take place. Support was provided for the collection and evaluation of near-miss data from multiple vendors, leveraging AI and ML techniques to compare detection methodologies, data outputs, and analytical approaches. This evaluation identified strengths, limitations, and opportunities for application across platforms. The effort was conducted in parallel with multimodal safety planning initiatives, where AI-enhanced insights informed concept development focused on improving safety for pedestrians, cyclists, transit users, and motorists. The case study assessed how AI- and ML-enabled near-miss analytics could enhance routine traffic engineering practices, including warrant analyses, safety studies, and crash investigations, by providing a broader, more dynamic, and near real-time understanding of roadway risk. Findings highlighted the value of near-miss analytics in identifying conflict patterns at scale, while also identifying challenges related to data consistency, model transparency, interpretation, and integration into established workflows.

This project consists of the design and implementation of geothermal heating and cooling systems at NYCHA’s Eastchester Gardens and Jackson Houses developments. The systems replace aging fossil-fuel infrastructure with high-efficiency, all-electric ground-source heat pump systems, improving energy reliability, reducing emissions, and enhancing resident comfort. The project supports NYCHA’s long-term sustainability and decarbonization goals.

Learning Objectives:
Participants will gain an understanding of how geothermal systems can be implemented in dense urban environments,
the challenges of decarbonizing existing residential buildings, and strategies for integrating clean energy solutions into occupied developments. They will be equipped with practical approaches for managing stakeholder coordination, minimizing construction impacts, and advancing scalable electrification initiatives.

Highlights:
 Decarbonization challenges in existing buildings,
 Integration of geothermal systems within dense, occupied urban environments
 Transitioning from fossil-fuel heating systems to electrified solutions
 Managing construction impacts in occupied residential developments
 Coordinating multidisciplinary stakeholders
 Navigating regulatory and infrastructure constraints

The rapid expansion of AI infrastructure is driving one of the largest capital buildouts in modern history, and the federal government has put incentives, programs, and subsidies in place to ensure the United States continues to lead on AI. ACEC NJ members are at the center of this work, but most are significantly underutilizing these programs meant to subsidize the work they are already doing in this space. Programs such as Section 41, Section 48, advanced manufacturing incentives like Sections 48C and 48X, energy infrastructure credits Section 48A energy efficient building deduction 179D, and production credits Section 45 are all highly relevant to data center and AI infrastructure projects. When combined with state and local incentives—such as hiring credits, abatements, and location-based subsidies, the financial impact can materially improve project economics and firm profitability. However, these programs are complex and require a deep understanding of both engineering workflows and tax policy. Firms that rely on generalist advisors often miss substantial value because their work is not properly identified, documented, or positioned. For ACEC NJ members these programs can represent six, seven, or eight figures in funds when claiming multiple benefits

Learning Objectives:
1. Identify federal, state, and local incentive programs available for AI infrastructure, data center, energy, and advanced manufacturing projects, including the tax credits and deductions most relevant to engineering firms.
2. Recognize qualifying engineering and design activities that can generate substantial tax credits, deductions, and incentives, and understand why these opportunities are frequently misse
3. Assess opportunities within their own project portfolios to capture available incentives and improve project economics, client value, and firm profitability.

Audience:
This session is designed for owners and executives for engineering, architecture, and consulting firms, particularly ACEC NJ members—working on AI infrastructure, data centers, energy, and advanced manufacturing projects. It addresses the challenge of underutilized federal, state, and local tax incentives that can significantly improve project profitability and economics when properly identified and claimed. Key themes include AI infrastructure, tax credits, government incentives, R&D credits, energy incentives, strategic tax planning, project profitability, and engineering-driven growth.

Thank you to our Networking Luncheon Sponsor: 
TYLin!

This session presents a case study on the use of two-dimensional (2D) hydraulic modeling to evaluate urban flooding conditions and assess off site impacts which may extend beyond traditional regulatory frameworks. It highlights how system-wide analysis can improve culvert and stormwater design decisions and promote more resilient infrastructure in highly developed watersheds.

Learning Objectives:
Participants will be able to understand how two-dimensional hydraulic modeling can be applied to better represent urban floodplain behavior, including overland flow paths, flood extents, and downstream impacts that are not fully captured in one-dimensional analyses. Participants will also be able to recognize the importance of assessing system-wide and off site impacts which surpass traditional regulatory guidance when designing hydraulic structures.

Audience:
This session is intended for civil and environmental engineers, stormwater and floodplain professionals, transportation planners, and regulatory agency staff involved in the design, review, and management of urban drainage and hydraulic systems. It addresses challenges in aging and undersized stormwater infrastructure in highly developed watersheds, where constrained conveyance systems and changing rainfall patterns increase flooding and downstream impacts. The focus is on engineering design and regulatory decision-making, particularly the use of two-dimensional (2D) hydraulic modeling to evaluate retrofit alternatives, system-wide performance, and floodplain compliance.Key subject areas include urban stormwater management, flood risk and floodplain analysis, culvert and conveyance design, infrastructure retrofit, and downstream impact assessment. Keywords: 2D hydraulic modeling, urban flooding, stormwater infrastructure, flood risk, FHACA compliance, overland flow, and climate resilience.

Autonomous technologies are transforming how infrastructure is inspected, managed, and maintained. This session examines the use of drones, robotics, AI, and reality capture technologies to improve safety, inspection quality, and asset management. Through real-world applications and emerging trends, attendees will learn how infrastructure owners and engineers are leveraging technology-enabled inspections to support more efficient, data-driven decision-making and long-term asset performance.

Learning Objectives:
Explain how technology driven inspection methodologies are transforming infrastructure assessment and management.
Identify the benefits and challenges of deploying robotics, drones, AI, and reality capture in infrastructure programs.
Evaluate how advanced inspection data can support asset management, maintenance planning, and capital decision-making.
Develop strategies for incorporating routine and repeatible inspection technologies into existing organizational workflows and asset management practices.

Audience:
Infrastucture owners, engineers, asset managers, and public agencies.

In the past decade, CREATES has made a significant impact regionally and nationally in conducting projects funded by federal, state and industry.  It has attracted close to $70million dollars and graduated annually 60 undergraduate and graduate students with hands-on experience in transportation engineering.

Learning Objective:
The participants will have a clear understanding of the impact CREATES is having on the state and nation. The participants will also be introduced to some of the research work conducted at CREATES.

Audience:
CREATES at Rowan University is home to a state-of the-art accelerated pavement testing facility featuring a Heavy Vehicle Simulator (HVS) capable of replicating up to 20 years of traffic loading in just a few months, enabling rapid evaluation of innovative transportation solutions. This session is intended for transportation agencies, engineers, researchers, consultants, contractors, and industry partners interested in advancing resilient, sustainable, and data-driven transportation infrastructure. It highlights CREATES' research, education, workforce development, and technology transfer activities across innovative construction materials, pavement engineering, pavement preservation, asset management, transportation safety and mobility, bridge engineering, geotechnical engineering, and additive manufacturing for concrete infrastructure. The session will showcase CREATES' expanding capabilities in artificial intelligence, digital twins, pavement management systems, and infrastructure sensing, demonstrating how emerging digital technologies are supporting performance-based decision-making, predictive maintenance, and the next generation of smart transportation infrastructure. With its unique capabilities, and broad portfolio can be a great resource to engineering companies to New Jersey, this presentation will serve as an introduction of these capabilities and how we can collaborate that is mutually beneficial

Thank you to our Coffee Break Sponsor:
MAKS Engineers, PC!

The durability assessment of three NJTA’s culverts near Cherry Hill Township, New Jersey was a collaborative effort between durability specialists and structural designers. Designed initially for 75 years, the three culverts are required to last another 75 years, therefore doubling the service life. A condition assessment and residual service-life evaluation of the concrete guided the structural rehabilitation design, resulting in a strategy to extend the service life for the next 75 years. The project demonstrates how the service-life of satisfactory to good condition structures showing cracks, spalls, rust staining, and efflorescence while dealing with a structural apacity reduction can be extended.

Learning Objective:
Following the presentation, participants will understand alternative solutions to extend the service life of concrete box culverts. They will also understand the value of providing valuable scientific data to support the rehabilitation work selection with regards to sustainability and service life considerations.

Audience:
This session is designed for owners, infrastructure managers and engineers involved in the planning of rehabilitation of concrete structures. It addresses the growing need to balance durability, sustainability, and long-term performance in aging infrastructure. The session supports a lifecycle-oriented model, helping organizations move beyond prescriptive practices toward performance-based approaches that optimize service life, maintenance costs, and operational disruptions.

Every engineering firm leader has had the same conversation: a project went over budget and nobody saw it coming. The data was in Deltek the whole time. The Friday report came on Monday. The change order conversation happened three weeks too late. This session walks through a different model. Instead of dashboards waiting to be read, AI agents continuously read project, time, billing, and resource data from Deltek Vantagepoint and surface what needs attention - before the margin erosion happens. We will share the practical architecture, what is working today, and the honest gotchas (data quality, PM adoption, false positives) we have encountered along the way. This is a practitioner session for principals, CFOs, COOs, operations leaders, and IT decision-makers at engineering firms who are evaluating AI for project management and finance operations. Attendees will leave with a realistic view of what is possible today, what still requires manual work, and a framework for evaluating AI investments against their firm's data maturity.

Learning Objectives:
1. Describe the practical architecture for connecting AI agents (such as Claude) to Deltek Vantagepoint data via API and MCP (Model Context Protocol).
2. Identify which project intelligence use cases (margin risk, utilization forecasting, AR aging, pipeline analytics) are realistic today versus aspirational.
3. Recognize the data quality and process prerequisites that determine whether an AI implementation will succeed or stall.
4. Apply a decision framework to evaluate AI investment opportunities against the firm's specific project portfolio and operational maturity.

Audience:
Engineering firm principals, CFOs, COOs, finance directors, operations leaders, and IT decision-makers — both Transportation and Non-Transportation tracks. Particularly relevant for mid-sized engineering firms (50–500 employees) operating on Deltek Vantagepoint or Deltek Vision who are evaluating practical AI investments in 2026 and 2027.
The session addresses the strategic question every firm leader is being asked by their board this year: "What is our AI plan, and is it real?" It speaks to project-based service business models where margin protection, resource utilization, and proactive intelligence are operational priorities.

Thank you to our Dessert Reception Sponsors:
Boswell | Jacobs