Context Summary: LinkedIn + Resume Strategy for Shaswat Gupta
User profile and current positioning
The user is Shaswat Gupta, a recent MSc Computer Science graduate from ETH Zürich, previously BTech Mechanical Engineering at IIT Bombay, where he graduated Department Rank 1 / Gold Medalist, GPA 9.6/10. He is joining IBM Research Zürich full-time as a Software Developer in a research-facing role. His technical identity should now center on:
A research-oriented software engineer working across data systems, ML systems, and applied machine learning — with research output from ETH Zürich and applied-ML deployment experience from AB InBev.
This spine should govern all profile and resume edits. All profile elements should either support this spine or be compressed/cut.
The user originally had an over-dense, credential-heavy LinkedIn/CV style. An external LinkedIn reviewer diagnosed the issue as “performative credentialism,” claiming the profile tries too hard to prove excellence instead of demonstrating it. We refined that diagnosis to something more accurate:
Root issue: high signal, low editorial hierarchy / undisciplined signal density. The profile contains strong evidence, but everything is presented at equal intensity, making the reader work too hard to infer the user’s core professional identity.
The guiding principle established in the chat:
Do not replace old credential-stacking with new credential-stacking. IBM Research Zürich, ETH, SIGMOD, VLDB, IIT, and AB InBev should feel inevitable under one coherent identity, not stacked to impress.
Tone target: calm, precise, technical, international, not promotional. Avoid self-awarded praise, prestige explanations, and inflated verbs.
Forbidden / discouraged terms and patterns included:
Preferred verbs:
⸻
Key updated facts to preserve
The user’s new profile facts:
⸻
LinkedIn headline strategy
Current old headline:
| MS CS @ETH Zurich | IIT Bombay Gold Medalist, Rank 1 | ML Engineer | Ex-World Bank, Budweiser, ISB |
Problems:
Recommended headline:
| Software Developer @ IBM Research Zürich | ML & Data Systems | ETH MSc CS |
Slightly denser alternative:
| Software Developer @ IBM Research Zürich | ETH MSc CS | Data Systems, ML Systems & Applied ML |
Recommendation: prefer the leaner version. It is cleaner and lets the About section carry nuance.
Avoid putting SIGMOD/VLDB in headline until papers are public, titled, and linkable. Otherwise it can read as publication-name-dropping. Keep SIGMOD/VLDB in About, Publications, Projects, and Featured.
Avoid “IIT Bombay Gold Medalist, Rank 1” in the headline. It belongs in About/Education/Awards, not the header.
⸻
LinkedIn About section
Old About section was too promotional:
Recommended About:
I am a Software Developer at IBM Research Zürich and recently completed my MSc in Computer Science at ETH Zürich. My work sits at the intersection of data systems, ML systems, and applied machine learning, with recent research on provisioning-aware query routing for heterogeneous lakehouse engines. My ETH thesis received a 6/6; a related workshop paper was accepted at SIGMOD, and an extended version is under review at VLDB. Previously, I worked as a Data Scientist at AB InBev, building forecasting, recommender, and optimization systems for supply-chain and commercial analytics. I graduated Department Rank 1 and Gold Medalist from IIT Bombay, with a parallel background in journalism and technical communication.
Notes:
⸻
Featured section strategy
Featured should carry artifacts, not claims.
Feature 3–5 items max:
Do not feature:
⸻
Publications section
Add LinkedIn native Publications section.
Format:
[SIGMOD paper title] SIGMOD Workshop, [SIGMOD year] — Accepted [VLDB paper title] VLDB, [VLDB year] — Under Review
Cautions:
⸻
Experience strategy
Experience ordering:
General rule:
⸻
IBM Research Zürich experience
Keep conservative until the project has substance.
Recommended full-time entry:
IBM Research Zürich | Software Developer | [start month] 2026 – Present • Research-facing software development role in Zurich, working across systems engineering and applied machine learning.
Do not use “Research Scientist” unless official.
For thesis placement:
Recommended thesis entry if used in Experience:
IBM Research Zürich / ETH Zürich | Master’s Thesis | [start] 2025 – Sep 2025 • Provisioning-aware query routing for heterogeneous lakehouse engines; thesis graded 6/6.
If collaboration continued:
IBM Research Zürich / ETH Zürich | Research Collaboration | [start] 2025 – Present • Provisioning-aware query routing for heterogeneous lakehouse engines; thesis graded 6/6.
Avoid contradictory dates such as Sep 2025–2026 if MSc ended Sep 2025 unless it is truly a post-thesis collaboration.
⸻
ETH D-MTEC / Chair of Technology and Innovation Management RA
The initially proposed compressed two-bullet version was too diluted. This role has strong technical signal and deserves 3 bullets, one per major project.
Recommended LinkedIn experience version:
ETH Zürich (D-MTEC) | Research Assistant | Mar 2024 – Aug 2025 • Built statistical and NLP pipelines for ETH-Zühlke AI-adoption research across 600+ enterprises, automating 10,000+ statistical tests and 2,600+ visualizations. • Engineered a concurrent multi-format document-processing system for 20,000+ Unicode Technical Consortium documents, achieving 94% extraction success and 42% lower LLM API costs. • Developed an asyncio-based semiconductor patent analytics platform for 10,000+ patents, using BERTopic, Sentence Transformers, UMAP, and HDBSCAN to identify 80+ technology clusters.
More concise alternative:
• Built statistical and NLP pipelines for ETH-Zühlke research on AI adoption across 600+ enterprises, reducing analysis time by 80% and generating 2,600+ research visualizations. • Engineered a concurrent document-processing system for 20,000+ Unicode Technical Consortium documents, with 94% extraction success and 42% lower OpenAI API costs. • Developed a semiconductor patent analytics platform for 10,000+ patents, using BERTopic and Sentence Transformers to identify 80+ technology clusters and 5 major technological shifts.
Skills to attach:
⸻
AB InBev full-time role
Important strategic point: AB InBev is the user’s only major relevant full-time pre-ETH experience, and it served as proof that he could do strong applied ML/data work before ETH. Do not dilute too much. Use controlled density.
Current old content had:
Recommended full-time AB InBev entry with 4 bullets:
AB InBev — Growth Analytics Center | Data Scientist | Aug 2022 – Aug 2023 • Built logistics forecasting and route-optimization systems for US supply-chain analytics across 2,000+ distribution routes. • Developed ensemble time-series models using Prophet, SARIMAX, XGBoost, and classical forecasting methods, improving forecast accuracy by 15%. • Built a Gurobi/PuLP integer-programming optimizer and scenario simulator for logistics cost-to-serve planning. • Delivered $2.4M in annual savings, led a 3-analyst enhancement squad, and received AB InBev’s Pint and Pitcher awards.
Alternative if preserving nested promotions:
Full Stack Data Scientist | Feb 2023 – Aug 2023 • Delivered the production enhancement and scenario-planning layer for logistics forecasting and cost-to-serve optimization. • Led a 3-analyst enhancement squad and received AB InBev’s Pitcher Award for global impact. Associate ML Engineer | Aug 2022 – Jan 2023 • Built forecasting and route-optimization systems across 2,000+ US distribution routes. • Improved forecast accuracy by 15% and supported $2.4M in annual savings through ensemble forecasting and integer programming.
Full-time AB InBev skills:
Prioritize if limited:
⸻
AB InBev internship
Current old content:
Final recommendation:
Recommended internship entry:
AB InBev — Growth Analytics Center | Data Science Intern | May 2021 – Jul 2021 • Built an SVD/NMF recommender system for cross-selling across 18,500+ Tanzanian retailers. • Designed interaction scoring and evaluation metrics for precision, recall, diversity, novelty, and coverage, improving performance by 30% over existing baselines. • Supported $6M in projected annual sales growth; selected as Best Intern among 100+ peers and offered a full-time Associate ML Engineer role.
Artifact: Keep:
Best Intern Award Selected as Best Intern among 100+ interns.
or:
Best Intern Award Recognition for product recommendation engine internship at AB InBev.
Remove:
Brewery Visit Had the wonderful opportunity to witness the king of beers…
Internship skills:
⸻
Protium / Growth Source Financial Technologies
This is the strongest technical fit among the older pre-ETH roles because it directly supports optimization/recommendation/financial analytics.
Current old content had inflated phrasing:
Clean version:
Growth Source Financial Technologies (Protium) | Data Science Intern | Apr 2020 – Jul 2020 • Built a linear-programming framework for MSME debt refinancing, modeling feasible loan-consolidation options using collateral appreciation. • Developed a loan recommendation system ranking refinancing options across 350+ client portfolios. • Prototyped geospatial sales-territory clustering for six metropolitan markets and built yield-tracking analytics across 600+ bond securities.
Artifact: Keep recommendation letter, captioned simply:
Partner-signed recommendation letter for data science internship work.
Remove:
Skills:
⸻
World Bank Group x KPMG India
Keep as separate experience under Option B, but compressed.
Recommended:
World Bank Group × KPMG India | Summer Associate | Apr 2021 – May 2021 • Developed 10-year green-hydrogen demand models across three countries, analyzing end-use demand across manufacturing, energy, and mobility sectors. • Compared conventional fuels with cleaner alternatives on technical feasibility and economic viability. • Built a market-readiness framework using renewable-energy policy, planned industrial capacity, and corporate sustainability signals.
If LinkedIn forces one company, use The World Bank as company and mention KPMG in description.
Artifact: Keep “Green Hydrogen in Developing Countries” if professional. Caption:
Research report on green-hydrogen investment opportunities in emerging economies.
Avoid:
Provides a foundational analysis… Cited multiple times.
unless citations are verified and linked.
Skills:
⸻
Indian School of Business / MIHM
Keep as separate experience, compressed.
Recommended:
Indian School of Business — Max Institute of Healthcare Management | Research Assistant | Aug 2020 – Nov 2020 • Modeled SARS-CoV-2 transmission risk in agricultural market systems under Prof. Sarang Deo at ISB’s Max Institute of Healthcare Management. • Analyzed grain movement across 3,200 agricultural markets serving 12,800 villages. • Built geospatial datasets and adapted regression/SIR-style models to study procurement-network risk during COVID-19.
Current old content overclaimed “directly informing public health intervention strategies” and “exceptional research.” Use only if strongly evidenced.
Artifact: Keep if relevant; caption neutrally:
Research artifact from COVID-era epidemiological modeling work at ISB MIHM.
If the artifact is actually about testing and not agricultural markets, ensure caption does not misrepresent it.
Skills:
⸻
Capital Foods / Warehousing Automation
General recommendation:
Possible minimal version if needed:
Warehousing Automation Capital Foods Researched FMCG warehousing automation technologies and prepared executive recommendations for modernization planning.
But recommended to archive.
⸻
RephraseAI / Synthetic Media
Potentially useful because of GenAI/synthetic media and Adobe acquisition, but user’s actual role was product validation / TTS data collection / demo, not core model development. Do not overstate.
Recommended if kept in Projects:
Synthetic Media User Testing and TTS Data Collection RephraseAI Supported synthetic-video product validation at RephraseAI, including AWS AI Conclave demonstrations, custom-voice TTS data collection, and Mechanical Turk user studies. Designed a feature validation study with 160+ respondents to evaluate generated media quality and user perception.
Skills:
But recommendation: archive unless user specifically wants a GenAI/synthetic-media signal.
⸻
Education section strategy
Education should be dignified and factual. Remove rankings, course lists, and selectivity percentages that create credential clutter.
ETH:
Recommended LinkedIn ETH section:
ETH Zürich Master of Science — Computer Science Sep 2023 – Sep 2025 Focus: Machine Intelligence; Data Management Systems Thesis: 6/6 — provisioning-aware query routing for heterogeneous lakehouse engines
If mentioning both aggregate and thesis:
Grade: 5.44/6 Thesis: 6/6 — provisioning-aware query routing for heterogeneous lakehouse engines
Recommendation: For LinkedIn, omit aggregate grade and mention only thesis grade clearly as thesis grade. For CV/resume, use:
MSc Computer Science, ETH Zürich — GPA: 5.44/6; Thesis: 6/6
Do not write:
Grade: 6/6
because that implies overall degree grade.
IIT Bombay: Remove:
Recommended IIT section:
Indian Institute of Technology Bombay Bachelor of Technology — Mechanical Engineering 2018 – 2022 Grade: Department Rank 1 / 165 · GPA 9.6/10 · Gold Medalist Activities and societies: Editor, Student Journalism Wing; Project Leader, Data Analytics Team; debating; public speaking; technical competitions.
Alternative if including ETH exchange:
Activities and societies: Editor, Student Journalism Wing; Project Leader, Data Analytics Team; selected exchange student at ETH Zürich; debating and public speaking.
Avoid including:
International Student Delegate @ Harvard, Princeton
in IIT education. It reads name-droppy and belongs elsewhere if anywhere.
⸻
Licenses & Certifications
Recommendation: remove/hide almost all. At this level, they are wrong-level signals and make the profile look junior.
Items and decisions:
Best choice:
Licenses & Certifications: hidden / empty
If preserving HPAIR/SABF somewhere:
Selected delegate to Harvard HPAIR and South American Business Forum.
But recommendation: omit from main LinkedIn.
⸻
Test Scores
Recommendation: remove/hide entire Test Scores section.
Scores:
Decisions:
Reason: Profile should say “research-oriented software engineer,” not “candidate proving aptitude.”
⸻
Awards section
Current awards:
Keep all seven. They are defensible and useful. But clean descriptions.
Recommended ordering:
Clean descriptions:
Letter of Distinction:
Recognized for the ETH Large-Scale AI Engineering course, involving hands-on distributed training on CSCS Alps.
KC Mahindra:
Scholarship for graduate studies abroad.
Journalism Color:
Institute award for contribution to student journalism; one of two recipients selected that year.
Heyning-Roelli:
Scholarship supporting international exchange at ETH Zürich.
Department Rank 1 & Gold Medalist:
Graduated Rank 1 of 165 students in Mechanical Engineering.
OPJEMS:
Selected among three IIT Bombay recipients for academic and leadership record.
Institute Academic Award:
Awarded to two students for highest academic performance during the year.
Do not use:
Thumbnails: Keep only clean, official, polished artifacts. Remove random event photos, blurry certificate screenshots, decorative award images, or social-media scrapbook items.
⸻
Volunteering section
Keep both volunteering items, cleaned heavily. They show communication leadership and data-for-institutional-decisions.
Insight, IIT Bombay
Current:
Recommended:
Editorial Board Member Insight, IIT Bombay Apr 2022 – Mar 2023 • Led a 20-member editorial board for IIT Bombay’s official student media platform, coordinating reporting across campus issues, student life, and institutional affairs. • Managed editorial workflows, stakeholder communication, and long-form writing for a 10,000+ student community.
If preserving readership:
• Managed editorial workflows and long-form writing for a 10,000+ student community and wider alumni readership.
Avoid using “0.9M+ global readers” unless cleanly defensible.
Artifact caption:
IIT Bombay Journalism Color Award Institute award for contribution to student journalism.
Avoid:
Exclusive Honor recognising exceptional contribution… Awarded to only 2/10,000+ students.
Skills:
Data Analytics and Visualization Team, IIT Bombay
Recommended:
Project Leader Data Analytics and Visualization Team, IIT Bombay Apr 2021 – Mar 2022 • Led student analytics projects using survey data, statistical analysis, and visualization to support institute-level reporting. • Analyzed 1,400+ COVID-era student responses and 500+ graduate admissions outcomes, publishing reports and dashboards for the campus community.
Alternative technical bullet:
• Built statistical analyses and visual dashboards for institute-level reports on COVID-era student experience and graduate admissions outcomes.
Artifacts: Keep:
Caption:
Graduate admissions analysis and dashboard for IIT Bombay students.
Avoid “delivering institutional intelligence to 10,000+ prospective students” as it sounds consultant-ish.
Skills:
Volunteering should remain secondary, not Experience.
⸻
Projects strategy
User clarified:
Projects section strategy:
Projects = artifact-backed technical work that does not deserve full Experience weight. Keep only projects with code, website, report, or clear technical artifact. Write them as engineering/research projects, not as “led ML research.”
Avoid saying:
Recommended project lineup:
Archive:
Provisioning-Aware Query Routing Project
Recommended:
Provisioning-Aware Query Routing for Lakehouse Engines Associated with ETH Zürich / IBM Research Zürich Built a cost-aware routing framework for heterogeneous lakehouse engines, combining query latency prediction with spill-free memory estimation. Thesis graded 6/6; related workshop paper accepted at SIGMOD and extended version under review at VLDB.
Skills:
SimpleSleepNet
Recommended:
SimpleSleepNet: Self-Supervised Learning for EEG Sleep Staging Associated with ETH Zürich Built a lightweight contrastive-learning framework for EEG sleep-stage classification, optimized for limited-label medical signal settings. Achieved 80%+ accuracy with a 200K-parameter model and evaluated 13 EEG signal augmentations across amplitude, frequency, temporal, noise, and masking transformations.
Skills:
Do not attach TensorFlow unless significantly used.
DeepSleepBench
Recommended:
DeepSleepBench: Neural Representations for EEG Associated with ETH Zürich Benchmarked contrastive, masked-prediction, and hybrid self-supervised objectives for EEG sleep-stage classification. Compared CNN, CNN+Attention, and Transformer backbones; CNN+Attention with contrastive objectives produced the strongest representations in the benchmark.
Skills:
Demand Planning Automation / Glenmark
Optional fourth project if Glenmark not in Experience:
Demand Planning Automation Glenmark Pharmaceuticals Built automated demand-planning analytics for 5,000+ SKUs across 20+ countries, with redesigned KPI calculations and validation workflows. Reduced reporting cycle time by 75% through Python, SQL, Tableau, and cloud-backed data pipelines.
Skills:
Recommendation: Prefer Demand Planning Automation over RephraseAI for user’s target identity.
⸻
Conference networking resume strategy
User asked to craft a clean, elegant, technical resume for conference networking at SIGMOD/VLDB using LaTeX.
Resume target:
Main fixes made:
The final LaTeX resume included the following structure:
Shaswat Gupta Research-oriented Software Engineer · Data Systems · ML Systems · Applied Machine Learning Zurich, Switzerland | shagupta@ethz.ch | phone | LinkedIn | GitHub | shaswat.dev
ETH Zürich — MSc Computer Science, Sep 2023–Sep 2025 Focus: Machine Intelligence and Data Management Systems Thesis: 6/6 — provisioning-aware query routing for heterogeneous lakehouse engines. Relevant coursework: Large-Scale AI Engineering, Cloud Computing Architecture, Big Data, Deep Learning, Machine Learning. IIT Bombay — BTech Mechanical Engineering, Jul 2018–Aug 2022 Department Rank 1/165, Gold Medalist, GPA 9.6/10.
Important final resume caveats:
The LaTeX resume draft used the user’s existing template and included polished bullets. The core IBM thesis bullets were:
• Developed a provisioning-aware query router for heterogeneous lakehouse deployments, routing queries across Spark and PrestoDB under latency, memory, and cloud-cost constraints. • Achieved 22–70% cost reduction over best fixed-engine baselines by combining learned latency prediction with spill-free memory prediction; extended paper submitted to VLDB. • Introduced the spill-free memory threshold, a cross-engine abstraction that maps heterogeneous memory telemetry into a billing-aligned provisioning unit. • Built deterministic telemetry-inversion adapters for Spark and PrestoDB to reconstruct query-level memory requirements from engine-internal execution signals. • Implemented a GNN-based learned cost model with a shared query-plan encoder and engine-specific heads, jointly predicting execution time and peak memory with median Q-error ≈ 1.1 at 10–20 ms inference latency.
⸻
General style principles established
⸻
Most important final LinkedIn content snippets
Headline
| Software Developer @ IBM Research Zürich | ML & Data Systems | ETH MSc CS |
About
I am a Software Developer at IBM Research Zürich and recently completed my MSc in Computer Science at ETH Zürich. My work sits at the intersection of data systems, ML systems, and applied machine learning, with recent research on provisioning-aware query routing for heterogeneous lakehouse engines. My ETH thesis received a 6/6; a related workshop paper was accepted at SIGMOD, and an extended version is under review at VLDB. Previously, I worked as a Data Scientist at AB InBev, building forecasting, recommender, and optimization systems for supply-chain and commercial analytics. I graduated Department Rank 1 and Gold Medalist from IIT Bombay, with a parallel background in journalism and technical communication.
ETH Education
ETH Zürich Master of Science — Computer Science Sep 2023 – Sep 2025 Focus: Machine Intelligence; Data Management Systems Thesis: 6/6 — provisioning-aware query routing for heterogeneous lakehouse engines
IIT Education
Indian Institute of Technology Bombay Bachelor of Technology — Mechanical Engineering 2018 – 2022 Grade: Department Rank 1 / 165 · GPA 9.6/10 · Gold Medalist Activities and societies: Editor, Student Journalism Wing; Project Leader, Data Analytics Team; debating; public speaking; technical competitions.
AB InBev full-time
AB InBev — Growth Analytics Center | Data Scientist | Aug 2022 – Aug 2023 • Built logistics forecasting and route-optimization systems for US supply-chain analytics across 2,000+ distribution routes. • Developed ensemble time-series models using Prophet, SARIMAX, XGBoost, and classical forecasting methods, improving forecast accuracy by 15%. • Built a Gurobi/PuLP integer-programming optimizer and scenario simulator for logistics cost-to-serve planning. • Delivered $2.4M in annual savings, led a 3-analyst enhancement squad, and received AB InBev’s Pint and Pitcher awards.
AB InBev internship
AB InBev — Growth Analytics Center | Data Science Intern | May 2021 – Jul 2021 • Built an SVD/NMF recommender system for cross-selling across 18,500+ Tanzanian retailers. • Designed interaction scoring and evaluation metrics for precision, recall, diversity, novelty, and coverage, improving performance by 30% over existing baselines. • Supported $6M in projected annual sales growth; selected as Best Intern among 100+ peers and offered a full-time Associate ML Engineer role.
ETH RA
ETH Zürich (D-MTEC) | Research Assistant | Mar 2024 – Aug 2025 • Built statistical and NLP pipelines for ETH-Zühlke AI-adoption research across 600+ enterprises, automating 10,000+ statistical tests and 2,600+ visualizations. • Engineered a concurrent multi-format document-processing system for 20,000+ Unicode Technical Consortium documents, achieving 94% extraction success and 42% lower LLM API costs. • Developed an asyncio-based semiconductor patent analytics platform for 10,000+ patents, using BERTopic, Sentence Transformers, UMAP, and HDBSCAN to identify 80+ technology clusters.
Protium
Growth Source Financial Technologies (Protium) | Data Science Intern | Apr 2020 – Jul 2020 • Built a linear-programming framework for MSME debt refinancing, modeling feasible loan-consolidation options using collateral appreciation. • Developed a loan recommendation system ranking refinancing options across 350+ client portfolios. • Prototyped geospatial sales-territory clustering for six metropolitan markets and built yield-tracking analytics across 600+ bond securities.
World Bank/KPMG
World Bank Group × KPMG India | Summer Associate | Apr 2021 – May 2021 • Developed 10-year green-hydrogen demand models across three countries, analyzing end-use demand across manufacturing, energy, and mobility sectors. • Compared conventional fuels with cleaner alternatives on technical feasibility and economic viability. • Built a market-readiness framework using renewable-energy policy, planned industrial capacity, and corporate sustainability signals.
ISB
Indian School of Business — Max Institute of Healthcare Management | Research Assistant | Aug 2020 – Nov 2020 • Modeled SARS-CoV-2 transmission risk in agricultural market systems under Prof. Sarang Deo at ISB’s Max Institute of Healthcare Management. • Analyzed grain movement across 3,200 agricultural markets serving 12,800 villages. • Built geospatial datasets and adapted regression/SIR-style models to study procurement-network risk during COVID-19.
Projects: SimpleSleepNet
SimpleSleepNet: Self-Supervised Learning for EEG Sleep Staging Associated with ETH Zürich Built a lightweight contrastive-learning framework for EEG sleep-stage classification, optimized for limited-label medical signal settings. Achieved 80%+ accuracy with a 200K-parameter model and evaluated 13 EEG signal augmentations across amplitude, frequency, temporal, noise, and masking transformations.
Projects: DeepSleepBench
DeepSleepBench: Neural Representations for EEG Associated with ETH Zürich Benchmarked contrastive, masked-prediction, and hybrid self-supervised objectives for EEG sleep-stage classification. Compared CNN, CNN+Attention, and Transformer backbones; CNN+Attention with contrastive objectives produced the strongest representations in the benchmark.
Awards descriptions
Letter of Distinction, Large-Scale AI Engineering — ETH AI Center, 2025 Recognized for the ETH Large-Scale AI Engineering course, involving hands-on distributed training on CSCS Alps. Department Rank 1 & Gold Medalist — IIT Bombay, 2022 Graduated Rank 1 of 165 students in Mechanical Engineering. Institute Academic Award — IIT Bombay, 2021 Awarded to two students for highest academic performance during the year. KC Mahindra Scholarship — Mahindra & Mahindra, 2023 Scholarship for graduate studies abroad. OPJEMS Scholarship — Jindal Group, 2021 Selected among three IIT Bombay recipients for academic and leadership record. Heyning-Roelli Scholarship — Heyning-Roelli Foundation, 2022 Scholarship supporting international exchange at ETH Zürich. Journalism Color — IIT Bombay, 2022 Institute award for contribution to student journalism; one of two recipients selected that year.
Volunteering
Editorial Board Member Insight, IIT Bombay Apr 2022 – Mar 2023 • Led a 20-member editorial board for IIT Bombay’s official student media platform, coordinating reporting across campus issues, student life, and institutional affairs. • Managed editorial workflows, stakeholder communication, and long-form writing for a 10,000+ student community. Project Leader Data Analytics and Visualization Team, IIT Bombay Apr 2021 – Mar 2022 • Led student analytics projects using survey data, statistical analysis, and visualization to support institute-level reporting. • Analyzed 1,400+ COVID-era student responses and 500+ graduate admissions outcomes, publishing reports and dashboards for the campus community.