CarPlay is an Apple standard that enables a car radio or automotive head unit to be a display and controller for an iOS device. It is available on iPhone 5 and later models running iOS 7.1 or later. More than 800 car and motorcycle models support CarPlay, according to Apple. Vehicle owners can add support by installing certain aftermarket vehicle audio products. Most CarPlay systems connect to iOS through USB, some are wireless, and wireless support can be added through aftermarket dongles. CarPlay Ultra, a more integrated version of CarPlay, was first announced on Aston Martin DBX707 in May 2025. == Software == Apple's CarPlay-enabled apps include: Phone Apple Music Apple Maps Calendar Messages Audiobooks (part of Apple Books) Podcasts Settings News Developers must obtain permission from Apple to develop CarPlay-enabled apps. Such apps fall into five categories: Audio: primarily provide audio content, such as music or podcasts. Examples: Amazon Music, Audible, Google Play Music, iHeartRadio, QQ Music, Spotify, and Overcast. Navigation: turn-by-turn guidance, including searching for points of interests and navigating to a destination. Examples: AutoNavi, Baidu Maps, Google Maps, ChargeFinder and Waze. Automaker-made apps allow a user to control vehicle-specific features such as climate controls, gas levels, or radio via CarPlay. Messaging/Voice over IP (VoIP): listen to new messages and reply using dictation in an audio-only interface. Messaging apps on CarPlay integrate with third-party Siri support (known as SiriKit), while VoIP apps integrate with the iOS calling interface using CallKit. Examples: Telegram, WhatsApp, and Zoom. Food-ordering and parking-services apps. To discourage distracted driving, Siri is used extensively, providing voice turn-by-turn navigation guidance and voice-input for text messages. Newscast-style weather and stock results are announced instead of displayed. Requests that bring up visual information may be blocked when the car is in gear, and most native CarPlay apps deliver audio content with minimal interaction. CarPlay-enabled apps installed on the device appear on the CarPlay home screen unless disabled by the user. The inclusion or exclusion and order of app appearance can be changed on a per-vehicle basis. == Hardware == Most of the CarPlay software runs on the connected iPhone. The CarPlay interface provides audio output and a visual display to the vehicle's infotainment system, while adapting to the vehicle's available control methods, including touch screens, rotary dials, physical buttons, steering-wheel controls, and hands-free microphones. Aftermarket head units may support CarPlay or Android Auto, and many support both platforms. === Wired CarPlay === In a wired CarPlay configuration, the iPhone connects to the vehicle or head unit via a USB cable. The USB connection supplies power to the iPhone and provides a stable data link for audio, video, and control input. Wired CarPlay is supported by a wide range of factory-installed infotainment systems and aftermarket head units. Some third-party devices marketed as wireless CarPlay adapters operate by emulating a wired CarPlay connection to the vehicle. These devices plug into the vehicle's USB port and present themselves as a wired CarPlay interface, while separately establishing a wireless connection to the iPhone. Such devices still require the vehicle or head unit to support standard (wired) CarPlay. === Wireless CarPlay === Wireless CarPlay allows the iPhone to connect to a compatible vehicle or head unit without a physical cable. During the initial pairing process, the iPhone exchanges network credentials with the CarPlay receiver over Bluetooth. Once paired, CarPlay data is transmitted over a two-way Wi-Fi connection between the phone and the vehicle. Wireless CarPlay support depends on both the vehicle or head unit hardware and the iPhone model, and is generally limited to newer factory systems and select aftermarket receivers. == History == === Predecessor === In 2008, one year after the release of the iPhone, Mercedes vehicles were first to sell an audio system incorporating both the iPod and iPhone, equipped with 30-pin iOS input jacks. The new 2008 Harman Kardon NTG 2.5 featured full audio streaming, syncing, charging and control integrated into the steering wheel controls, instrument panel, and head unit. Apple was working with Mercedes to develop iOS compatible audio systems into their cars first only a year after iPhone launch. With an Apple Lightning-to-30-pin adapter, iPhones/iPods remain backwards-compatible with the Harman Kardon 2.5 and later models. This is the earliest audio system specifically engineered for iPod/iPhone integration, which predated CarPlay and every other manufacturer incorporating iOS into vehicles. The concept of CarPlay was based on the iOS 4 feature called "iPod Out" which was produced through several years of joint development by Apple and the BMW Group's Technology Office USA. iPod Out enabled vehicles with the necessary infrastructure to "host" the analog video and audio from a supporting iOS device while receiving inputs, such as button presses and knob rotations, from a car's infotainment system, to drive the "hosted" user interface in the vehicle's built-in display. It was announced at WWDC 2010 and first shipped in BMW Group vehicles in early 2011. The BMW and Mini option was called "PlugIn" and paved the way for the first cross-OEM platforms, introducing the concept of requiring a car-specific interface for apps (as opposed to MirrorLink's simple and insufficient mirroring of what was shown on the smartphone's screen). === Development === CarPlay's codename was Stark. Apple's Eddy Cue announced it as iOS in the Car at WWDC 2013. In January 2014, it was reported that Apple's hardware-oriented corporate culture had led to release delays. iOS in the Car was then rebranded and launched as CarPlay with significant design changes at the Geneva Motor Show in March 2014 with Ferrari, Kia, Mercedes-Benz, and Volvo among the first car manufacturers. At WWDC 2022, Apple announced plans to release an all-new version of CarPlay, informally dubbed CarPlay 2. The new version was said to be able to control vehicle functions, access vehicle stats, and take over multiple vehicle screens. Officials said they planned to release it in late 2024 and that manufacturers that are planning to adopt the new CarPlay include: Audi, Acura, Ford, Honda, Infiniti, Jaguar, Land Rover, Lincoln, Mercedes-Benz, Nissan, Polestar, Porsche, Renault, and Volvo. In January 2025, amidst delays, Apple removed the planned released date from its website. On May 15, 2025, Apple announced that next-generation CarPlay, now called CarPlay Ultra, would be included with all new vehicles from Aston Martin. Existing vehicles will also be receiving CarPlay Ultra through a future software update. It is only available in the US and Canada. == Timeline == June 2013: Apple introduced iOS in the Car; an early version of CarPlay that was never publicly released, at WWDC 2013. June 2013: BMW officials announced their cars would not support iOS in the Car; they later changed their minds. November 2013: Siri Eyes Free mode was offered as a dealer-installed accessory in the US to some Honda Accord and Acura RDX & ILX models. In December, Honda offered additional integration, featuring new HondaLink services, on some US and Canada models of the Civic and the Fit. March 2014: Apple introduced CarPlay, which was renamed from iOS in the Car with significant design changes, at the 2014 Geneva Motor Show with automakers Ferrari, Mercedes-Benz and Volvo. September 2014: A Ferrari FF was the first car with a full version of CarPlay. November 2014: Hyundai announced the Sonata sedan would be their first model with available CarPlay by the end of the first quarter of 2015. January 2015: Volkswagen announced CarPlay support would be coming later in 2015 and would be either standard or available on the majority of their 2016 model year lineup. May 2015: General Motors announced CarPlay would be available starting with 14 different 2016 model year Chevrolet vehicles. July 2015: Honda announced CarPlay would be available in their vehicles starting with the 2016 Honda Accord. December 2015: Volvo implemented CarPlay in the 2016 Volvo XC90 as their first vehicle with CarPlay support. December 2015: Mercedes-Benz confirmed that CarPlay would be available starting with select 2016 model year vehicles. January 2016: Apple released a list detailing the car models which support CarPlay. January 2016: Ford announced CarPlay would be available on all 2017 Ford/Lincoln model year vehicles equipped with the Sync 3 infotainment system. January 2016: FCA (now a part of Stellantis) announced CarPlay would be available on their UConnect infotainment system starting with select 2016 model year vehicles. March 2016: Subaru announced the beginning of CarPlay and Android Auto support, st
Beauty.AI
Beauty.AI is a mobile beauty pageant for humans and a contest for programmers developing algorithms for evaluating human appearance. The mobile app and website created by Youth Laboratories that uses artificial intelligence technology to evaluate people's external appearance through certain algorithms, such as symmetry, facial blemishes, wrinkles, estimated age and age appearance, and comparisons to actors and models. The Beauty.AI 2.0 contest caused great concern over important ethical issues with deep neural networks such as age, race and gender bias and lead to the creation of the Diversity.AI think tank dedicated to developing new methods for uncovering and managing bias in artificially intelligent systems. Beauty.AI was also an attempt to find approaches on how machines can perceive human face through evaluating particular features, commonly associated with health and beauty. == Concept == The Beauty.AI app was created by Youth Laboratories, a company based out of Russia and Hong Kong that focuses on facial skin analytics. The bioinformation company Insilico Medicine assists in the Beauty.AI app by testing its deep learning techniques to the app. One goal of the app is to reduce the need for human and animal testing as well as improving people's overall health. Its first contest was started in December 2016, and the results were announced in August 2016. More than 60,000 people submitted entries into the contest. The mobile app uses artificial intelligence technology to inspect photographs for certain facial features in order to both determine a person's beauty through artificial means by multiple robots. Part of the Beauty.AI app's purpose is to collect visual and anecdotal data to improve its creator's Youth Laboratories skin analyst skills. == Accusations of racism == There were a total of 44 individuals from different age groups and genders judged as the most attractive, with 37 white entrants, six Asian entrants, and one dark-skinned entrant. The app has received criticism from social justice advocates and computer science professionals. However, Alex Zhavoronkov, PhD, chief science officer of Youth Laboratories and chief technology officer Konstantin Kiselev, both for Youth Laboratories, noted that a lack of data may have contributed to these results. Also, Kiselev added that another issue was that approximately 75% of entrants were white Europeans, whereas only 7% and 1% were from India and Africa, respectively. Kiselev stated that they would work on doing more and better outreach to these areas to improve in this area. Despite this, it was said by Dr. Zhavoronkov that the AI would discard photos of dark-skinned people if the lighting is too poor. Dr. Zhavoronkov vowed to weed out the issues for the next beauty pageant and to try to avoid a similar controversy in the future.
Threat actor
In cybersecurity and risk assessment, a threat actor (or threat agents, attackers, or adversaries) is a person, group, organisation, state, or other entity with the ability to cause, carry, transmit, support, or exploit a threat. Threat actors are commonly analysed according to their motivations, resources, technical capability, access to systems, relationship to a target, and degree of connection to state authority. They may exploit vulnerabilities, conduct social engineering, steal or monetise data, disrupt operations, or support other actors who carry out such activity. Because the term covers a wide range of actors, researchers and security organisations use taxonomies that distinguish between groups such as cybercriminals, state-linked actors, ideologically motivated actors, thrill seekers or trolls, insiders, and competitors. Threat actor classifications are used in risk management, cyber threat intelligence, and incident response to connect observed behaviour with possible objectives and likely future activity. The categories are not always mutually exclusive: the same actor may combine criminal, ideological, commercial, or state-linked motivations, and different organisations may use different names for similar actors. == Risk assessment and security management == In risk assessment, threat actor analysis is used to identify who or what may create, carry, transmit, support, or exploit a threat, and how that actor relates to the system being assessed. Rausand and Haugen classify threat actors by their relationship to the system, distinguishing between internal and external actors, and by intent, distinguishing between intentional and unintentional actors. Threat actor classification may also support incident investigation. Rogers argued that actor categories could be inferred from observable case points, such as tools used, messages left, data targeted, forensic knowledge, and the degree of damage, allowing investigators to assess likely motivation and skill level. Later work similarly linked actor classification to operational analysis. Chng, Lu, Kumar and Yau proposed a framework connecting hacker types, motivations and typical strategies, arguing that observed behaviour before or during an attack can help analysts infer the likely type of actor involved. At the strategic level, actor analysis may consider an actor's resources, capabilities, degree of state involvement, motivations and objectives. == Landscape == The United Nations Institute for Disarmament Research has described the contemporary cyberthreat landscape as involving an increasingly diverse and interconnected set of actors, including state-led operations, cybercriminal syndicates, ideological hacktivists, commercial cyber mercenaries, private companies and civilian volunteers. Its 2026 report argued that these actors vary in resources, technical sophistication and relationships with states, making it traditional distinctions between state, civilian combatant roles, and legitimate and illegitimate conduct harder to apply. == Academic taxonomies == Early taxonomies classified hackers by activity, skill, motivation, or criminal profile. Landreth proposed six categories based on activity: novice, student, tourist, crasher, and thief. Hollinger classified computer misuse into pirates, browsers, and crackers, describing a progression from less-skilled activity to more technically serious offences. Chantler used attributes including activity, skill, knowledge, motivation, and duration of involvement to distinguish between an elite group, neophytes, and "losers and lamers". Parker proposed seven profiles of cybercriminals: pranksters, hacksters, malicious hackers, personal problem solvers, career criminals, extreme advocates, and malcontents, addicts, and irrational or incompetent people. In 2000, Marc Rogers proposed a taxonomy of hackers with seven, non-mutually-exclusive categories: newbie/tool kit users, cyber-punks, internals, coders, old guard hackers, professional criminals, and cyber-terrorists. Rausand and Haugen distinguish between internal and external threat actors, and between intentional and unintentional threat actors. Internal actors have some relationship with, access to, or position inside the system or organisation, while external actors operate from outside it. Intentional actors seek to create, exploit, or support a threat event, whereas unintentional actors may cause or enable a threat event through error, negligence, accident, or lack of awareness. Rogers later revised his hacker taxonomy into Novices, Cyber-punks, Internals, Petty Thieves, Virus Writers, Old Guard hackers, Professional Criminals, Information Warriors, and, more tentatively, Political Activists. In the model, motivation is grouped into four broad domains: curiosity, notoriety, revenge, and financial gain. A 2022 review by Chng, Lu, Kumar and Yau examined 11 hacker typologies published over three decades and proposed a unified framework linking hacker types, motivations, and strategies. The framework identified 13 hacker types and seven motivations, and argued that observed strategies during an attack can help analysts infer the likely type of actor involved. == Government taxonomies == Taxonomies of threat actors by governments are much more likely to include state-level threat actors. In the United States the National Institute of Standards and Technology (NIST) uses the term threat source in its risk-assessment guidance: organisations are directed to identify and characterise threat sources of concern, including capability, intent and targeting for adversarial threat sources, and the range of effects for non-adversarial threat sources. NIST treats threat-source identification as part of the risk-assessment process, alongside identifying threat events, vulnerabilities, likelihood and impact. In the EU, European Union Agency for Cybersecurity publishes the annual ENISA Threat Landscape, which analyses cyber incidents and adversary behaviour affecting the European Union. The 2025 report analysed selected incidents from the previous year and grouped activity around cybercrime, state-aligned activity, foreign information manipulation and interference, and hacktivism. In ENISA's 2025 analysis, hacktivist activity dominated reporting, representing almost 80% of recorded incidents and consisting mainly of low-level distributed denial-of-service operations. ENISA also reported increasing convergence between hacktivism, cybercrime and state-nexus activity, including state-aligned use of hacktivist personas, hacktivist adoption of ransomware, and false-flag or impersonation activity. At the UN level, A 2026 report by the United Nations Institute for Disarmament Research described the cyberthreat landscape as involving state-led operations, cybercriminal syndicates, ideological hacktivists, commercial cyber mercenaries, and civilian volunteers, with actors varying in resources, technical sophistication, and links to states. Canada defines threat actors as states, groups, or individuals who aim to cause harm by exploiting a vulnerability with malicious intent. A threat actor must be trying to gain access to information systems to access or alter data, devices, systems, or networks. The Japanese government's National Centre of Incident Readiness and Strategy (NISC) was established in 2015 to create a "free, fair and secure cyberspace" in Japan. The NICS created a cybersecurity strategy in 2018 that outlines nation-states and cybercrime to be some of the most key threats. It also indicates that terrorist usage of the cyberspace needs to be monitored and understood. The Security Council of the Russian Federation published the cyber security strategy doctrine in 2016. This strategy highlights the following threat actors as a risk to cyber security measures: nation-state actors, cyber criminals, and terrorists. == Techniques == Threat actors use techniques like Social engineering (security), and Phishing, alongside technical exploits like Cross-site scripting, SQL injection, and denial-of-service attacks. == Limitations == In practice, actor categories may overlap (Edward Snowden for example), and the same activity may combine features associated with hacktivism, cybercrime and state-linked operations. The lines between hacktivism, cybercrime and state-nexus activity had continued to blur, with shared toolsets, overlapping methods, fake personas, hacktivist adoption of ransomware, and cybercriminal or state-linked actors masquerading as other groups. Threat actor analysis also has limits as a risk-management method. NIST notes that risk assessments depend on their purpose, scope, assumptions, constraints, information sources, risk model and analytic approach, and that assessments are tied to particular time frames and organisational contexts. NIST also warns that simple threat-vulnerability pairing may be undesirable or problematic where there are many threats and vulnerabilities, and recom
Tensor glyph
In scientific visualization a tensor glyph is an object that can visualize all or most of the nine degrees of freedom, such as acceleration, twist, or shear – of a 3 × 3 {\displaystyle 3\times 3} matrix. It is used for tensor field visualization, where a data-matrix is available at every point in the grid. "Glyphs, or icons, depict multiple data values by mapping them onto the shape, size, orientation, and surface appearance of a base geometric primitive." Tensor glyphs are a particular case of multivariate data glyphs. There are certain types of glyphs that are commonly used: Ellipsoid Cuboid Cylindrical Superquadrics According to Thomas Schultz and Gordon Kindlmann, specific types of tensor fields "play a central role in scientific and biomedical studies as well as in image analysis and feature-extraction methods."
Collaboration-oriented architecture
Collaboration Oriented Architecture (COA) is a computer system that is designed to collaborate, or use services, from systems that are outside of the operators control. Collaboration Oriented Architecture will often use Service Oriented Architecture to deliver the technical framework. Collaboration Oriented Architecture is the ability to collaborate between systems that are based on the Jericho Forum principles or "Commandments". Bill Gates and Craig Mundie (Microsoft) clearly articulated the need for people to work outside of their organizations in a secure and collaborative manner in their opening keynote to the RSA Security Conference in February 2007. Successful implementation of a Collaboration Oriented Architecture implies the ability to successfully inter-work securely over the Internet and will typically mean the resolution of the problems that come with de-perimeterisation. == Etymology == The term Collaboration Oriented Architectures was defined and developed in a meeting of the Jericho Forum at a meeting held at HSBC on 6 July 2007. == Definition == The key elements that qualify a security architecture as a Collaboration Oriented Architecture are as follows; Protocol: Systems use appropriately secure protocols to communicate. Authentication: The protocol is authenticated with user and/or system credentials. Federation: User and/or systems credentials are accepted and validated by systems that are not under your (locus of) control. Network Agnostic: The design does not rely on a secure network, thus it will operate securely from an Intranet to raw-Internet Trust: The collaborating system have the capacity to be able to confirm to a specified degree of confidence that the components in a transaction chain have. Risk: The collaborating systems can make a risk assessment on any transaction based on the communicated levels of required trust, based on the required degree of identity, confidentiality, integrity, availability. == Authentication == Working in a collaborative multi-sourced environment implies the need for authentication, authorization and accountability which must interoperate / exchange outside of your locus / area of control. People/systems must be able to manage permissions of resources and rights of users they don't control There must be capability of trusting an organization, which can authenticate individuals or groups, thus eliminating the need to create separate identities In principle, only one instance of person / system / identity may exist, but privacy necessitates the support for multiple instances, or one instance with multiple facets, often referred to as personas Systems must be able to pass on security credentials /assertions Multiple loci (areas) of control must be supported
List of performance analysis tools
This is a list of performance analysis tools for use in software development. == General purpose, language independent == The following tools work based on log files that can be generated from various systems. time (Unix) - can be used to determine the run time of a program, separately counting user time vs. system time, and CPU time vs. clock time. timem (Unix) - can be used to determine the wall-clock time, CPU time, and CPU utilization similar to time (Unix) but supports numerous extensions. Supports reporting peak resident set size, major and minor page faults, priority and voluntary context switches via getrusage. Supports sampling procfs on supporting systems to report metrics such as page-based resident set size, virtual memory size, read-bytes, and write-bytes, etc. Supports collecting hardware counters when built with PAPI support. == Multiple languages == The following tools work for multiple languages or binaries. == C and C++ == Arm MAP, a performance profiler supporting Linux platforms. AppDynamics, an application performance management service for C/C++ applications via SDK. AQtime Pro, a performance profiler and memory allocation debugger that can be integrated into Microsoft Visual Studio, and Embarcadero RAD Studio, or can run as a stand-alone application. IBM Rational Purify was a memory debugger allowing performance analysis. Instruments (bundled with Xcode) is used to profile an executable's memory allocations, time usage, filesystem activity, GPU activity etc. Intel Parallel Studio contains Intel VTune Amplifier, which tunes both serial and parallel programs. It also includes Intel Advisor and Intel Inspector. Intel Advisor optimizes vectorization (use of SIMD instructions) and prototypes threading implementations. Intel Inspector detects and debugs races, deadlocks and memory errors. Parasoft Insure++ provides a graphical tool that displays and animates memory allocations in real time to expose memory blowout, fragmentation, overuse, bottlenecks and leaks. Visual Studio Team System Profiler, commercial profiler by Microsoft. == Java == inspectIT is an open-source application performance management (APM) service for monitoring and analyzing software applications, available under the Apache License, Version 2.0 (ALv2). JConsole is the profiler which comes with the Java Development Kit JProfiler JRockit Mission Control, a profiler with low overhead. Netbeans Profiler, a profiler integrated into the NetBeans IDE (internally uses jvisualvm profiler) Plumbr, Java application performance monitoring with automated root cause detection. Links memory leaks, GC inefficiency, slow database and external web service calls, locked threads, and other performance problems to the line in source code that causes them. OverOps, Continuous reliability for the modern software supply chain, automatically detect and deliver root cause automation for all errors. VisualVM is a visual tool integrating several commandline JDK tools and lightweight profiling capabilities. It is bundled with the Java Development Kit since version 6, update 7. == JavaScript == The Firefox web browser's developer tools contain a Performance tool, which gives insight into JavaScript performance of a website. Microsoft Visual Studio AJAX Profiling Extensions is a free profiling tool for JavaScript by Microsoft Research. == .NET == CLR Profiler is a free memory profiler provided by Microsoft for CLR applications. GlowCode is a performance and memory profiler for .NET applications using C# and other .NET languages. It identifies time-intensive functions and detects memory leaks and errors in native, managed and mixed Windows x64 and x86 applications. Visual Studio == PHP == BlackFire.io Dbg Xdebug is a PHP extension which provides debugging and profiling capabilities.
Stanza Living
Stanza Living is the common brand name for Dtwelve Spaces Private Limited. It provides fully-managed shared living accommodations to students and young professionals. Founded by Anindya Dutta and Sandeep Dalmia, the company is present across 23 cities including Delhi, NCR, Bangalore, Visakhapatnam, Hyderabad, Chennai, Coimbatore, Indore, Pune, Baroda, Vijayawada, and Dehradun, Kota in India, with a capacity of 70,000 beds. Stanza Living is a technology-enabled housing concept which provides fully-furnished residences with amenities like meals, internet, laundry services, housekeeping, security and community engagement programmes. The company has an asset-light business model under which it engages in long-term lease agreements with property owners/developers, who convert their assets into shared living residences as per company guidelines. These assets are subsequently operated by Stanza Living. == Industry background == A report by Cushman & Wakefield (C&W) titled 'Exploring the Student Housing Universe in India City Insights', estimates that there were over 9.08 million migrant student enrolments in India's higher educational institutions (HEIs) for the year 2018-19 who need quality accommodation facilities. According to the report, Delhi-NCR, Mumbai, and Pune are the three biggest markets for student housing in the country, and these cities require an additional 4.75 lakh beds from organized co-living operators to meet the current demand. == History == Stanza Living provides tech-enabled, fully managed community living facilities for students and working professionals. The company was launched as a student housing business in Delhi NCR with a capacity of 100 beds, and grew to 14 cities by 2019. By early 2020, the company began catering to working professionals as well. The company has a combined inventory of 70,000 beds under management for both students and working professionals. Stanza Living is currently valued at $300 million. It has raised a capital of about $70 million from leading global investors like Falcon Edge Capital, Sequoia Capital, Matrix Partners and Accel Partners. November 2017 – Seed funding, September 2018 – Series A, March 2019 – Debt financing, July 2019 – Series C round, December 2019 - Debt financing. The company has invested in building technology products for business efficiency and consumer experience, like the Stanza Resident App and Stanza Real Estate App. Stanza Living has close to 1,500 employees across India. It is recognized among Top Real Estate Tech Startups of 2020 across the globe by research and analysis company Tracxn. The company has been shortlisted among Top 25 Start-ups of India in 2019 by LinkedIn == Founders == Stanza Living was co-founded by Anindya Dutta and Sandeep Dalmia. Sandeep Dalmia is an alumnus of Delhi College of Engineering and IIM Ahmedabad. Prior to Stanza, he was a Principal at Boston Consulting Group, working across India, US and South East Asia markets. Anindya Dutta was previously a Real Estate investor with Oaktree Capital and prior to that, he worked at Goldman Sachs in London. He is an alumnus of IIT Kharagpur and IIM Ahmedabad.