Senior Principal Scientist, Adobe
For the past several years, I’m working on applying machine learning towards understanding the structure and semantics of documents.
Most recently, I developed the ML model powering Acrobat Liquid Mode.
From Adobe blog:
With the push of a button, Liquid Mode automatically reformats text, images, and tables for quick navigation and consumption on small screens. Powered by Adobe Sensei, Liquid Mode uses AI and machine learning in the background to understand and identify parts of a PDF, like headings, paragraphs, images, lists, tables, and more. It also attempts to understand the hierarchy and ordering of those parts to reformat a static PDF into a more dynamic and customizable experience.
Press coverage: The Wall Street Journal - Adobe Freshens Up Its PDF for Mobile, Fortune - Adobe 2020: Change the World, Fast Company - Adobe finally figured out how to make PDFs make sense on a phone, CNET - Adobe peps up PDF on smartphones with AI-powered Liquid reformatting, Business Insider - Adobe exec explains why the firm is using AI to transform the way people access and use documents on mobile, TechCrunch - Adobe’s ‘Liquid Mode’ uses AI to automatically redesign PDFs for mobile devices, Axios - Adobe reinvents PDF to work better on phones, VentureBeat - Adobe’s Liquid Mode leverages AI to reformat PDFs for mobile devices, Engadget - Adobe’s Liquid Mode uses AI to make PDFs easier to read on phones
Acrobat and Reader Sandboxes
Before that, I worked in application security, and specifcally on the design and implementation of the Adobe Reader Protected Mode sandbox. ASSET has some posts anouncing and describing it. Which was later integrated into Acrobat Protected View Sandbox.
Adobe Reader Protected Mode represents an exciting new advancement in attack mitigation. Even if an exploitable security vulnerability is found by an attacker, Adobe Reader Protected Mode will help prevent the attacker from writing files, changing registry keys or installing malware on potential victims’ computers.
Press coverage: PCWorld - Why a “Sandbox” Makes Adobe Reader More Secure, ComputerWeekly - Sandboxing for secure app development: Adobe Reader’s ‘protected mode’, ZDNet - Adobe adding ‘sandbox’ to PDF Reader to ward off hacker attacks, PCMag - Adobe Explains More of Reader X Protected Mode
Patents and publications
- Several patents applied for at the USPTO
- Co-authored a paper on Black-box Explanation of Object Detectors via Saliency Maps (not peer reviewed)
Vulnerability Research – Bug Bounties and CVEs
- Listed in the Top 50 security researchers for 2015 by Microsoft Security Response Center (MSRC).
- Shared the $1000 bounty and mentioned in The Chromium Projects Security Hall of Fame for a reporting a Chrome sandbox security bug.
- Reported and credited in 18 CVEs for Windows and Internt Explorer sandbox vulnerabilities; see my CVE credits page.
Honors and Awards
- Received several reward checks from Don Knuth.
- Was selected by Don Knuth to proof-read his books Selected Papers on Design of Algorithms and Selected Papers on Fun and Games (as part of a 4-member team).
- Picked up several prizes at the CodeChef competetive programming contests
- Was among the top 20 students to qualify the Indian National Physics Olympiad (InPhO) in 1999
- Recently, I’ve been mostly been using Python (with TensorFlow) for the ML projects
- My prior work was largely in C++ (on Windows and Mac), with heavy x86-assembly debugging.
- I have a reasonably good understanding of the PDF format
- For jun, I enjoy programming in EMACS LISP and Haskell
B.E. (with honors) in Computer Science, BITS Pilani, India (August 1999 – June 2003). I recevied a Bronze Medal (CGPA 9.92/10) and many merit scholarships.