This interview is with Robert Chen, VP & CIO at DataNumen.

Robert Chen, VP & CIO, DataNumen

As the VP & CIO of DataNumen, can you tell us about your journey in the tech industry and how you came to specialize in data recovery?

My journey in tech started over two decades ago when I encountered my first major data loss incident as a junior IT administrator. A critical server crash wiped out weeks of work, and watching the panic in my colleagues’ eyes as they realized their data might be gone forever was a pivotal moment for me. That experience sparked my fascination with data recovery and digital forensics.

I began my career in systems administration, but I found myself increasingly drawn to the challenge of recovering seemingly lost data. I spent countless hours learning about file systems, storage architectures, and the intricate ways data is written to and corrupted on various media. What started as curiosity evolved into expertise as I began developing custom recovery scripts and tools for my organization.

The turning point came when I successfully recovered critical financial data from a severely damaged RAID array that other specialists had deemed unrecoverable. Word spread quickly in our industry network, and I realized there was a significant gap between what existing recovery tools could do and what was actually possible with the right technical approach.

This led me to DataNumen, where I’ve been able to combine my technical background with strategic leadership. As VP & CIO, I oversee both our product development and our internal technology infrastructure. My hands-on experience with data loss scenarios directly informs our software development priorities—we build solutions for the real-world problems I’ve encountered throughout my career.

What drives me most is that data recovery isn’t just about technology; it’s about restoring people’s digital lives, preserving businesses, and sometimes even helping with legal investigations. Every algorithm we optimize and every new file format we support represents someone’s irreplaceable memories or critical business operations being saved.

What inspired you to pursue a career in technology, and how has your role evolved over the years?

My initial inspiration to pursue technology came from a childhood fascination with understanding how things work. I was the kid who took apart every electronic device I could get my hands on—radios, computers, even old hard drives. My parents weren’t always thrilled, but that curiosity about the inner workings of technology never left me.

In college, I was initially torn between computer science and electrical engineering, but a database management course changed everything. The professor demonstrated how a single corrupted bit could render an entire database unusable, yet with the right knowledge, that same data could often be recovered. That intersection of problem-solving, technical depth, and real-world impact was exactly what I was looking for.

My role has evolved dramatically over the years. I started as a junior IT administrator focused purely on keeping systems running—basic troubleshooting, user support, and maintenance tasks. But I quickly gravitated toward the more complex challenges: the failed backups, the corrupted databases, the “impossible” recovery scenarios that others would escalate or abandon.

As I developed specialized expertise in data recovery, my responsibilities expanded to include forensic analysis and disaster recovery planning. I began leading cross-functional teams, training other technicians, and eventually consulting on recovery architectures for enterprise clients.

Now, as VP & CIO at DataNumen, my role spans three critical areas: strategic technology leadership, product innovation, and operational oversight. I’m still deeply involved in the technical aspects—reviewing our recovery algorithms, testing edge cases, and staying current with emerging storage technologies. But I also shape our company’s technology roadmap, manage our engineering teams, and ensure our internal infrastructure can scale with our growing customer base.

The most rewarding evolution has been moving from solving individual data loss crises to building solutions that prevent and resolve thousands of cases simultaneously. Every feature we ship potentially saves someone from the heartbreak of permanent data loss.

Can you share a challenging data recovery case that you’ve worked on and how it shaped your approach to problem-solving in tech?

One case that fundamentally changed how I approach complex recovery scenarios involved a law firm that had experienced a catastrophic RAID failure combined with a ransomware attack. They had lost access to over 15 years of case files, including ongoing litigation documents worth millions of dollars. The attackers had not only encrypted their data but also corrupted the RAID metadata, making traditional recovery methods ineffective.

What made this particularly challenging was the time pressure—they had court deadlines just days away—and the fact that three different recovery specialists had already attempted and failed to retrieve the data. The RAID controller had failed during the ransomware attack, and the drives had been improperly handled during previous recovery attempts, causing additional physical damage.

My approach was to step back and analyze the problem systematically rather than rushing into another recovery attempt. I spent the first day just documenting the drive states, examining the corruption patterns, and reverse-engineering how the ransomware had interacted with their specific RAID configuration. I realized that while the file allocation tables were destroyed, the actual data blocks remained largely intact but scattered.

Instead of trying to rebuild the RAID structure conventionally, I developed a custom algorithm that could identify and reassemble file fragments based on content patterns and metadata signatures. Working 72 hours straight, I was able to recover 94% of their critical files, including all the time-sensitive litigation documents.

This case taught me that often the most complex problems require abandoning conventional approaches and building solutions from first principles. It also highlighted the importance of having a systematic methodology before attempting any recovery—something I’ve since institutionalized at DataNumen through our “diagnostic-first” protocol.

More importantly, this experience led us to develop our patent-pending fragmented data reconstruction technology, which is now a core component of several of our enterprise recovery products. That single case not only saved a client’s business but became the foundation for helping thousands of other organizations facing similar challenges.

How do you stay ahead of rapidly evolving technology trends, and what strategies do you use to keep your team innovative?

Staying ahead in data recovery means constantly anticipating where technology is heading, because we need to be ready to recover data from technologies that haven’t even been fully adopted yet. My approach is multi-layered and deliberately proactive.

First, I maintain deep connections with storage hardware manufacturers and file system developers. We participate in beta programs for new storage technologies, encryption standards, and operating system updates. This gives us 6-12 months advance notice of changes that could impact data recovery methods. For example, when Apple was developing APFS, we were already working on recovery algorithms before the first public release.

I dedicate 20% of my time to hands-on research and experimentation. Every Friday, I’m in the lab working with emerging technologies—whether it’s testing recovery techniques on the latest NVMe drives, analyzing new ransomware encryption patterns, or exploring how cloud storage architectures affect data recovery possibilities.

For my team, innovation isn’t optional—it’s built into our DNA. We run monthly “Innovation Sprints” where engineers can pursue any data recovery challenge that interests them, no matter how unconventional. Some of our most successful product features have come from these sessions, including our current machine learning-based file carving algorithms.

We also maintain what I call “technology watch lists”—each team member monitors specific technology domains and presents quarterly briefings on emerging trends. This distributed intelligence gathering ensures we’re not missing critical developments across the entire tech landscape.

Perhaps most importantly, we encourage controlled failure. We have a dedicated test environment where the team can experiment with risky recovery approaches without consequences. This psychological safety has led to breakthrough innovations, like our recent development of recovery methods for solid-state drives with hardware encryption controllers.

We also collaborate extensively with universities and research institutions, sponsoring graduate research projects focused on next-generation storage and recovery challenges. This gives us access to cutting-edge academic research while contributing to the broader data recovery knowledge base.

In your experience, what are the most common misconceptions about data security that businesses have, and how do you address them?

The biggest misconception I encounter is the “backup equals security” fallacy. Companies invest heavily in backup systems and assume they’re protected, but I’ve seen countless cases where businesses discovered their backups were corrupted, incomplete, or inaccessible precisely when they needed them most. Just last year, we helped a manufacturing company that had been diligently backing up to tape for five years, only to discover during a crisis that their backup software had been failing silently for months.

Another dangerous misconception is that cloud storage automatically means data is safe. While cloud providers offer excellent infrastructure, I’ve recovered data from numerous cloud migration failures, sync errors, and even cases where employees accidentally deleted entire folders that propagated across all synchronized devices before anyone noticed.

The “it won’t happen to us” mindset is perhaps the most costly misconception. Companies often treat data protection as an IT checkbox rather than a business continuity imperative. I address this by sharing real case studies—like the medical practice that lost 10 years of patient records because they assumed their server room was “secure enough,” or the architecture firm that nearly went bankrupt when ransomware hit during their backup maintenance window.

I also see businesses confusing data protection with data recovery capabilities. They’ll invest in sophisticated security tools but have no plan for data reconstruction when those tools fail. My approach is to advocate for layered strategies that include prevention, detection, AND recovery components.

To address these misconceptions, I emphasize testing recovery procedures regularly. I recommend quarterly “disaster simulation” exercises where companies actually attempt to restore critical data from their backups under time pressure. This reveals gaps that theoretical security audits miss.

Most importantly, I help businesses understand that data security isn’t just about preventing breaches—it’s about ensuring business continuity regardless of what goes wrong. True data security means having multiple recovery pathways and regularly validating that those pathways actually work when you need them most.

Can you describe a time when you had to implement a major technological change at DataNumen? What were the challenges and lessons learned?

One of the most significant changes I led was migrating our core recovery engine from a monolithic architecture to a modular, parallel-processing framework. Our legacy system, designed when most drives were under 500GB, was taking weeks to process modern 18TB drives.

The biggest challenge wasn’t technical—it was convincing stakeholders to rebuild our most successful product while maintaining 100% backward compatibility. Customers trusted our engine with their most critical data, and any regression was unacceptable.

I implemented a parallel development approach, building the new engine alongside the old one with extensive A/B testing on anonymized datasets. Every recovery scenario had to produce identical or better results. This took 18 months and required expanding our QA team significantly.

Technically, we had to decompose monolithic algorithms into parallelizable components while preserving the intricate decision trees that made our recovery effective. Memory management became critical as we processed multiple data streams simultaneously.

Key lessons learned: incremental migration beats big-bang approaches, customer communication during major changes is crucial, and preserving institutional knowledge requires deliberate documentation of not just what algorithms do, but why certain decisions were made.

The results exceeded expectations: 300% faster recovery times, better success rates on modern storage, and a foundation that now supports our AI-enhanced recovery features. Most importantly, we maintained our reputation for reliability while dramatically improving performance.

How do you balance the need for cutting-edge technology with ensuring user-friendly solutions for your customers?

The fundamental tension in data recovery is that the most effective solutions often require deep technical expertise, but our customers are usually non-technical users facing an emergency. They don’t want to learn about file allocation tables—they just want their photos back.

My approach centers on what I call “progressive complexity.” Our software presents a simple, one-click interface for most users, but layers in advanced options for power users. When someone launches our photo recovery tool, they see three buttons: “Quick Scan,” “Deep Scan,” and “Custom Recovery.” Behind that simplicity, we’re running sophisticated algorithms that automatically detect drive types, optimize scan parameters, and apply machine learning to improve success rates.

We invest heavily in user experience research, particularly studying how people behave during data loss crises. Stress testing revealed that users in panic mode can’t process more than three options at once. This insight led us to redesign our interfaces around decision trees rather than feature matrices.

One specific example: our RAID recovery software can handle 47 different RAID configurations, but most users don’t know what RAID level they’re using. Instead of asking technical questions, we guide them through identifying their setup with visual cues: “How many drives do you see?” “Are they the same size?” The software determines the configuration automatically.

We also maintain “explain modes” throughout our products. Every technical term has hover explanations in plain English, and our progress indicators tell users what’s happening: “Analyzing drive structure” rather than “Parsing MFT entries.”

The key insight is that cutting-edge technology should make things simpler for users, not more complex. Our most advanced algorithms run invisibly in the background, making intelligent decisions so customers don’t have to. When we succeed, users think data recovery is easy—they have no idea we just performed digital surgery with precision tools.

This philosophy has become a competitive advantage. While competitors focus on adding features, we focus on removing friction.

What advice would you give to aspiring tech professionals about building a successful career in the data recovery and security field?

Start with the fundamentals, but go deeper than most people are willing to. Don’t just learn how file systems work—understand why they were designed that way and what happens when they fail. I tell every new hire to spend time with hex editors and low-level disk utilities. You need to be comfortable reading raw binary data and understanding storage at the bit level.

Get your hands dirty early and often. Set up test environments where you can safely corrupt data and practice recovery techniques. I still maintain a lab with drives I deliberately damage to test new recovery methods. There’s no substitute for practical experience with real failures.

Develop a systematic problem-solving methodology. Data recovery isn’t about knowing every possible solution—it’s about having a repeatable process for analyzing unknown problems. Document everything you learn, especially your failures. Some of my most valuable insights came from cases where standard approaches didn’t work.

Don’t neglect the business side. Technical brilliance means nothing if you can’t communicate the value to non-technical stakeholders. Learn to translate technical concepts into business impact: “This encryption will reduce our liability exposure” resonates more than “This uses AES-256.”

Specialize, but maintain broad knowledge. I became the RAID expert on my team, but I also understood networking, databases, and forensics. That breadth helped me see connections others missed and made me more valuable as my career progressed.

Build relationships across the industry. Data recovery is a small community—the specialist you help today might become your customer or colleague tomorrow. Attend conferences, contribute to forums, and share knowledge generously.

Most importantly, never lose sight of the human element. Behind every data recovery case is someone having a terrible day. Whether it’s family photos or business-critical files, you’re often their last hope. That responsibility should drive everything you do.

Stay curious and stay humble—technology evolves faster than any individual can master completely.

Looking ahead, what emerging technologies do you believe will have the biggest impact on data recovery and security, and how is DataNumen preparing for these changes?

Three technologies will fundamentally reshape data recovery in the next decade, and we’re actively preparing for each.

First, AI and machine learning are transforming recovery success rates. Traditional recovery relies on recognizing known file signatures and structures, but AI can identify patterns in seemingly random data that humans would miss. We’re developing neural networks that can reconstruct files even when traditional markers are completely destroyed. Our current ML models have improved recovery rates by 23% on heavily fragmented drives, and we’re just scratching the surface.

Second, quantum computing presents both unprecedented threats and opportunities. Quantum computers will eventually break current encryption standards, but they’ll also enable recovery techniques that are computationally impossible today. We’re partnering with quantum research labs to develop post-quantum recovery algorithms and exploring how quantum error correction principles might apply to data reconstruction.

Third, the shift toward edge computing and IoT devices is creating entirely new recovery challenges. These devices often use custom storage formats and have limited access interfaces. We’re building specialized hardware adapters and developing recovery protocols for everything from smart home devices to autonomous vehicle data recorders.

At DataNumen, we’re investing 35% of our R&D budget in these emerging areas. We’ve hired specialists in quantum cryptography and edge computing, and we’re building a dedicated AI research team. We’re also creating strategic partnerships with hardware manufacturers to ensure we have early access to new storage technologies.

Perhaps most importantly, we’re developing modular recovery frameworks that can adapt to technologies we haven’t even imagined yet. The core principle remains the same—understanding how data is stored so we can recover it when systems fail—but the implementation methods are evolving rapidly.

We’re not just preparing for the future; we’re actively shaping it by contributing to industry standards and open-source recovery tools that benefit the entire data recovery community.

Thanks for sharing your knowledge and expertise. Is there anything else you’d like to add?

What I’d emphasize is that data recovery isn’t just a technical discipline—it’s fundamentally about resilience and continuity in our digital world. Every day, we become more dependent on digital information, yet most people and businesses still treat data protection as an afterthought until disaster strikes.

The most rewarding aspect of my career has been the human stories behind the technology. I’ve helped recover everything from a grandmother’s only digital photos of her late husband to mission-critical research data that took scientists years to generate. These experiences remind me that behind every corrupted drive or failed backup is someone whose digital life hangs in the balance.

For businesses reading this, my key message is simple: test your recovery capabilities before you need them. Don’t wait for a crisis to discover that your backup strategy has gaps or that your team doesn’t know how to execute your disaster recovery plan.

Looking forward, I’m excited about how emerging technologies will make data recovery more effective and accessible. But regardless of how sophisticated our tools become, the core mission remains unchanged: ensuring that when technology fails, we can restore what matters most to people.

At DataNumen, we’re not just building software—we’re providing peace of mind in an increasingly digital world. That responsibility drives our innovation and shapes every decision we make about our products and services.

Finally, I’d encourage anyone interested in this field to remember that every expert was once a beginner. The data recovery community is remarkably collaborative and willing to share knowledge. If you’re passionate about solving complex problems and helping people recover from digital disasters, this field offers incredibly rewarding challenges and opportunities to make a real difference.