1. Can you share your career journey and the key experiences that influenced your philosophy and led you to your role at DTE Energy?
My career has been shaped by a combination of technical depth, strategic vision, and business insight. I began with a PhD in Mechanical Engineering, building strong analytical and problem-solving skills. Recognizing the growing role of data in innovation, I earned an MSc in Applied Data Science and AI from the University of Michigan. This foundation enabled me to bridge the gap between physical systems and digital intelligence.
Professionally, I’ve advanced through roles in engineering consulting, product management, and digital solutions leadership always focused on solving real-world problems. In consulting, I applied AI to improve asset reliability and shift strategies from reactive to predictive maintenance. At Schneider Electric, I developed AI/Cloud/Edge-based SaaS solutions, delivering MVPs that provided immediate business value. This taught me to align technology with customer pain points using an agile mindset.
Today, as Director of IT Digital Transformation at DTE Energy, I lead a team that partners with diverse stakeholders across the organization, including corporate strategy and advanced analytics hub, to deliver customer-focused innovation that turns technology into measurable impact.
2. How would you describe your leadership style, and in what ways does it reflect your commitment to solving customer challenges through innovative technology?
My leadership style is primarily transformational. I strive to inspire change by setting a compelling vision, encouraging innovation, and fostering personal and professional growth. I believe that when people are motivated, empowered and trusted, they can deliver incredible outcomes, which is essential for driving innovation in today’s fast evolving digital landscape.
At the same time, I recognize that leadership is not one-size-fits-all. I also embrace situational leadership, adapting my approach based on the maturity and needs of the team or customer project. Early-stage teams may need more guidance, structure and support, while experienced teams thrive with greater autonomy and space to explore bold ideas. This flexibility ensures that every team is set up for success.
Ultimately, I focus on building trust and enthusiasm, creating a collaborative environment where cross-functional teams are empowered to solve customer challenges with bold, pragmatic innovation.
3. As someone who merges technical expertise with strategic business vision, how do you prioritize initiatives to ensure that digital transformation projects deliver real value to end customers?
To effectively prioritize digital initiatives, I focus on two key dimensions: business value and technical feasibility. It’s critical to work closely with customers to understand their challenges—after all, no one knows their pain points better than they do. We avoid assumptions and instead validate value through direct engagement.
Once we identify the right problems, we design solutions iteratively. Rather than aiming for perfection upfront, an approach that can be costly, we start small and gather user feedback early. I typically use a phased approach: beginning with a Proof of Concept (PoC), advancing to a Minimum Viable Product (MVP), and scaling from there. This helps test technical and business assumptions efficiently.
My mindset is simple: “think big, act small.” We maintain a long-term vision but move forward in manageable, validated steps. This approach reduces risk, accelerates value delivery, and builds trust with customers ensuring our digital transformation efforts create real, measurable impact.
4. What are some of the key lessons learned from developing and launching MVPs for AI-driven solutions, and how do you translate these learnings into scalable, customer-centric products?
One key lesson is the importance of agility and iteration. MVPs aren’t about perfection—they’re about learning fast. Launching quickly and collecting feedback early helps us pivot or refine before investing heavily.
It’s also critical to accept that failure is part of innovation. When building something new, risk is inevitable, but failing fast and learning quickly allows for smarter adaptation and less wasted effort.
Another insight is that a functioning AI prototype is not a finished product. A well-performing model in Python is only the beginning. Scaling it into a reliable, maintainable solution brings real complexity.
Successful AI deployment at scale requires:
• Data pipelines: Real-time access to quality data
• Model monitoring: Detecting drift or degradation
• Scalability: Infrastructure that supports growth
• Integration: Seamless workflow embedding
• Security and compliance: Data protection and regulation
• User experience: Intuitive and actionable design
Addressing these early, with cross-functional teams, transforms MVPs into scalable, customer-centric products that deliver real value.
5. How do you build and lead cross-functional teams that merge insights from engineering, data science, and business strategy to drive digital transformation?
Effective cross-functional teams begin with a clear sense of purpose. Everyone, including engineers, data scientists, and business leaders must understand the “why” behind their work. When people see how their contributions support the digital strategy and customer outcomes, they’re more motivated, engaged, and empowered to innovate.
Assigning tasks in isolation isn’t enough. Providing context, clarifying the problem, and explaining the value we aim to deliver fosters ownership, collaboration, and accountability. I emphasize this alignment early, so each team member sees the bigger picture.
I also promote a culture where diverse perspectives are essential. Each discipline brings unique strengths, and integrating technical expertise with business insights leads to solutions that are both innovative and practical. I ensure alignment on the customer problem we’re solving and apply agile practices such as ceremonies and regular check-ins to maintain transparency and adaptability. Continuous learning is vital, so I encourage cross-domain growth to keep the team engaged and effective.
6. Looking ahead, what trends do you anticipate will most profoundly reshape the energy sector, and how will a customer-centric approach remain central in navigating this change?
The energy sector is undergoing a profound transformation driven by several converging trends.
First, electricity demand is accelerating, mainly driven by the rapid growth of data centers, artificial intelligence, and electric vehicles. Simultaneously, the expansion of renewables like wind and solar, along with advances in battery storage, is reshaping how energy is generated, stored, and consumed.
Second, digitalization and AI are transforming grid operations, predictive maintenance, and customer engagement, empowering consumers to become “prosumers” through smart technologies and DERs. This shift is making the grid more dynamic, decentralized, and data-driven.
Third, customer expectations are evolving. Today’s energy consumers are informed, environmentally conscious, and digitally savvy, demanding proactive communication and seamless digital experiences.
Other key concerns like energy security and supply chain resiliency are rising amid global uncertainty.
In this new landscape, customer-centricity is essential. Energy providers must move beyond asset-centric models and integrate customer needs into every strategy, product, and service. Those who lead with agility and innovation will thrive in this decentralized, rapidly evolving ecosystem.
7. What advice would you offer to emerging digital leaders who aspire to balance technological innovation with business strategy, particularly in traditional industries facing rapid change?
Start with the customer. Understand their world, their pain points, and their goals. Then, use technology as a means not an end to deliver value. Adopt an experimental approach, but do so with discipline: fail fast, learn faster. Build diverse teams that can think holistically, and always keep the business impact in mind. In traditional industries, change can be slow, but with the right mindset and approach, digital leaders can be the catalysts for meaningful transformation.
